Contract No: FCS 53-3198-6-025

Use of Biometric Technology to Reduce

Fraud in the Food Stamp Program

USE OF BIOMETRIC IDENTIFICATION TECHNOLOGY

TO REDUCE FRAUD IN THE FOOD STAMP PROGRAM:

FINAL REPORT

December 1999

Authors:

Paul J. Sticha

R. Lewis & Company, Inc.

David Thomas

Chris Zamberlan

Caliber Associates

Monica A. Gribben

R. Lewis & Company, Inc.

Submitted to:

U.S. Department of Agriculture

Food and Nutrition Service

3101 Park Center Drive

Alexandria, VA 22302

Project Officer:

Sharron Cristofar

Submitted by:

R. Lewis & Company, Inc.

1235 Jefferson Davis Highway

Suite 606

Arlington, VA 22202

Project Director:

Paul J. Sticha
NON-DISCRIMINATION POLICY

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and

activities on the basis of race, color, national origin, gender, religion, age, disability, political

beliefs, sexual orientation, or marital or family status. (Not all prohibited bases apply to all

programs.) Persons with disabilities who require alternative means for communication of

program information (Braille, large print, audiotape, etc.) should contact USDA’s TARGET

Center at (202) 720-2660 (voice and TDD).

To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room 326-W,

Whitten Building, 14th and Independence Avenue, S.W., Washington D.C. 20250-9419 or call

(202) 720-5964 (voice and TDD). USDA is an equal opportunity provider and employer.
i

ACKNOWLEDGMENTS

The authors acknowledge the contributions of the State officials who shared their time and

knowledge with us, and provided us much of the information that is summarized in this report.

Officials from Arizona, California, Connecticut, Illinois, New Jersey, New York, and Pennsylvania

participated in 1-2 hour interviews to discuss all phases of their projects. In an earlier task, we

conducted site visits to San Antonio, Texas to observe the Lone Star Image System

demonstration and to interview State and county agency staff. In addition to participating in the

survey, the State representatives provided written documentation and were available to answer

many follow-up questions to clarify the accomplishments of their offices.

We also thank Sharron Cristofar, the project officer from Food and Nutrition Service, who

provided guidance throughout the project. This report has benefited from the thoughtful

comments of Steven Carlson and Cecilia Fitzgerald. Judith Barokas, of Consulting Research and

Information Services, developed the interview guides used for the client advocate interviews.
ii
iii

TABLE OF CONTENTS

EXECUTIVE SUMMARY....................................................................................................... vii

1. INTRODUCTION ................................................................................................................1

1.1 Increasing the Integrity of the Food Stamp Program.................................................1

1.2 Biometric Identification in Social Services................................................................2

Expansion of Biometric Identification...................................................................3

Assistance Programs Subject to Biometric Requirements......................................5

1.3 Organization of This Report.....................................................................................5

2. STATE INTERVIEWS.........................................................................................................9

2.1 State Selection and Data Collection Methods...........................................................9

2.2 Interview Results: Planning and Implementation.....................................................10

Impetus and Technology Selection .....................................................................10

State Planning Activities.....................................................................................10

Implementation ..................................................................................................12

Modifications to State Systems...........................................................................14

Organization and Staffing...................................................................................15

Vendor Role ......................................................................................................15

Staff Preparation and Training............................................................................16

Informing Clients and the General Public............................................................17

2.3 Interview Results: Policy and Procedure ................................................................17

Mandatory Participants and Exemptions.............................................................18

Match Response.................................................................................................20

Binning and Filtering..........................................................................................21

2.4 Interview Results: Ongoing Operations..................................................................22

Types of Matches and Investigations..................................................................22

Office and Client Burden....................................................................................22

Technical Problems............................................................................................23

3. IMPACT OF FINGER IMAGING ......................................................................................25

3.1 Detected Fraud ......................................................................................................26

3.2 Refusals to Comply with Finger-image Requirements.............................................28

3.3 Reduction in Applications or Caseload...................................................................31

3.4 Summary ...............................................................................................................33
iv

4. DETERRENT EFFECTS OF FINGER IMAGING ON ELIGIBLE INDIVIDUALS ..........35

4.1 Client Reactions.....................................................................................................35

4.2 Former Client Interviews........................................................................................37

4.3 Client Advocate Opinions ......................................................................................37

4.4 Summary ...............................................................................................................39

5. COST ANALYSIS OF FINGER IMAGING IN THE FSP..................................................41

5.1 Review of State Costs Estimates............................................................................41

5.2 Elements of Implementation and Operating Cost....................................................43

5.3 Quantifying the Benefits of Finger Imaging ............................................................45

5.4 Summary ...............................................................................................................46

6. SUMMARY, CONCLUSIONS, AND DISCUSSION.........................................................49

6.1 Summary of Findings.............................................................................................49

6.2 Biometric Technology, Welfare Reform and Assessment of Duplicate Participation50

6.3 Future Developments.............................................................................................52

REFERENCES .........................................................................................................................53

APPENDIX A. STATE STAFF INTERVIEW GUIDE..........................................................A-1

APPENDIX B. PROFILES OF STATE FINGER-IMAGING SYSTEMS.............................B-1

APPENDIX C. REPORT OF CLIENT ADVOCATE INTERVIEWS....................................C-1

APPENDIX D. CLIENT ADVOCATE INTERVIEW PROTOCOL ......................................D-1

List of Tables

Table 1. Enabling Legislation for Biometric Systems ............................................................... 11

Table 2. Start-Up and Implementation Description .................................................................. 13

Table 3. Mandatory Participants by Assistance Program and Allowable Exemptions ................ 19

Table 4. Match Response Time................................................................................................. 21
v

Table 5. Finger-image Matches Attributed to Fraud ................................................................. 27

Table 6. Refusals of Existing Cases to Participate in Finger Imaging ........................................ 29

Table 7. Summary of Client Survey Results ............................................................................. 36

Table 8. Three-Year Cost Estimates for Finger Imaging .......................................................... 42

Table 9. Cost Elements Included in State Estimates.................................................................. 44

List of Figures

Figure 1. Current and planned biometric identification systems in the U.S. (November 1998)......7

Figure 2. Food Stamp and TANF/AFDC households, 1993-1997 ............................................. 32
vi
vii

EXECUTIVE SUMMARY

Biometric identification technology provides automated methods to identify a person

based on physical characteristics—such as fingerprints, hand shape, and characteristics of the eyes

and face—as well as behavioral characteristics—including signatures and voice patterns.

Although used in law enforcement and defense for several years, it has recently been used in

civilian applications and shows some promise to reduce the number of duplicate cases in the Food

Stamp Program (FSP) and other assistance programs (GAO, 1995).

Biometric identification systems are currently operational at some level in Arizona,

California (under county initiative, first by Los Angeles County), Connecticut, Illinois,

Massachusetts, New Jersey, New York, and Texas. Finger imaging is the principal form of

technology used in all eight States, though alternative technologies have simultaneously

undergone trials in Massachusetts (facial recognition) and Illinois (retinal scanning). By the end

of 2000, new systems are expected to be in place in California (statewide unified system),

Delaware, and North Carolina. Other States are currently in the initial planning stages, including

Florida, Maryland, Michigan, Mississippi, Pennsylvania, and South Carolina. However, there is

little information available at this point regarding the specific course and trajectory these States

will follow in terms of system types, implementation schedules, and the benefit programs in which

they will implement the new requirement.

This report provides an overview of the experience of nine States with biometric

identification technologies as of September 1999 and discusses some of the major policy and

operational issues encountered during implementation and testing. The report also synthesizes

available information on the effectiveness of the technology in reducing duplicate participation

and provides a discussion of measurement complexities and issues on the horizon as use of the

technology continues to expand. A companion report (Sticha & Ford, 1999) contains an

overview of biometric identification technology, examining the functional capabilities,

performance, and applications of the various technologies with a particular focus on finger

imaging, the most commonly used and well known.

Telephone interviews of 1-2 hours in duration were conducted in May-June 1998 with

representatives of human service agencies in Arizona, California, Connecticut, Illinois,

Massachusetts, New Jersey, New York, and Pennsylvania. As part of an earlier task of this

study, we conducted site visits to San Antonio, Texas to observe the Lone Star Image System

(LSIS) demonstration and to interview State and county agency staff. Information on Texas is

based on those visits and interviews. The States interviewed, with the exception of Pennsylvania,

have installed biometric identification systems and are requiring applicants to federal and State

benefit programs to submit to the new procedures during the eligibility determination process.

The purpose of the interviews was to explore State experiences with biometric

identification systems, including factors in the decision-making and planning processes, the

dynamics of system start-up and implementation, issues and problems related to system and

agency operations, and perceptions regarding the impact of biometric identification procedures on

the application and eligibility determination processes. Each of the States participating in the
viii

study was asked to provide a description of the critical early events that occurred during the

planning phases of their respective projects. In addition, those States that had already

implemented systems were asked to describe their implementation experiences.

Results of State Interviews

When finger-imaging technology was first applied to reduce multiple participation fraud in

assistance programs, there were many concerns about the performance and reliability of the

technology in a social service application, as well as about the potential stigma that a finger-image

requirement would place on potential clients. The experience of the eight States that have

incorporated finger imaging into the process of applying for welfare assistance suggests that many

of these fears were unfounded. Finger imaging has been readily integrated into the human

services programs of the affected states. However, despite the positive reaction to finger imaging

from the State officials we interviewed, there is still uncertainty regarding the extent to which this

technology can reduce multiple participation fraud.

The States planned for implementation of their biometric identification systems in response

to a wide variety of factors and considerations idiosyncratic to each State environment. Some

States reported that their respective legislative mandates, which prescribed specific dates by which

biometric systems were required to be in place, allowed insufficient time for development and

planning. The States developed and followed implementation schedules in accordance with

internal priorities and considerations. The States uniformly described their implementation

processes as largely uneventful, though they encountered a variety of minor implementation

issues, most of which were associated with the logistical difficulties of mobilizing and managing

such a complex initiative.

Preparing staff for the implementation of the biometric systems, both philosophically and

operationally, took different forms, priorities, and levels of effort in the States. At

implementation, advance notification to clients and/or the general public about new biometric

client identification procedures was considered important by all State representatives. The

objective of providing advance notification was to inform and prepare clients for the additional

application or recertification step (i.e., to explain the requirement and who is required to submit,

and to address client concerns), as well as to accelerate enrollment of the existing caseload. All

States prepared informational mailings to clients advising them of the new requirement. Some

States reported developing additional outreach media including multilingual (English and Spanish)

videos, posters, and brochures for viewing and distribution in the local office. Most of the States

also identified various outlets in the community through which they informed the general public in

advance about the implementation of biometric client identification procedures.

The States with operating systems reported that implementation of new biometric client

identification procedures had a negligible impact on operations at the local office level. In

general, States also reported that the problems and obstacles encountered in operating their

respective projects are not unlike those encountered in demonstrating any new technology or

procedural modification. These States also reported that their systems and procedures were

implemented without unexpected difficulty and were rapidly institutionalized. All the States

confronted a range of basic physical space and logistical issues, including where to situate the new
ix

equipment, how to appropriately alter job descriptions, who to reassign or hire to handle the new

procedures, and how to adjust the flow of clients and paperwork most efficiently. However, none

reported any particularly noteworthy difficulties. States reported that clients have been

cooperative and accepting of the technology.

Finger Imaging and Fraud Reduction

Assessing the ability of finger imaging to reduce fraud is difficult because the amount of

fraud caused by duplicate participation in welfare programs is unknown, and because changes in

caseload after the introduction of finger imaging cannot be interpreted unambiguously as

reduction of fraud. The evaluations of finger imaging systems conducted by six States have

produced the following findings.

• A small number of duplicate applications (approximately 1 duplicate for every 5,000

cases) have been detected by finger imaging systems. Finger-imaging systems appear to

detect more fraud in statewide implementations than in regional pilot systems. Additional

matches have been found by interstate comparisons of finger-image data.

• Institution of a finger-imaging requirement can produce a significant, short-term reduction

in caseload, because some existing clients refuse to comply with the requirement. The

number of refusals depends on the implementation procedures and appears to be lower

when finger imaging is incorporated into the recertification process.

• The most carefully controlled estimate of non-compliance among existing clients suggests

that introduction of a finger-imaging requirement reduces participation by approximately

1.3%. However, this estimate reflects both reduced fraud and deterrence of eligible

individuals and households.

Finger Imaging as a Deterrent to Legitimate Participants

Clients do have some concerns about finger imaging. Roughly 15% expressed concerns in

the State surveys and interviews conducted to evaluate finger-imaging programs. These concerns

center on issues of privacy, unjust treatment of poor people, inconvenience, and fear of

interagency sharing.

There is little data on which to estimate the size of the deterrence effect. Based on the

results from client surveys in five States, a substantial majority of clients had no objection to

finger imaging and thought it was a good idea.

There was little evidence that clients discontinued benefits because they were intimidated

by the finger-image requirement. Interviews with former clients in Texas found that only two of

the 78 former food stamp recipients (both of whom had refused to be imaged) attributed their loss

of benefits to finger imaging. Similar interviews in Los Angeles County found that, of those

former clients interviewed, no one who refused to be finger imaged expressed a concern with the

process.
x

Cost and Effectiveness of Finger Imaging

Since there is no reliable estimate of the magnitude of duplicate participation in the FSP,

there is uncertainty regarding the cost effectiveness of finger imaging. Available data are

inadequate to make precise estimates of either the costs or benefits of finger imaging for the FSP.

Calculations using the data that are available, supplemented by a number of assumptions, suggest

that reduction in caseload covers the costs of finger imaging technology. However, the

percentage of the caseload reduction due to decreased multiple participation is unclear.

The analysis makes no assumption about how costs or benefits are allocated among Federal

or State agencies. In addition, it does not include the cost required to modify existing software to

make it compatible with the finger-imaging system. Finally, it does not take into account that

certain cost elements, such as the cost for infrastructure or centralized equipment, may be

independent of caseload fluctuation.
1

1. INTRODUCTION

This report provides an overview of the experiences of nine States with biometric

identification as of September 1999, and discusses some of the major policy and operational issues

encountered during implementation and testing. The report also synthesizes available information

on the effectiveness of the technology in reducing duplicate participation and provides a

discussion of measurement complexities and issues on the horizon as the use of this technology

continues to expand. A companion report contains an overview of biometric identification

techniques, examining the functional capabilities, performance, and applications of the various

technologies with a particular focus on finger imaging, the most commonly used and well known

(Sticha and Ford, 1999).

1.1 Increasing the Integrity of the Food Stamp Program

The Food Stamp Program (FSP) provided more than $16.9 billion in benefits to over 19

million individuals in 1998. As part of its ongoing effort to increase program integrity, the Food

and Nutrition Service (FNS) monitors the level of food stamp overpayments and has developed

and promoted procedures to prevent households from obtaining benefits to which they are not

entitled.

The overall level of food stamp overpayment is estimated by FNS in its annual quality

control review. Summarizing these reviews, the General Accounting Office (GAO, 1997, 1998a)

reported that households receive more benefits than they are entitled to in approximately 15% of

all food stamp cases; these overpayments represent 7% of the benefits that are issued.

Approximately one-quarter of these overpayments were judged to be caused by intentional

program violations by clients (GAO, 1994). The report enumerates four potential sources of

fraud, waste, and abuse in the FSP: (1) The eligibility and benefit determination process, (2) the

use of benefits for nonfood purposes, (3) counterfeiting of food stamp coupons or their use by

unauthorized individuals, and (4) theft or loss of coupons in the mail.

Until recently, investigation of questionable information given by an applicant for food

stamps was a labor-intensive activity that often severely taxed the capabilities of local welfare

offices (GAO, 1997). Furthermore, the resulting information—based on interviews with

employers, landlords, friends and neighbors of the applicant—was often of limited reliability.

Recent technological advances have provided tools that can be used to make fraud more

difficult to commit and easier to detect. For example, the Income Eligibility Verification System

(IEVS), established in 1986, required that case records be matched with six external data bases.

Relevant data bases may contain information about wages, income taxes, unemployment insurance

benefits, or other information that can be used to verify the income or assets of a recipient or

applicant household. A study sponsored by FNS established the cost-effectiveness of IEVS when

appropriate targeting methods were used (Maxfield & Allin, 1995). GAO (1997, 1998b) has

suggested other data bases that can be used to verify the legitimacy of an application for food

stamp aid. These data bases include death records maintained by the Social Security

Administration (GAO, 1998b) and records of prison inmates (GAO, 1997). Comparison of case
2

records to the information in these data bases can help ensure that ineligible individuals are not

included as members of the recipient or applicant household.

The Food Stamp Act as amended [7 CFR 272.4(f)(1)] requires each State agency to

establish a system to assure that no individual participates in the FSP more than once a month, in

more than one jurisdiction, or in more than one household within the State. The system

established to identify such individuals must use identifiers such as names and social security

numbers at a minimum, and may use other identifiers, as the State agency deems appropriate.

Under 7 CFR 272.4(f), the use of finger images and other non-intrusive biometric identifiers is

permissible in fulfilling this requirement.

There are many ways an individual can commit program fraud using duplication of

identity. An individual can apply for and receive concurrent benefits from more than one program

when, in fact, he or she is ineligible or would be eligible for a lower benefit amount, for example.

More specifically, a recipient of benefits under the Temporary Assistance to Needy Families

(TANF) program who is eligible for a fairly low food stamp benefit may apply for food stamps

under another identity, thus fraudulently obtaining the full TANF benefit and the full FSP benefit.1

To create a fictitious identity, one needs a false birth certificate—created with a fictitious name—

to obtain secondary identification documents from issuing agencies. With these documents, a

person has sufficient identification to obtain assistance concurrently in multiple cases without fear

of detection.

Recent developments in biometric identification technology have potential to provide

positive identification of applicants and recipients of food stamp benefits, and consequently reduce

the level of fraud in the program. This technology provides automated methods to identify a

person based on physical characteristics—such as fingerprints, hand shape, and characteristics of

the eyes and face—as well as behavioral characteristics—including signatures and voice patterns.

Although these technologies have been used in law enforcement and defense for several years,

they have recently been used in civilian applications and show some promise to reduce fraud in the

FSP and other assistance programs (GAO, 1995). This technology has the potential to identify

individuals who attempt to apply for benefits on more than one case, or who attempt to obtain

benefits belonging to someone else.

1.2 Biometric Identification in Social Services

Following a 1983 California Superior Court ruling that prohibited human services agencies

in Los Angeles County from denying aid to applicants without identification, the Los Angeles

County Department of Public Social Services (DPSS) began exploring the use of biometric

identification technology to confront and eradicate the potential for duplicate case fraud

 

1

Passage of the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) in 1996

dismantled the old Aid to Families with Dependent Children (AFDC) program and replaced it with a timelimited cash assistance program called Temporary Assistance for Needy Families (TANF). The effect of the

legislation was to revoke the entitlement status of the old AFDC program and return administrative control of

basic welfare services to the States, which are now free to design services within broad, federal parameters.

AFDC is used in this report to reference cash assistance prior to implementation of TANF.
3

(DePompa 1997). In 1991, embarking on the first demonstration of its kind in a non-law

enforcement environment, DPSS, in cooperation with Electronic Data Systems (EDS),

implemented the Automated Fingerprint Image Reporting and Match (AFIRM) system and began

fingerprinting all applicants to the county’s General Relief (GR) program, which dispenses

financial assistance to families ineligible for federal or State assistance programs.

Under an agreement with the California Department of Social Services, and with matching

funds from the U.S. Department of Health and Human Services (DHHS), a three-year project

beginning in April 1994 expanded the requirement to the Aid to Families with Dependent Children

program. A review of the AFIRM project conducted by the department’s Office of the Inspector

General (OIG) in 1996 found that the system generated considerable savings that were attributed

to the discontinuance of AFDC and food stamp benefits to a large number of cases in LA County.

The county estimated its total savings to be $86 million (accounting for operating costs), with net

savings estimated to be $66 million. The OIG report indicates that the AFIRM system also had

benefits in the detection of other types of welfare fraud. While investigating a sample of 137

cases in which persons for whom fingerprinting was required failed to show, the county found

evidence of non-multiple case fraud in 63 cases (46% of the cases). These forms of fraud

included concealing income and misrepresenting household composition (DHHS OIG, 1996).

Expansion of Biometric Identification

Since the Los Angeles County experiment, the technological landscape has become more

complex and competitive with the emergence and continuing refinement of alternative biometric

applications, including hand geometry, iris recognition and retinal scanning, voice recognition, and

facial imaging (Lazar, 1997). Encouraged by the performance of the AFIRM system, a number of

other States began exploring the feasibility of finger imaging as well as alternative systems,

pursued enabling legislation, selected systems, and began implementing selected systems in

accordance with legislative mandate.2 In the wake of the AFIRM experiment, seven States

implemented biometric identification systems, chronologically as follows:

• The New York Department of Social Services, under contract with Sagem-Morpho,

implemented its Automated Finger Imaging System (AFIS) in 38 counties in June 1995,

began an expansion throughout the rest of the State in August 1995, and had a statewide

finger imaging system in place by January 1996.

• The New Jersey Department of Human Services, under contract to The National Registry,

followed in July 1995 with implementation of its Recipient Identification Program (RIP),

which is currently operating in an experimental phase in portions of the northern tier of the

State.

 

2 The State of California functions under a State-administered, county-operated system in which six counties

followed LA County and implemented biometric systems independently, with State approval. However,

interviews for this study were conducted only at the state level; this report, therefore, does not include

information specific to each of California’s seven counties that currently have independently operating systems.
4

• The Connecticut Department of Social Services implemented its Digital Imaging System

in January 1996, under contract to the Polaroid Corporation (formerly NBS Imaging

Systems) and The National Registry, and completed a statewide roll-out the following

September.

• The Massachusetts Department of Transitional Assistance implemented finger imaging

and facial recognition technology in April 1996, under contract to Viisage Technology,

with a subcontract to The National Registry specifically for the finger imaging component,

and currently is the only State experimenting with a dual platform system.

• The Illinois Department of Human Services implemented its Retinal Identification System

(ISCAN) in May 1996 (discontinued in March 1998), and its Automated Identification and

Match System (AIMS), a finger imaging system, in February 1997, under contract to

Printrak International.

• The Texas Department of Human Services implemented its Lone Star Image System

(LSIS) in October 1996, under contract to Sagem-Morpho, as a two-county

demonstration in the San Antonio metropolitan area (Bexar and Guadalupe). Statewide

implementation of the system was completed in August 1999.

• The Arizona Department of Economic Security implemented the Arizona Fingerprint

Imaging Program (AFIP) in January 1998, under contract to Sagem-Morpho, and

completed a rapid statewide roll-out by July 1998.

As of September 1999, two States were in the very late planning stages and were preparing for

implementation, including:

• In California—a State-administered, county-operated State in which seven counties

implemented biometric systems independently with State approval since 1991—the

California Department of Social Services awarded a contract to implement a statewide,

unified finger imaging system covering all 225 counties in September 1999. Contract

award had been delayed after the request for proposals (RFP) was released in 1997,

recalled, and reissued in 1998.

• The Pennsylvania Department of Public Welfare, which released its original request for

proposals in January 1997 and encountered legal challenges, now expects to release a new

RFP for the Pennsylvania Automated Recipient Identification System (PARIS), a finger

imaging system, by January 2001.

As of September 1999, five States had biometric identification systems operating statewide,

including Arizona, Connecticut, New York, and Texas, which have finger imaging systems, and

Massachusetts, which has a statewide facial matching system in operation. California, Illinois, and

New Jersey currently have systems operating at a pilot capacity in a limited number of

jurisdictions.
5

Other States are currently in the initial planning stages, including Delaware, Florida,

Maryland, Michigan, Mississippi, North Carolina, and South Carolina; however, there is little

information available at this point regarding the specific course and trajectory these States will

follow in terms of system types, implementation schedules, and the benefit programs in which they

will impose the new requirement. This report focuses on the experiences to date of, and the

current activity underway in, a number of front-running States. The current status of biometric

identification systems in food and income assistance programs in the U.S. is presented in Figure 1.

Assistance Programs Subject to Biometric Requirements

Only in Massachusetts (facial matching only) and certain demonstration counties in

California are applicants to each of the major federal and State food and income assistance

programs—the Food Stamp, TANF, and General Assistance programs—currently subject to new

biometric client identification procedures.

Food Stamp Program: As of September 1999, applicants for food stamps in five States

with biometric identification systems in operation at some level—Arizona, California (LA County

as well as six other counties with county-operated systems), Massachusetts, New York, and

Texas—were required to submit to new client identification procedures. Food stamp applicants in

Connecticut, Illinois, and New Jersey are not currently required to comply. Both California (as it

assimilates all of its counties under one unified statewide system) and Pennsylvania plan to require

food stamp applicants to submit to finger imaging procedures when those systems become

operational.

TANF and General Assistance: Applicants for cash assistance under the Temporary

Assistance for Needy Families (TANF) program are required to submit to new client identification

procedures in seven States with systems in operation, including Arizona, California, Connecticut,

Illinois, Massachusetts, New York, and Texas; only TANF applicants in New Jersey currently are

not. Applicants for General Assistance (GA) are required to submit to new identification

procedures in five States, including California, Connecticut, Massachusetts, New Jersey, and New

York; applicants for general assistance in Arizona, Illinois, and Texas are not required to comply.

1.3 Organization of This Report

The remainder of this report summarizes the information obtained from the States and

synthesizes it to assess three issues that are important in determining the effectiveness of fingerimaging technology to reduce duplicate participation fraud in the FSP. It begins with a summary

of the State interview results, highlighting the activities involved in planning and implementation

of the systems, the policies and procedures governing their use, and their impact on the ongoing

operation of the affected assistance programs. The report then addresses three effectiveness

issues, including the ability of finger-imaging technology to reduce duplicate participation fraud,

the extent to which the technology may deter participation by eligible households, and the costs

required to implement and operate such systems. The discussion of these issues is based primarily

on supporting documentation provided by the States in conjunction with the interviews. The

report concludes with a discussion of measurement complexities and issues on the horizon as the

technology continues to proliferate. Several appendices present supporting information, including
6

interview guides, profiles of the biometric systems planned or in use in the nine States from which

information was obtained, and details of interviews that were conducted with client advocates

regarding the LSIS pilot in Texas.
IGURE

URRENT AND LANNED IOMETRIC DENTIFICATION YSTEMS IN HE

EPTEMBER

F 1

C P B I S T U.S.

(S 1999)

* Use of biometric identification systems in California began under county initiative in Los Angeles County; six other counties have since followed,

including Alameda, Contra Costa, Orange, Sacramento, San Diego, and San Francisco counties. A unified, statewide system is

expected in FY01.

States With Operating Systems

States Planning To Implement Systems

States Planning For Future Systems

STATES PLANNING FOR FUTURE

BIOMETRIC IDENTIFICATION SYSTEMS

Florida

Maryland

Michigan

Mississippi

Pennsylvania

South Carolina

California (statewide system)

Delaware

North Carolina

STATES PLANNING TO

IMPLEMENT SYSTEMS IN FY00

(as of September 1999)

(as of September 1999)

STATES WITH OPERATING BIOMETRIC IDENTIFICATION SYSTEMS

STATE SYSTEM TYPE START UP STATUS BENEFIT PROGRAM

Arizona Finger Imaging January 1998

California*

LA County Finger Imaging April 1991

New York Finger Imaging June 1995

Retinal Scanning Discontinued Eye Dentify

National Registry

Finger Imaging April 1996 National Registry

(as of September 1999)

SAGEM-MORPHO TANF, FSP

VENDOR

Electronic Data Systems TANF, FSP, GR

NBS Imaging TANF, GA

PRINTRAK TANF

VIISAGE TANF, FSP, GA

National Registry GA

SAGEM-MORPHO TANF, FSP, GA

SAGEM-MORPHO TANF, FSP

Statewide

County-wide

Statewide

Statewide

Pilot

Statewide

Pilot

Pilot

Statewide
8
9

2. STATE INTERVIEWS

This study was designed to include three principal components: (1) Evaluation support

for the Lone Star Image System (LSIS) demonstration in Texas, (2) Interviews with technology

vendors to focus on capabilities and applications of biometric identification technology to the

Food Stamp Program, and (3) Interviews with a sample of State agency representatives in the

lead in experimentation and testing of these technologies, with a focus on implementation and

operational issues. The project team conducted site visits to offices of the Texas Department of

Human Services in Austin, as well as to the demonstration offices in San Antonio, in December

1996 and June 1997. The purpose of the visits was to observe LSIS and to conduct interviews

and focus groups with operators, eligibility workers, and supervisors, and where possible, with

staff in the investigative divisions of the local offices. Interviews with technology vendors were

conducted in 1997, the results of which were published in a companion report in April 1998

(Sticha and Ford, 1999).

2.1 State Selection and Data Collection Methods

As the study began, FNS had been tracking State activity regarding use of biometric

identification technology in their human services programs; that information served as the starting

point for selecting States to participate in the State agency interviews. Other candidate States

were identified from multiple sources, including technology conferences, as well as the Biometrics

in Human Services User Group (BHSUG) Newsletter. Nine states were originally selected to

participate. One state (North Carolina) declined to participate, because, at the time the invitation

was extended, the State was in a very early planning stage and believed its potential contribution

would be limited.

Following the first visit to observe LSIS in San Antonio, the project team began

developing an interview guide to collect systematic information from States selected to participate

in the study. Telephone interviews of 1-2 hours in duration were arranged and conducted in MayJune 1998 with State-level staff in Arizona, Connecticut, Illinois, Massachusetts, New York, New

Jersey, California, and Pennsylvania. Similar information requested from these States by

telephone was collected during site visits to Austin and San Antonio; information on Texas

contained in this report is based on those visits. The interview guide to which all other States

responded appears in Appendix A.

The purpose of interviews was to explore State experiences with biometric identification

systems, including forces in the decision-making and planning processes, the dynamics of system

start-up and implementation, issues and problems related to system and agency operations, and

perceptions regarding the impact of biometric identification procedures on the application and

eligibility determination processes. It is important to point out that each State’s situation is

unique. Four of the States interviewed have systems currently in operation statewide, while

others continue to operate at a pilot level; two States included in the study are in the late planning

stages. In addition, State staff play different roles vis-à-vis their respective vendors. Information

available and provided by the States during interviews reflects conditions and circumstances

specific to each State environment. With that in mind, this summary presents a discussion of the
10

more critical issues that apply across all participating States and around which meaningful

summary observations are possible. Individual State profiles, appearing in Appendix B, present

more detailed information about each State’s specific status and circumstances.

2.2 Interview Results: Planning and Implementation

Each of the States participating in the study was asked to provide a description of the

critical early events that occurred during the planning phases of their respective projects. In

addition, those States that had already implemented systems were asked to describe their

implementation experiences.

Impetus and Technology Selection

State law mandated biometric identification systems in each of the States in the study.

Finger imaging was selected in each of the States, either alone or as one of two selected systems.3

Not all States passed legislation mandating finger imaging specifically. Connecticut's Department

of Social Services, for example, was charged with reviewing existing technology, and, to the

greatest extent possible, selecting a system compatible with systems in place in-State and in

surrounding States. On the other hand, Illinois' legislation was very specific and required finger

imaging.

The States reported that finger imaging technology was selected because of its long track

record in other applications, its relative cost-effectiveness, and its accuracy. Table 1 identifies

Web sites available for the State agencies in the study, some of which contain text of the enabling

legislation.

State Planning Activities

The States planned for implementation of their biometric identification systems in response

to a wide variety of factors and considerations specific to each State environment. A number of

States reported that their respective legislative mandates, which prescribed dates by which

biometric systems were required to be in place, allowed for insufficient time for development and

planning.

In New Jersey, the planning process was initiated in March 1994 when the Department of

Human Services formed a work group—constituted of various members within the Division of

Family Development—to assemble a request for proposal (RFP) and to select a vendor. The RFP

was released in September 1994, followed by a bidder’s conference in November 1994. The

department considered bids from four vendors, from which it selected the three lowest bidders to

conduct a benchmark test that would serve as the basis for a final selection. The benchmark

allowed the department to observe the performance of each bidder,

 

3

Illinois elected to test retinal scanning in addition to finger imaging, while Massachusetts elected to test facial

matching simultaneously with finger imaging.
11

Table 1

Enabling Legislation for Biometric Systems

STATE ENABLING

LEGISLATION

STATE LEGISLATION

WEB SITE AGENCY WEB SITE

Arizona Title 46,

Section 217

Title 46,

Section 218

http://www.azleg.state.az.us

/ars/ars.htm

Http://www.de.state.az.us

California Welfare and

Institutions Code,

Section 10830

http://www.leginfo.ca.gov

/calaw.html

Http://www.dss.cahwnet.gov/

Connecticut PA 96-176 http://www.cslnet.ctstateu.edu

/psindx96/psind017.htm#I1

Http://www.dss.state.ct.us

/digital.htm

Illinois PA 88-554

PA 90-017

http://www.legis.state.il.us

(No bill text presently available online.)

Http://www.state.il.us

/agency/dhs

Massachusetts Chapter 5,

Section 115

(Acts of 1995)

http://www.magnet.state.ma.us

/legis/laws/mgl/index.htm

Http://www.state.ma.us

/eohhs/agencies/dta.htm

New Jersey P.L. 1947, c.156

P.L. 1983, c.85

http://www.njleg.state.nj.us Http://www.state.nj.us

/humanservices/DFD.html#G

A

New York Chapter 55,

Article 5,

Title 1,

Section 139-a

http://assembly.state.ny.us

/cgi-bin/claws?law=108&art=23

Http://www.dfa.state.ny.us/

Pennsylvania Act 1994-49,

Section 414;

Act 1995-20,

Section 414

(amended)

http://www.pasen.gov

(No bill text presently available online.)

Http://www.state.pa.us

/PA_Exec/Public_Welfare

/overview.html

Texas H. R. Code,

Chapter 31,

Title 2,

Subtitle C,

Section 31.0325

http://www.capitol.state.tx.us

/statutes/codes/HR000007.html

Http://www.dhs.state.tx.us/
12

as demonstrated by response speed and accuracy, on a sample of 100 “cards,” or sample clients.

A final decision was rendered on both performance and cost considerations.

In Connecticut, legislation passed in 1995 specifically required the Commissioner of Social

Services to examine available biometric identifier systems—defined as any system which allows

for recognition of an individual through retinal scanning, finger imaging, hand geometry, or facial

recognition—and, to the greatest extent possible, select a system that is compatible with the

systems in surrounding States. During this exploratory phase, the Department of Social Services

(DSS) invited vendors in for demonstrations, while also conducting visits to New York and New

Jersey to observe field operations and to consult with State personnel. Finger imaging was found

to be accurate, clean, and quick. The commissioner was also authorized in the legislation “to

enter into a memorandum of understanding with the State’s Department of Motor Vehicles

(DMV), permitting the DMV to provide the hardware, software, equipment maintenance,

technical training, and other necessary resources. DSS and DMV, which had a vendor under

contract at the time for licensing services, amended the vendor’s contract to enable it to develop a

similar technical platform for DSS.

In Arizona, following passage of enabling legislation in 1994, the accounting firm of Ernst

& Young (which conducted an evaluation of the Los Angeles County AFIRM demonstration) was

commissioned to conduct a cost-benefit analysis of using biometric technology. Predictive models

were developed under three scenarios, including conditions under which the biometric platform is:

(1) owned in its entirety by the State, (2) jointly owned by the State and by a vendor, and (3)

owned in its entirety by the vendor. Within Arizona’s Department of Economic Security, the

planning process included three principal components, including an analysis of in-State operations

(particularly a review of finger imaging as it existed at the time in the State’s Department of

Public Safety), a review of activities in other jurisdictions (e.g., New York, Los Angeles County,

Pennsylvania, and Washington), and an examination of all previous studies on the issue of welfare

fraud in Arizona.

Implementation

The States uniformly described their implementation processes as largely uneventful,

though they encountered a variety of minor implementation issues, most of which were associated

with the logistical difficulties of mobilizing and managing such a complex initiative. Table 2

provides a brief summary of startup and implementation activities. In New York, vendor staff had

to learn quickly to understand the State’s social services environment, with which it was

previously unfamiliar. States conducting mass call-ins to enroll their existing caseloads as quickly

as possible, such as New York and Texas, faced the problems of scheduling and the difficulties

associated with overflow in the local offices. Some States, including New York, Texas, and New

Jersey, identified image quality control as a particularly important issue in the initial months of

implementation. In New York, where 400,000 clients were imaged in a period of three months,

the Department of Social Services reported that it had to conduct additional training for operators

to increase image quality control.
13

Table 2

Start-Up and Implementation Description

STATE CURRENT STATUS

INITIAL

START-UP

IMPLEMENTATION DESCRIPTION

Arizona Statewide January 1998 3-month pilot began in 10 offices in three counties (La

Paz, Mojave, and Yuma) in rural District IV. System

operational in one-third of State by May 1998; system

completely rolled out by July 1998.

California* Systems implemented

at county initiative

with State approval.

The State of California

is currently planning

for a unified, Statewide

system

Los Angeles

County started

the AFIRM

system in 1991,

followed by six

other counties

Alameda – finger imaging

Contra Costa – finger imaging

Los Angeles – finger imaging

Orange – finger imaging

Sacramento – hand geometry

San Diego – finger imaging

San Francisco - finger imaging

Connecticut Statewide January 1996 State’s five regional offices were divided over three

implementation phases, beginning in the North Central

Region. In first two months, workstations and

communications with the central site were established

in 16 DSS offices and 20 general assistance sites.

Illinois Pilot (finger imaging) February 1997 AIMS, the State’s finger imaging system, began in

DuPage, Western, and West Suburban offices. ISCAN,

the State’s retinal scanning system, began in Alton and

Granite City (Madison County); ISCAN has since been

discontinued.

Massachusetts Pilot (Finger)

Statewide (Facial)

April 1996 Finger imaging pilot began in three offices, two in

Springfield and one in Lawrence. Facial matching

began in 39 offices within first 30 days; now statewide.

New Jersey Pilot July 1995 Pilot began in northern tier of the State, including the

Trenton area. A statewide rollout has been funded, but

not yet initiated.

New York Statewide June 1995 Two-county demonstration began in 1992. Legislation

expanded to 12-county demonstration, giving other

counties the option of joining. In June 1995, began

with 38 of 58 counties (including New York City), with

a statewide rollout completed in January 1996.

Pennsylvania Planning Unknown

Texas Pilot October 1996 Pilot began in Bexar and Guadalupe counties in the

San Antonio area. The area was selected because of its

proximity to DHS headquarters, its mix of urban and

rural counties, its record of performance in past

initiatives, and the implementation of other pilots in

alternative areas. The San Antonio area was affected

by some other initiatives including a demonstration of

AFDC time limits in Bexar County in May 1996.

Statewide rollout of LSIS, originally scheduled for

October 1997, was postponed and was not completed

until August 1999.

* Information for this study was supplied by State-level staff; it was not possible to interview each county in

California. Source for county-level information in California: Connecticut Department of Social Services

(1998).
14

Modifications to State Systems

A number of implementation issues arose in each State regarding the automated systems

on which case management functions depend. Whether and precisely how to modify the State

automated case management systems was the basic issue to be resolved. First, should the

biometric system database stand alone—leaving the agency at risk for data entry errors and the

burdens of a routine reconciliation process—or should the State bear the expense and time

required to interface or to integrate with the State's automated case management system? All

States answered similarly in the pilot stages by making the biometric efforts "stand-alone"

databases. Connecticut has since interfaced its finger imaging system with the rest of the welfare

database. Illinois, Massachusetts, New Jersey, and Texas also plan to interface, if not fully

integrate, their systems at some point in the future. As of November 1998, Arizona and New

York intended to continue with stand-alone systems, while California and Pennsylvania planned to

maintain stand-alone databases when their biometric identification systems become operational in

FY99.

Second, should biometric information or other statewide demographic information be

accessible? Should it be possible to purge information from each terminal? Because of the standalone nature of most biometric systems and concern about errors in updating or deleting

demographic information, the general practice is to permit viewing of certain State information,

but to allow fundamental case changes in the State's database to be made only through the central

site in the State. Specific practices range from the strictest in Illinois and Arizona to a more

relaxed practice in New Jersey. At least until any future rollout, Illinois does not allow client

information to be changed once it has been entered from any site other than the central site in

Springfield. Arizona also permits deletions only from the central site. New Jersey, on the other

hand, permits updating, modification, and deletion of biometric records, but only at the site where

the record originated. Within this continuum is New York, which allows deletions to be made at

a single site, but allows updates from multiple terminals.

Third, what security features should exist? To maintain the security of sensitive

information at a local or central office, the States follow a number of policies and procedures to

keep client data secure. New Jersey is a good example of the ideal kinds of safeguards controlling

access to biometric systems. In order to enter New Jersey's system, one has to be an enrolled user

at that particular work station, has to have the correct individual password and security code, and

must be positively identified with a finger image. One must be finger imaged during the staff

enrollment process and this finger image is the final step in the opening of a client application.

Additionally, there is an audit trail for every transaction. It records the site, time, and operator for

every transaction. As New Jersey's system is currently configured, the only information in the

system is case number, name, Social Security Number, sex, and date of birth. There is no benefit

information attached to the records. Other States, including Arizona, Illinois, and Massachusetts,

use various basic security features such as firewalls, Windows NT security, and password

protections.
15

Organization and Staffing

States were asked to describe any organization and staffing changes—either at the level of

the State bureaucracy or at the local office level—that were necessary to accommodate the

implementation and operation of their respective biometric identification systems. Among the

States with systems in operation statewide, approaches to supplying necessary staff varied.

In Arizona, for example, six existing State staff were transferred to provide management

and oversight of the Arizona Fingerprint Imaging Program, while at the local level, all functions

were absorbed by existing staff. New York use existing staff and dedicated them to the project,

though some areas, including New York City, used system operators supplied by the vendor.

Illinois and New Jersey also reported relying wholly on existing staff.

In contrast, the Connecticut Department of Social Services determined that administrative

functions associated with its AFIS system could not be adequately absorbed by existing staff.

Instead, DSS hired 40-50 new enrollment operators, drawn from candidates identified by a

temporary services agency as well as qualified public assistance recipients identified by DSS staff.

In California, several State-level positions were created for oversight and management of the

project. Once its statewide system becomes operational, counties will be given the responsibility

for securing operators and support personnel at the local office level, as well as the discretion to

determine whether to draw from existing staff, hire new county employees, or contract out.

Finally, in Texas and New Jersey, the need for temporary staff during the implementation was

filled by participants of the Job Opportunities and Basic Skills (JOBS) program.

Vendor Role

The division of labor between the contractor and the State has run along similar lines for

all States in the study. Beginning with informing the client population and the public, before the

biometric system actually is in place, and continuing through training and the actual biometric

imaging, the vendor and State serve relatively discrete functions, though overlap is sometimes

inevitable. For example, the States have performed much of the public information function,

although sometimes the contractor demonstration was a part of the acquaintance process. The

contractors have been used to provide much of the training (see Training), although follow-up

training may be initiated by the State.

The division of labor for the actual imaging process begins with the operators who

perform the biometric imaging. The county or the State generally hires and employs the

operators, but the vendor supplies human examiners (in the form of "minutiae experts") to analyze

suspect finger prints, retinal scans, or facial matches, and to testify in court, if necessary.4 The

vendor staffs the central site and processing unit and a help desk in Arizona, New Jersey, New

York, Texas, and California, planned). The central processing unit (CPU) is typically found in the

 

4

“Minutiae” refer to the unique characteristics of the ridges that make up a fingerprint. Two finger images match

if a sufficient number of corresponding minutiae can be identified on the two images. Human examiners, or

minutiae experts, are trained to make these determinations. For additional detail, see the companion report

(Sticha and Ford, 1999).
16

State capital, although the vendor located Arizona's CPU in the same office in Austin, Texas

which managed the Lone Star Image System demonstration.

The States reported that their respective vendors are responsive by and large to occasional

system problems and disabilities and have established records for providing adequate and timely

on-site technical assistance, as necessary. The Illinois Department of Human Services, however,

terminated its retinal scanning project in 1998, citing the complexity of the system, the time

required to secure biometric records, and the declining responsiveness of its vendor to the

department’s needs and issues.

Staff Preparation and Training

Preparing staff for the implementation of the biometric systems differed across the States.

New York and Illinois used policy memos to ease the way into implementation. New York also

conducted regional information sessions. Pennsylvania had the additional task of clearing matters

with the relevant unions. Connecticut may have laid the most groundwork when it formed a

statewide Digital Imaging Workshop with representation from each of the DSS regional offices,

all major departments within DSS's administrative organization, and from some of the General

Assistance programs in the State's 169 towns. Connecticut also used a department newsletter—4

in the first 6 months, then once every 2 months—to share information and to discuss potential

operational impacts with department staff.

California has exhibited a similar amount of effort up front. Regional meetings were

initially held with county staff to describe the planned system, the activities surrounding the

implementation of the system, the needs and expectations of the system, and to provide the

counties with the opportunity to ask questions. At the time interviews were conducted, the State

welfare programs staff were meeting regularly with county staff on the development of

procedures and regulations. The State also keeps counties updated with regular written

information notices to county welfare directors and Statewide Fingerprint Imaging System (SFIS)

representatives assigned in each county.

To help in the operational transition, the vendor provided general training. As an example

of significant pre-implementation training, the Arizona Department of Economic Security and its

vendor employed formal classroom sessions with overviews and presentations, computer-based

training (a training course at any computer with a test at the end), and 8-hour hands-on-training

for operators. In Texas, extensive training was provided to office staff in its two demonstration

counties by both DHS staff and the vendor. Connecticut and Illinois staff received a 4-hour

training session (less so for Illinois' discontinued retinal scanning) at the outset.

Collecting biometric information from applicants at a technically acceptable threshold is an

issue for all State systems, which, in general, are configured to reject images of insufficient

quality, returning a message to that effect immediately to the work station. Most States indicated

that operator error or insufficient training is a principal reason why client information of sufficient

quality may not be obtained, and the need for follow-up training to improve image capture and to

reduce client processing time was not uncommon across the States.
17

Informing Clients and the General Public

At implementation, advance notification to clients and/or the general public about new

biometric client identification procedures was considered important by all State representatives.

The objective of providing advance notification was to inform and prepare clients for the

additional application or recertification step (i.e., to explain the requirement and who is required

to submit, and to address client concerns), as well as to accelerate enrollment of the existing

caseload. All States, with exception of California and Pennsylvania, which remain in a preimplementation phase, prepared informational mailings to clients advising them of the new

requirement. Some States, particularly Arizona and Texas, reported developing additional

outreach media including bilingual (English and Spanish) videos, posters, and brochures for

viewing and distribution in the local office.

Most of the States also identified various outlets in the community through which they

informed the general public in advance about the implementation of biometric client identification

procedures. In Arizona, for example, staff used local councils of government as conduits for

information to interested parties and interest groups across the State, while also making

presentations to the local United Way, schools, and hunger councils in and around La Paz,

Mojave, and Yuma Counties, the three jurisdictions selected to pilot the system. The Texas

Department of Human Services used a similar approach in the San Antonio and south-central

Texas area, where it organized discussions with a regional coalition representing immigrant

interests. In Pennsylvania, where client outreach will be a vendor responsibility as the State

prepares to implement its system, staff expect to mobilize an informational campaign specifically

targeted to client advocacy groups across the State. Most of the States, particularly Connecticut

and Texas, emphasized that public information is essential to minimizing uncertainty and anxiety

about this technology and that open and unrestricted dialogue ought to be encouraged.

In addition to providing information, Connecticut deployed portable workstations in the

community during its initial implementation and throughout its statewide roll-out. For the

convenience of clients, State staff set up enrollment workstations in locations such as a former

State hospital, an office building, and various non-profit facilities. These stations helped to get

the system up quickly, while also relieving the logistical and scheduling burdens within the local

offices themselves.

2.3 Interview Results: Policy and Procedure

As new biometric identification systems were installed, State agencies informed current

recipients or new applicants of the biometric identification procedure and the need to follow the

procedure as a step in the recertification or application process. Though there may be variations

across States, the following describes a basic process for an incoming new applicant:

A new applicant completes the application by supplying the required demographic,

household, income, resource, and expense data, and submits it, generally in person, to the local

office. Once submitted, a clerk informs each applicant about the biometric requirement, and the

State’s policy on other family members who are also required to comply (see Mandatory
18

Participants, below). Once a determination is made regarding expedited processing, clerks

schedule applicants for intake appointments with eligibility workers.

On the day of and just prior to the intake interview, an applicant is referred to the

biometric identification specialist, who first conducts a system inquiry to determine whether the

individual has already undergone the procedure and whether the biometric information (e.g.,

finger or facial image, retina scan) is therefore already on record. If the specialist determines that

the applicant’s biometric information is not on record, the specialist will enter demographic

information for the applicant and will collect the biometric information. The information is then

transmitted to a central system for matching. If the applicant and any other family member who is

also required to comply with the requirement refuse to do so, the entire application is either

officially pended or processing is terminated, unless an exemption is granted.

Households eligible for expedited processing are subject to different procedures. In

Texas, for example, only household members present at the time of application are required to be

imaged. The image requirement is handled like any other postponed verification for absent

household members who are required to be imaged. If postponed, the absent household members

must be imaged prior to release of the held benefits.

Mandatory Participants and Exemptions

All adults (over the age of 18) applying for food stamp, TANF, and State general

assistance benefits must submit to the new biometric identification requirements, including adult

household members (see Table 3). In most States, minor heads of households and minor parents

(individuals under age 18 who are not heads of households) are also required to comply.

In all States, case processing continues in the event of a temporary exemption. The

inability to obtain a finger image by itself, therefore, is not the basis for delaying issuance of

benefits beyond federal and State processing time standards. However, there are important

differences in the stipulated conditions under which an exemption may be permitted. As a matter

of policy, most States observe some established set of conditions under which exemptions are

granted. Most relate to the capacity of the individual to supply the necessary physical information

at the moment of application or recertification.

Where finger imaging is used, States tend to grant temporary exemptions to individuals

with injuries to the index fingers and permanent exemptions in cases where individuals are missing

index fingers. In Illinois, where retinal scanning was tested, persons with bandaged eyes were

granted temporary exemptions, while blind individuals were granted permanent exemptions. In all

States, exemptions are temporarily granted in the case of system failure or scheduled downtime, in

which case applicants and recipients are scheduled to appear at a later date. Massachusetts grants

exemptions to those individuals for whom the procedure is inconsistent with religious beliefs;

Pennsylvania, when its system becomes operational, also expects to grant a religious exemption.

Texas granted a religious exemption in its pilot, but discontinued this exemption when the system

was implemented statewide. New York provides
19

Table 3

Mandatory Participants by Assistance Program and Allowable Exemptions

STATE MANDATORY PARTICIPANTS EXEMPTION POLICY

Arizona FSP: All adult household members (18

years or older)

TANF: All adults (18 years or older) and

minor parents

No written policy identifying specific

exemptions. In practice, household

members with missing fingers or arthritis.

A temporary exemption is granted for

illness.

California (plan for

unified, statewide

system)

FSP: All adult household members (18

years or older) and minor heads of

household

TANF and GR: All adults (18 years or

older)

Household members with missing fingers or

with a medically verified physical condition.

Connecticut TANF and GA: All adults (18 years or

older)

No written policy identifying specific

exemptions. Exemptions are possible at the

discretion of the DSS commissioner,

however, who has since extended authority

to the State’s Regional Managers.

Illinois TANF: All adult applicants and recipients

(including second and minor parents) and

non-aided payees

Permanent exemptions for household

members who are blind (ISCAN) or missing

fingers (AIMS).

Temporary exemptions for household

members with both eyes bandaged (ISCAN)

or injured fingers (AIMS).

Massachusetts FSP: All adult household members (18

years or older)

TANF and GA: All grantees (18 years or

older), including teen parents

Household members with both fingers

missing or for whom the procedure is

inconsistent with religious beliefs.

Temporary exemption granted to household

members with documented illness.

New Jersey GA: All adults (18 years or older) No permanent exemptions. Temporary

exemptions granted for injuries, but only for

2 months. In cases of missing fingers, facial

image taken.

New York TANF and GA: All adults (18 years or

older), minor parents, and minor heads of

household

Age for Medicaid cases is 21

At county discretion, and upon State

approval, the homebound may be exempted.

A general “good cause” exemption may also

be granted.

Pennsylvania FSP: All adults (18 years or older);

considering minor heads of household

TANF: All adults (18 years or older);

considering emancipated minors and

minor parents

For TANF benefits, no exemptions. For

food stamp benefits, will allow religious

exemption.

Texas FSP: All adults (18 years or older) and

minor heads of household

TANF: All adults (18 years or older) and

teen parents

Exemption is granted if the household

member appeals the requirement, is certified

out of the office, and/or is unable to have at

least one finger imaged. Religious

exemption was granted in pilot, but dropped

for statewide implementation.
20

for exemptions to the homebound, and a general “good cause” exemption may also be granted,

though the specific circumstances under which it has been or can be invoked are unclear. Three

States—Arizona, Connecticut, and New Jersey—have no formal policy that identifies specific

exempt conditions, though exemptions are possible and have been granted in practice.

In Connecticut, exemptions were possible only at the discretion of the commissioner of the

Department of Social Services, as originally authorized in the 1995 enabling legislation. Authority

to grant exemptions was recently extended to the State’s regional managers. Connecticut credits

its more restrictive policy to an extremely limited number of exemptions pursued by clients in the

first year of operations, and recommends that States not set themselves up for significant

exemption claims by publicizing those conditions under which an exemption might be granted.

Biometric images can also be technically inadequate for reasons related to the client. The

States reported that the quality of an image may be inadequate if an individual has very fine or

worn ridge lines, which most commonly occurs among women of Asian descent, the elderly, and

individuals who perform physical work, such as construction workers. In such cases, offices have

no real choice but to grant an exemption, though these cases represent an extremely small

proportion of the overall caseload. The use of a second biometric in some States and digitized

photos in many States can sometimes compensate for any of the aforementioned issues related to

the technology, operators, or clients.

Match Response

Once individual biometric information is collected and transmitted from the local office

enrollment workstation to the central processing unit, State systems are configured to quickly

generate and supply information on potential matches. States reported that the rapid turnaround

time has not been a critical factor since the biometric requirement is only one step in a multi-step

eligibility determination process that may require several days to several weeks to complete. The

speed with which the central system accepts individual biometric information and returns a matchno match disposition to the local office, therefore, turns out not to be of practical significance.

States reported that cases are virtually never pended, and benefit issuance never delayed, solely

because the biometric identification step has not been completed or match results have not been

received.

A summary of estimated response times for each of the State systems appears in Table 4.

Most of the State systems operate on an “instant” response, ranging from a period of 90 seconds

in New Jersey and within 5 minutes in Connecticut, Illinois, New York, Pennsylvania (according

to its plan), and Texas. In other States, including Arizona, for example, batch processing for

potential matches is conducted each evening, with match information generated the following

morning. California (when its statewide system becomes operational) plans a 60-minute

turnaround time for priority searches—expected to account for 40% of the workload—and batch

processing on non-priority searches to be received by 7:00 a.m. the following day.
21

Table 4

Match Response Time

STATE RESPONSE TIME

Arizona Up to 24 hours (at will of batch processor)

California Up to 1 hour

Connecticut 5 minutes

Illinois 5 minutes

Massachusetts Within 24 hours

New Jersey 1.5 minutes

New York 5 minutes

Pennsylvania 5 minutes

Texas 5 minutes

With the exception of Texas, match information is not transmitted directly to the local

offices. Rather, cases of potential duplicate matches are first routed from the central processing

unit to a claims investigative office, where they enter the investigative queue along with other

suspect cases (e.g., cases flagged by eligibility workers and referred because of questionable

information supplied during application or recertification, cases reported over hotlines for

suspicion of fraud). There, each case is reviewed to determine whether a match can be

legitimately attributed to a State administrative error (SAE) or an inadvertent household error

(IHE), or whether sufficient cause is present to assert that an intentional program violation (IPV)

was attempted or perpetrated. In addition to examining information contained in case files, the

investigation might include a visit to the home for additional information or for information

verification purposes.

Binning and Filtering

Because finger images must be compared to a large database of enrolled individuals, two

procedures, termed binning and filtering, are commonly used to reduce the number of

comparisons required. Binning places images into categories based on their characteristics, such

as classification type, ridge count, or some other characteristic of the finger image. Filtering

partitions images based on exogenous characteristics, such as gender or the identification of the

finger that was imaged. The matching algorithm will then be applied only to images in the same

bin or filter category. Binning and filtering can substantially decrease the time required to

complete the matching algorithm. It also decreases the likelihood of a false match. However,
22

because there may be errors in the assignment of images to bins or filter categories, use of binning

or filtering increases the likelihood of a false non-match.5

Most of the States with finger imaging systems in operation use either binning or filtering,

thereby speeding match response by reducing the number of comparisons required. In New

Jersey, for example, records are separated in several ways to speed response time, including by

gender and by left/right image. In addition, the database of images is divided and stored in onefifth portions in five separate HP 712 computers, which are searched simultaneously. A similar

process is used in New York, where images are both binned (by classification type) and filtered

(by gender, left/right image), meaning that only approximately 25-35% of the database is

penetrated at one time. In Arizona, conversely, where response time was not considered a policy

priority, images are stored solely by gender.

2.4 Interview Results: Ongoing Operations

The States with operating systems reported that implementation of new biometric client

identification procedures has had a negligible impact on operations at the local office level. In

general, States also reported that the problems and obstacles encountered in operating their

respective projects are not unlike those encountered in demonstrating any new technology or

procedural modification.

Types of Matches and Investigations

None of the States participating in this study developed unique procedures or standards

for handling suspected fraud due to duplicate participation. Once a fraud determination is

made—which has occurred in insignificant numbers across the States—the local eligibility worker

is informed by the investigative office and takes the appropriate action. The applicant or recipient

is notified in writing and is entitled to those protections available to individuals suspected of

criminal violation of other program rules, including the right to appeal any decision in an

administrative hearing. Most of the actual “matches” found in the States can be characterized as

errors of an administrative nature (e.g., client applies for benefits in a new jurisdiction while

having an open case in another jurisdiction that should have been closed, staff inadvertently enters

erroneous social security number into system).

Office and Client Burden

Those States with biometric systems in operation consistently reported that their systems

and procedures were implemented without unexpected difficulty and were rapidly

institutionalized. All the States confronted a range of basic physical space and logistical issues,

including where to situate the new equipment, how to appropriately alter job descriptions, whom

to reassign or hire to handle the new procedures, and how to adjust the flow of clients and

paperwork most efficiently. However, none reported any particularly noteworthy difficulties.

States report that clients have been cooperative and accepting of the technology and suggest that

an experienced operator can process an applicant in approximately 2-21⁄2 minutes, though the total

 

5

See companion report (Sticha and Ford, 1999) for additional detail.
23

extra time the client spends in the office may be longer depending on the volume of clients and the

number of open work stations.

Technical Problems

The States were generally pleased with the performances of their finger-imaging systems,

though they also reported experiencing a number of minor technical problems. These included

occasional telephone, computer (e.g., hard drive, downloading), printer, and camera problems.

For example, the Connecticut Department of Social Services described a situation in which one of

its enrollment centers could not be connected to the server, requiring the re-enrollment of nearly

500 clients. In addition, Illinois experienced problems with the reliability of the retinal scanning

system, the principal reason leading to its termination. Technology failures, while perhaps not

routine enough to be described as a significant problem, still warrant an exemption from the

biometric procedure that all States permit (i.e., one is temporarily exempted from the finger

imaging requirement if the image cannot be taken due to technological failure).
24
25

3. IMPACT OF FINGER IMAGING

One of the most important questions regarding the effectiveness of finger imaging

technology, and one of the most difficult to answer, is concerned with the extent to which the

technology reduces duplicate participation fraud in the FSP. Answering this question is difficult

for three reasons: (1) The baseline rate of duplicate participation fraud in the FSP is unknown;

(2) There are no measures that unambiguously assess the extent to which fraud is reduced; and

(3) There is little data that specifically addresses finger imaging in the FSP.

The first difficulty in evaluating the capability of finger imaging technology to reduce

duplicate participation fraud arises because there is no good estimate of the magnitude of the

problem. Much of the evidence regarding this type of fraud is anecdotal, and consequently, it is

difficult to assess how prevalent the problem is in the FSP. For example, Mintie (1998) reported

that a single individual received more than $450,000 in welfare benefits over 6 years using as

many as 15 different identities. Similarly, Ernst and Young (1995a) identified 36 instances of

duplicate participation fraud in California over a 10-year period that led to overpayments of over

$1.0 million. Although these cases indicate that multiple participation in welfare programs can

lead to substantial losses, they do not indicate how common this type of fraud is or what its total

cost to the welfare system might be.

The second problem in assessing the effectiveness of finger imaging technology in

reducing fraud is that there are no measures that unambiguously assess the extent to which fraud

is reduced. Some measures (e.g., detected fraud) only capture a portion of the reduction. In

other potential measures, fraud reduction is confounded with reduction in participation due to

other reasons, such as changes in economic conditions, changes in eligibility requirements, or

resistance of legitimate clients to finger imaging.

Finally, the available evaluation data come primarily from TANF or General Assistance

programs rather than the FSP. There is a risk that generalizations from one program to another

will not be accurate because of differences between the program requirements, the benefits

provided, or the client populations. The substantial overlap between the FSP population and those

receiving other types of assistance suggests that this risk would not be very large, although some

differences between the programs would not be surprising. Evaluation data from Texas, which

implemented a finger imaging pilot for both TANF and the FSP, indicate an agreement on the

effects of the pilot on the two programs, as well as differences in a number of details

(Schexnayder, Olson, O’Shea, Norris, Schroeder, & King, 1997). Specifically, overall changes in

caseload that occurred when finger imaging was implemented were comparable between the two

programs. However, a more detailed analysis of caseload flows identified differences between the

two programs suggesting that finger imaging increased the time required to process food stamp

cases, but not TANF cases. These differences indicate that care should be taken in applying

existing results to the FSP.

Six of the States that we interviewed (Connecticut, Illinois, New Jersey, New York,

Texas, and counties in California) conducted evaluations to assess the ability of their systems to

reduce fraud. The evaluations measured fraud reduction based on detected fraud, refusals to be
26

finger imaged, or caseload reduction. This section summarizes the results of these evaluations

and attempts to give an overall assessment regarding the effectiveness of the technology.

3.1 Detected Fraud

There is little doubt that finger imaging has the technical capability to detect individuals

who try to obtain duplicate food stamp benefits using false identification. A recent evaluation of

the performance of finger-imaging systems conducted by the National Biometric Test Center

(Wayman, 1997) provides both an assessment of system performance under standard conditions

(verification of a single comparison) and a procedure to predict performance in other conditions

(e.g., one-to-many matching). Using these data and procedures, Sticha and Ford (1999, pp. 20-

21) estimated the system false match and false non-match error rates making assumptions

representative of the finger-imaging systems used by States in their assistance programs.6 Based

on these assumptions and on the performance data reported by Wayman (1997), Sticha and Ford

estimated the system false match rate to be 0.5% for each 1 million individuals in the data base.

Thus, in a situation in which 2 million individuals were represented in a finger-image data base,

1% of legitimate new applicants (not in the data base) would incorrectly be judged by the system

to match existing finger images. In most States, these false matches would be reduced to near

zero by the use of human minutiae analysts. The system false non-match rate does not depend

upon the size of the data base, but it does depend on the number of fingers that are imaged and

the criterion for declaring a match. Based on the previously stated assumptions and data, Sticha

and Ford estimated a system false non-match rate of approximately 4%. These calculations

indicate that finger-imaging technology has the potential to detect approximately 96% of

attempted duplicate identity fraud while producing a false match for less than 1% of legitimate

applicants.

Detected attempts at duplicate participation were rare in all State implementations for

which we have data. However, the detection rate may be reduced for those States that

implemented pilot programs in a limited geographical region. Attempts to match finger images

across State lines have produced more matches than within state comparisons, but reported data

were insufficient to calculate a match rate for interstate comparisons. Table 5 shows the number

of finger-image matches attributed to fraud by the six States that have conducted evaluations.

The number of matches varies from one match per 25,000 cases to one match per 1,800 cases and

has a median of 1 match per 5,000 cases.

These results are consistent with claim that main benefit of finger imaging is to prevent

duplicate participation from occurring, rather than to detect attempts at this type of welfare fraud

 

6 They assumed that two fingers were imaged for each individual, and that a match was declared if both of these

fingers matched corresponding fingers in the data base; otherwise, a non-match was declared. They further

assumed that applicants were categorized by gender, and that right and left fingers were distinguished. The

effect of possible errors in this categorization was not considered. Finally, they assumed that fingerprint type

was not used to place images into bins to reduce the number of images searched. Binning would have decreased

the false match rate and increased the false non-match rate.
27

Table 5

Finger-image Matches Attributed to Fraud

STATE/

LOCALITY

NUMBER OF

CASES TIME PERIOD NUMBER OFMATCHES

DUPLICATE

DETECTION RATE

California

 Alameda County

10,825 February 1993 –

April 1995

2 .02%

 LA County 280,000 April 1994 -

May 31, 1995

11 fraudulent; 3

under investigation

.005%

 San Francisco

 County

14,400 March 1994 –

November 1995

8 within county, 31

with other counties

.06% (within county)

Connecticut

 statewide

148,784 February 1, 1996 -

February 28, 1998

12 prosecuted; 20

under investigation

.02%

Illinois

 Chicago suburbs

21,000 (finger

image and

retinal scan)

May 20, 1996 –

December 1, 1997

1 .005%

New Jersey

 northern

counties

46,000 (as of

3/1998)

July 10, 1995 -

April 1999

<12 .03%

New York

 statewide

904,746 (as of

3/14/1997)

August 1995 –

December 1996

221 fraud; 92 under

investigation

.03%

Texas

 Bexar &

 Guadalupe

 Counties

110,000 (as of

3/1998)

October 24, 1996 –

September 16, 1997

1 .001%

Sources: Data for Alameda and San Francisco Counties, California, from Ernst & Young (1995b). Los Angeles

County, California, data from Department of Health and Human Services, Office of Inspector General (1996).

Connecticut data and caseload estimates from New Jersey and Texas from Connecticut Department of Social

Services (1998). Illinois data from Illinois Department of Human Services (1997). New Jersey match data from

State interviews. New York data from Nawrot (1997). Texas match data from personal communication, Herb

Kneisley, Texas DHS, Sept. 16, 1997.

when they occur. In addition, some of the implementations, especially the pilot programs, were in

small geographical areas. For these programs, it would be relatively easy for an individual

attempting to obtain duplicate benefits to apply at nearby offices that did not require finger

imaging. The data from the States seem to support this notion. Geographically limited pilot

programs, such as those in Texas and Illinois, tended to have low detection rates, while the

statewide operational systems in New York and Connecticut had higher detection rates.

Connecticut, New Jersey and New York have reported cross-State comparisons of fingerimage data; neighboring counties in California also compared data. These interjurisdictional

comparisons often produce more matches than comparisons within a State or county. For

example, examination of 137 cases involving AFDC recipients who refused to provide a finger
28

image for the AFIRM system in Los Angeles County uncovered 8 confirmed (and 23 suspected)

instances of multiple-case fraud. All of the confirmed instances involved one case within the

county and another outside of the county (DHHS, OIG, 1996). In addition, in 31 of the 39

matches involving cases in San Francisco County, the second case was in a neighboring county

(Ernst & Young, 1995b). The Connecticut Department of Social Services (1998) reported that

the first attempt to match finger images between Connecticut and New Jersey identified 53

matches that were referred for investigation. Only 32 matches that warranted referral for

investigation were found in more than 2 years of operation of finger imaging within Connecticut.

In evaluating the impact of identity matches made by finger image comparison, it is

important to recognize that some matches could be made based on name and Social Security

Number (SSN) only. For example, the GAO (1998a) recently compared the 1996 FSP roles for

California, Florida, New York, and Texas, and identified over 20,000 SSN matches between cases

in these States. With one exception, State evaluations did not indicate whether duplicate

participation identified by finger imaging could also have been found using applicant name or

SSN. The exception is the single fraudulent match found in Illinois; the applicant in this situation

used the same name and SSN in both cases (Illinois DHS, 1997). Consequently, that match could

have been found without finger imaging.

In summary, attempted duplicate-participation fraud detected by finger imaging represents

only a very small percentage of total caseload. Statewide implementations of finger imaging tend

to have a slightly higher detection rate than pilots in a limited geographical area.

Interjuristictional comparisons of finger-image data can identify additional fraud, but State

evaluation data are insufficient to calculate a match rate for these comparisons.

3.2 Refusals to Comply with Finger-image Requirements

One potential indicator of the number of duplicate cases in the FSP or other assistance

program is the number of existing clients who refuse to provide the required finger image at the

time of recertification. It is assumed that given the high likelihood of being caught, an individual

with multiple cases will almost certainly refuse to comply with the finger-imaging requirement for

all but one case. However, there may be other reasons that clients do not comply with the

requirement. Some of these reasons may be related to other types of client fraud; for example, the

client may have misrepresented household size (which can sometimes be detected by finger

imaging) or income (which cannot be detected) and may be concerned that the fraud would be

detected during the finger-imaging process. Other clients may have moved out of the area or may

be no longer qualified for assistance. In addition, some qualified clients may have concerns about

the legality of fairness of the finger-image requirement, or may decide that continuing their

benefits is not worth the extra effort of providing the required finger image. Finally,

administrative delays while waiting for household members to provide a finger image may be

incorrectly reported as refusals if they extend an application beyond the end of a reporting period.

Because there are many reasons that individuals may refuse to comply with the finger-image

requirement, the rate of refusals for existing clients overestimates the duplicate-participation fraud

rate.
29

Despite the ambiguous relationship between refusals and duplicate participation, this

measure has figured prominently in State evaluations of the ability of biometric systems to reduce

fraud. Since benefits are denied to those who refuse to provide a finger image, refusals are often

the primary factor in the cost justification for these systems, as well. The refusal rate is used by

these States to estimate the amount of fraud present before the introduction of the biometric

system. Attempts are made to adjust the refusal rate so that only those refusals indicating fraud

are considered.

Table 6 shows the number and percentage of existing cases that were cancelled or

otherwise sanctioned because of refusal to comply with a finger image requirement as reported by

the five States for which data were available.7 The data cover the same time periods as shown in

Table 5. Numbers include only those who refused to comply with the requirement and do not

include cases that were closed for other reasons when the finger image requirement was instituted.

Two refusal percentages are shown, the raw refusal rate, and the refusal rate adjusted for

recidivism. Recidivism refers to those clients whose benefits are canceled because they refuse to

comply with the finger-image requirement, but who later comply and return to the rolls.

Table 6

Refusals of Existing Cases to Participate in Finger Imaging

REFUSAL PERCENTAGE STATE CASELOAD REFUSALS

RAW ADJUSTED

California (Los

Angeles County)

24,334 (experimental

group)

914 3.7% 2.7% (8-month)

Connecticut 54,616 (TANF) 3,541 6.4% 3.7% (14-month)

Illinois 10,384 2 .02% NA

New York 552,358 42,372 7.7% 5.4%

Texas 66,025 266 .4% .2% (1-month)

Sources: Los Angeles County data from Ernst & Young (1995a). Connecticut data from Connecticut

Department of Social Services (1998). Illinois Data from Illinois DHS (1997). New York Data from

Nawrot (1997). Texas data from Texas DHS (1997).

 

7 Data from Connecticut include only TANF refusals that were sanctioned during 1996. Before implementation of

finger imaging, the GA program was administered by 169 local organizations, often without any automated

record of GA clients. When finger imaging was introduced, 7,568 of the 22,198 existing GA clients (34%)

failed to register during 1996. While this number is impressive, it is impossible to determine what percentage of

the reduction reflects client reactions to finger imaging, and what percentage reflects the condition of local

records regarding GA clients. In 1997, the TANF and GA programs were combined under State control.

During that year, an additional 1,072 cases in one of these programs were sanctioned. Since finger imaging had

already been introduced by this time, these cases appear to reflect new, rather than existing clients. Similarly,

the 449 refusals reported by Arizona Department of Economic Security (1999) combine new and existing clients.
30

Since the canceled cases that are later reopened cannot represent duplicate cases, subtracting

them from the total number of refusals reduces the extent to which refusals overestimate actual

duplicate participation fraud. Different States reported recidivism over different time periods, as

noted in the table. Since recidivism is cumulative, longer time periods produce greater recidivism

as well as a more accurate measure of fraud. However, the results from Texas, in which 61% of

those who refused to provide a finger image in one month returned the following month, illustrate

that substantial number of clients may return to the FSP or TANF rolls in a short time.

Examination of the refusal percentages in Table 6 shows two States, Illinois and Texas,

with very low refusal rates, substantially less than 1%, while the other three States have rates in

the range from 3% to 5%. This difference may be associated with differences in how the fingerimage requirement was implemented in the States. In the three programs with higher refusal

rates, existing clients were scheduled for appointments for the purpose of providing a finger

image. If a client missed this appointment, then procedures to terminate benefits for that client

were started. For example, in Los Angeles County, a client who failed to show up for finger

imaging was sent Notice of Action that stated the payments would stop in 10 days, and eligibility

would be reassessed (Ernst & Young, 1995a). If client came in for a meeting and was finger

imaged, then benefits were maintained. If the client came in and refused to be finger imaged, the

client would be taken off the case, although benefits for children would continue. If client did not

show up for the meeting, the entire case was terminated.

In contrast, for both Illinois and Texas, conversion was linked to the recertification

process. In Illinois, current recipients were notified that finger imaging would be required at their

next recertification appointment. In Texas, clients were given earlier appointments, but were not

required to provide finger images until their continuing eligibility was recertified. In these States,

it would be possible for a client with multiple cases to wait until the time to recertify eligibility, let

his or her benefits lapse, and not be counted as a refusal (although this action would reduce

overall caseload). Consequently, for these two States, the refusal rate is likely to miss some cases

of actual fraud, adding another source of error and making the rates more difficult to interpret.

The evaluation of the AFIRM system was designed to provide the most accurate measure

of fraud reduction based on refusals. In this evaluation, existing AFDC cases at sites in which

finger imaging was implemented were randomly assigned to experimental and control groups.

Finger images were not required for clients in the control group until after the end of the

evaluation. This experimental design controls for differences between sites as well as the natural

attrition in the assisted population that occurs over time. Ernst & Young (1995b) report that the

decrease in participation of clients in the experimental group was 1.3% greater than the decrease

in the control group. Because most confounding factors were controlled in this study, the

reduction is due primarily to two factors – reduced duplicate participation and deterrence of

eligible clients by their concerns about finger imaging. The data do not provide information that

could be used to allocate the reduction between these two factors.

The relationship between refusals and fraud is more ambiguous for new applicants for

assistance than it is for existing applicants. Individuals with more than one existing case have two

options regarding how they react to a finger-imaging requirement – they can refuse to comply

with the requirement, or they can comply and have a high probability of being detected.
31

Depending on the option they choose, their response will be recorded as either a detection or a

refusal.8 On the other hand, individuals seeking to open a new case, either a fraudulent duplicate

case or a legitimate one, have a third possible response to a finger-imaging requirement – they can

be deterred from applying. The refusal rate for new applicants does not capture the proportion of

potential applicants who take this third course. Consequently, it does not provide a good basis

for estimating either the prevalence of fraud among applicants or the effectiveness of finger

imaging to reduce it.

When refusals to participate in finger imaging were reported for new applicants, they had

a much smaller impact on caseload than refusals of existing recipients. Illinois had a single case in

which an applicant failed to appear to provide a finger image. New York found that 0.2% of new

applicants refused to provide finger images. Because of the small magnitude of these numbers

and because of the problem with interpreting new applicant refusals, the implication of these

numbers on the amount of fraud is unclear.

In summary, refusals to comply with finger-image requirements provide an imperfect

estimate of the amount of duplicate participation fraud that depends on the way that the fingerimaging requirement is implemented. Adjusting the refusal rate for recidivism improves the

estimate, but does not remove all sources of error. In particular, eligible individuals who refuse to

provide a finger image because of their concerns with the process cannot be distinguished from

fraudulent individuals who do so. Despite these concerns, the refusal rate provides a useful

indicator of the possible upper bound for an estimate of the amount of duplicate participation

fraud.

3.3 Reduction in Applications or Caseload

Evaluations based on refusals to comply with a finger-image requirement have focused

primarily on the existing caseload and provide limited information about the effects of biometric

technology on new cases. Also, the refusal rates appeared to be affected by the policies and

procedures used to implement finger imaging. The total number of applications or caseload (both

existing and new households) provides the most complete measure of the effects of biometrics on

fraud reduction. Two States, Illinois and Texas, have reported overall changes in applications or

caseload. However, interpreting these changes is difficult for the following two reasons.

First, there are many possible causes of changes in caseload, including changes in local

economic conditions, effects of other welfare reform initiatives, and other factors. For example,

Figure 2 shows that nationally, participation in the FSP has declined 26% from 1994 to 1998,9

and participation in TANF/AFDC has declined 33% in the same period.10 The implication of the

changing environment on evaluation of biometric systems is that it is necessary to have

 

8 As our previous discussion indicated, an estimated 4% of duplicate cases would not be detected by the system.

9

Source: Data for 1993-1997 from Cody & Castner (1999); data for 1998 from FNS Budgeting Division, Data

Base Monitoring Branch (1998).

10 Source: U.S. Department of Health and Human Services, Administration for Children and Families (1998).

Households for 1993-1997 represent average monthly values; 1998 households represents the month of June.
32

appropriate control regions against which to compare caseload changes that occur when biometric

requirements are implemented.

Figure 2. Food Stamp and TANF/AFDC 

households, 1993-1997.

6

7

8

9

10

11

12

1993 1994 1995 1996 1997 1998

Year

3

3.5

4

4.5

5

5.5

6

Food Stamps TANF/AFDC

Second, determining appropriate comparison groups is often a difficult process, especially

when potential comparison regions may be participating in other experiments with their welfare

system. It is not feasible to split the entire population into experimental and control groups, as

was done for existing cases by Los Angeles County. Consequently, comparisons must be made

between regions, adding undesired variability to results.

Illinois compared the number of applications for assistance in the pilot sites to applications

in adjacent regions. They based their assessment on the ratio of applications in the pilot region to

the comparable number in the adjacent regions. They found that this ratio decreased roughly 5-

6% for TANF-cash applications for retinal scanning, but only 1% for finger imaging. A similar 5-

6% decline was found in TANF-medical applications for both finger imaging and retinal scanning.

No difference was found for Food Stamp applications. The Illinois report presents detailed data

for TANF-cash applications only, since that was the only program directly affected by the fingerimage requirement. These data illustrate the difficulty in interpreting reductions in applications in

times when the total welfare system is changing in many ways. Applications in the pilot sites

decreased 24% from the previous year. However, applications in the adjacent sites decreased

23% in the same period, leading to a 1% net effect for finger imaging. This difference is

consistent with what has been found with refusal data, but was not considered to be significant

because the sample size was much smaller and the experimental design confounded reductions

with site differences.

The Texas evaluation of caseload changes included a more careful selection of comparison

sites, based on several demographic and program characteristics. Each pilot site was matched

with a similar comparison site. Caseload data were collected for the year prior to the pilot, as

well as for the first seven months of the pilot program. The analysis of caseloads also accounted
33

for differences between pilot and comparison sites. Nevertheless, the overall results indicated that

there were no differences between the comparison and pilot sites, and consequently, no reduction

in caseload that could be accounted for by the introduction of the biometric system.

3.4 Summary

Assessing the ability of finger imaging to reduce fraud in the FSP is difficult because the

amount of fraud caused by duplicate participation is unknown, and because changes in caseload

after the introduction of finger imaging cannot be interpreted unambiguously as reduction of

fraud. In addition, because little data specifically address the FSP, effects on that program must

be inferred by extrapolating from other assistance programs, such as TANF and GA. The

evaluations of finger imaging systems conducted by six States have produced the following

findings.

• A very small number of attempts at duplicate participation have been detected by finger

imaging systems. Finger-imaging systems appear to detect more fraud when the area of

coverage is larger. Additional matches have been found by interstate comparisons of

finger-image data.

• Institution of a finger-imaging requirement can produce a significant, short-term reduction

in caseload, because some existing clients refuse to comply with the requirement. The

number of refusals depends on the implementation procedures and appears to be lower

when finger imaging is incorporated into the recertification process.

• The most carefully controlled estimate of non-compliance among existing clients, based on

participation rates for experimental and control groups in the AFIRM system, suggests

that introduction of a finger-imaging requirement reduces participation by approximately

1.3%. However, this estimate reflects both reduced fraud and deterrence of eligible

individuals and households.

• Attempts to compare caseload trends at sites at which finger imaging is introduced to sites

without finger imaging have found no differences, due, in part, to the large reduction in

caseload that occurred in all sites.
34
35

4. DETERRENT EFFECTS OF FINGER IMAGING ON ELIGIBLE INDIVIDUALS

One of the persistent concerns regarding biometric identification systems has been whether

the given system complies with standards of individual liberty, privacy, and due process. In a

survey funded by The National Registry, Inc., a biometric system vendor, Westin (1996) assessed

the opinions of a national probability sample of adults regarding the use of finger imaging in

government benefits programs. Most survey respondents had positive opinions about finger

imaging; 75% would be comfortable if a finger-imaging process were used to identify them in a

government benefits program, and 81% thought that finger imaging was an appropriate method to

screen applicants for government benefits. However, the survey sample represents the adult

population in general, not necessarily the population of likely FSP clients. Such information can

best be obtained directly from clients.

Client data can also provide information regarding the reasons households leave assistance

programs when biometric requirements are established. This information can indicate the extent

to which eligible households are deterred from applying for assistance because of concerns with

the finger-imaging requirement. States have obtained client data using surveys or interviews with

current clients, former clients, and community leaders or other individuals representing client

concerns.

4.1 Client Reactions

Five States in our sample conducted interviews or surveys with current welfare clients to

ascertain their reactions to finger imaging. Since this information was obtained from clients who

complied with the finger-image requirement, it doesn’t indicate the reasons individuals refuse to

comply. Nevertheless, it can show the degree of discomfort that clients have with finger imaging.

The results of these surveys, summarized in Table 7, show that client responses to finger imaging

have been predominantly positive. Although different States asked different questions, some

common issues were addressed.

In New York, 77% of the respondents perceived a need for finger imaging. Clients in

Texas were asked a similar question both in interviews conducted with a small sample of clients

immediately after they were finger imaged, and on a satisfaction card given to a larger sample of

clients. In interviews, 96% of the clients said that they thought that finger imaging was a good

idea. Approximately 90% of these clients who filled out the client satisfaction card thought that it

was a good idea.

Clients were also relatively confident about the effectiveness of finger imaging in reducing

fraud. In the evaluation of the AFIRM system in Los Angeles County, 92% of clients surveyed

thought that finger imaging would help prevent people from cheating in order to obtain benefits.

Similar questions asked in Connecticut and Texas produced similar results (87% and 88%

agreement, respectively). Responses to a slightly different question included in interviews

conducted in Texas were somewhat less positive; 70% of clients interviewed thought that finger

imaging would keep people from getting benefits that they should not get. The Illinois

Department of Human Services asked whether others in the community would be less likely to
36

apply for aid because of finger imaging. Nearly 40% of clients responding were uncertain

regarding this question. Approximately three-quarters of the remaining clients (47% of the total)

thought that others would be less likely to apply, although the reasons they might not apply were

not ascertained.

Table 7

Summary of Client Survey Results

STATE SELECTED QUESTION CLIENT AGREEMENT

PERCENTAGE

California/

LA County

Have you been inconvenienced ... because of the

fingerprinting program?

How do you feel about having to be fingerprinted in

order to receive AFDC?

Do you think fingerprinting will help prevent people

from cheating in order to receive AFDC?

94% No

25% positive,5% negative

92% yes

Connecticut Have you been inconvenienced ... because of the

finger imaging process?

How do you feel about being finger imaged in order to

receive benefits?

Do you think finger imaging will help prevent people

from cheating in order to receive benefits?

Do you know of anyone ... prevented from cheating

because of finger imaging?

Do you like the new client identification card?

88% No

85% did not object

87% Yes

0.6% Yes (2 respondents)

88% Yes

Illinois Is electronic fingerprint imaging acceptable to you?

Was the process easy for you?

Are others in your community less likely to apply

because of fingerprinting?

Is the attitude of the general public positive toward

electronic fingerprinting?

82% Yes

97% Yes

47% Yes, 15% No

61% Yes, 9% No

New York Concern regarding provision of finger images (did

they feel stigmatized?).

Perceived need for finger imaging requirement.

80% No

77% felt requirement needed

Texas

(Interviews)

Do you think finger imaging is a good idea, bad idea,

or neither good nor bad?

Do you think finger imaging will keep people from

getting benefits they should not get?

96% good, 2% bad

70% Yes, 11% No

Texas

(Satisfaction

Cards)

What do you think about finger imaging?

Do you think finger imaging will help people be more

honest when applying for benefits?

90% good idea, 2% bad idea

88% Yes, 4% No

Sources: Los Angeles County data from Ernst & Young (1995a). Connecticut data from Connecticut Department

of Social Services (1998). Illinois Data from Illinois DHS (1997). New York Data from Nawrot (1997). Texas

data from Texas DHS (1997).
37

Clients reported little inconvenience related to finger imaging. Approximately 94% of

clients in Los Angeles County and 88% of clients in Connecticut stated that they were not

inconvenienced by the finger-image process. In Illinois, 97% of clients surveyed thought that the

process was easy for them.

Four States asked a general question to assess how clients felt about the finger-imaging

process. The purpose of these questions was to determine whether clients had any personal,

safety, health, religious, or cultural reasons for objecting to finger imaging. Results were most

positive in California; only 5% of respondents expressed negative impressions regarding finger

imaging. Results in the other three States were similar. Between 80% and 85% of clients

surveyed in these States had no objection to finger imaging.

4.2 Former Client Interviews

Evaluations in California and Texas included interviews with former clients who either

refused to be imaged or did not apply for recertification when finger imaging was introduced.

The goals of these interviews were to determine the reasons that these clients left the program, as

well as to find out their opinions about finger imaging.

In their evaluation of the AFIRM system in Los Angeles County, Ernst and Young

(1995b) contacted individuals from 86 cases that were terminated for failure to comply with finger

imaging requirements. For a substantial majority of the cases (88%), benefits were terminated

because the clients started working, moved, or requested termination of aid. None of the

individuals who were contacted indicated that they were intimidated by the finger-imaging

program.

Interviews conducted in Texas (Schexnayder et al., 1997) compared the opinions of

former clients in the area covered by the pilot finger imaging system with those of former clients

in matched comparison regions. Both former FSP and former TANF recipients were asked an

open-ended question about why they had stopped receiving benefits. The primary reasons cited

were increased earnings, other client choices, and agency errors. Increased earnings were cited

more frequently in pilot than in comparison regions, while client choices and agency errors were

cited more frequently in comparison regions. Client choices, which were a factor in one-third of

FSP exits and over one-quarter of TANF exits, include reasons that could reflect a deterrent

effect, such as a feeling that “benefits were not worth the effort.” Although none of the former

TANF clients identified finger imaging as the reason the discontinued benefits, two of the 78

former Food Stamp clients (3%) attributed their loss of benefits to finger imaging. Both of these

individuals had refused to be imaged. In another question, former clients were asked directly

whether their benefits, or the benefits of anyone they knew, had been affected by finger imaging.

Three additional individuals (4%) associated their reduction in benefits with finger imaging,

although Schexnayder et al. indicated that other factors played a role, as well.

4.3 Client Advocate Opinions

Client advocates and other community leaders may provide information regarding opinions

of participants and eligible non-participants that would be difficult to obtain directly. Their
38

position in the community gives them access to information and the opinions of many individuals.

They may be more willing to express client criticisms and concerns regarding finger imaging than

the clients would. Finally, they may have access to eligible individuals who were deterred from

applying by the finger-image requirement.

The State of Texas surveyed the opinions of community leaders shortly after the

introduction of their finger image pilot. They sent a three-question survey to 104 leaders in the

two counties participating in the finger-imaging pilot to collect community opinions about the

pilot program. Community leaders included “State legislators, city council members, and

[directors of] non-governmental, community-based agencies that serve public assistance clients

(including neighborhood centers and religious and non-sectarian social services)” (p. E-1, Texas

Department of Human Services, 1997). The three questions assessed the responses these leaders

have heard from their constituents and their personal opinions regarding finger imaging.

Over four-fifths of the 41 community leaders who responded to the survey indicated that

they had received little or no response from their constituents regarding finger imaging during the

first three months of its use. Of those who had received some response, nearly half of the

responses were neutral regarding the requirement, while those expressing opinions were slightly

more likely to be positive than negative. Nearly two-thirds of the respondents thought that finger

imaging would help keep ineligible people from getting benefits, while only 5% thought that it

would not.

We conducted follow-up interviews with nine community leaders who might represent the

concerns of food stamp recipients and applicants in Texas. The client advocate interviews

emphasized advocate and client concerns about finger imaging and the LSIS pilot program. A

detailed description of the interviews and results is presented in Appendix C.

We selected the interview participants from the mailing list of 104 government and nongovernment leaders who received the survey given by the State of Texas. To get a wide range of

opinions, we supplemented this list with suggestions given by an outspoken critic of finger

imaging. We selected nine candidates from the non-government leaders on the expanded list.

Even one year after the LSIS pilot project had been in place, some client advocates had

not heard much about the project. Along with the limited knowledge that some individuals had

about the project were misconceptions about the nature of the finger-imaging requirement. Four

of the persons interviewed thought that finger imaging was used at the point-of-sale. Two

advocates didn’t realize that finger imaging had begun.

Seven individuals had heard some concerns about finger imaging from either clients or

other sources such as colleagues or the media. Four of the nine had clients with concerns about

finger imaging in the Food Stamp program. The types of concerns most frequently voiced by

clients to their advocates fall into three categories: unjust treatment of poor people, cost and

inconvenience of being finger imaged, and fears of interagency sharing, especially with the INS.

Some advocates indicated that clients associate finger imaging with criminality and may be

embarrassed about giving their finger image. Others consider the finger-imaging requirement to

be degrading and as unjust treatment of poor people. The cost and inconvenience of going to the
39

food stamp office is a concern for some who must make child care arrangements or pay for

transportation to the office or take time off from work. With finger imaging, more individuals

must make trips to the food stamp office, increasing the cost or inconvenience to household

members. Further, there was a concern that delays in getting all members of a household imaged

could result in delays in receiving benefits. Finally, some client advocates reported client concerns

about sharing information with other agencies, especially the INS. These fears stem from a lack

of information about the INS process, leading to uncertainty about the status of immigration

cases, according to client advocates.

Five of the leaders personally thought that finger imaging in the FSP was a bad idea and

focused on negative aspects of finger imaging. One of these respondents noted that finger

imaging, per se, is not a bad idea. He believed that there are appropriate applications for the use

of biometrics, such as law enforcement. However, he deemed the use of finger imaging in a food

and nutrition program as inappropriate. The other four interviewees thought finger imaging was a

good idea and generally focused on its use in the prevention of fraud and consequent saving of

money in the FSP.

4.4 Summary

Clients do have some concerns about finger imaging. Roughly 15% expressed concerns in

the State surveys and interviews conducted to evaluate finger-imaging programs. These concerns

center on issues of privacy, unjust treatment of poor people, inconvenience, and fear of

interagency sharing. Despite these concerns, the overall client reaction to finger imaging is

decidedly favorable. A substantial majority of clients had no objection to finger imaging and

thought it was a good idea.

There is little evidence that many clients discontinue benefits because they are intimidated

by the finger-image requirement. Although there is little data on which to estimate the size of the

deterrence effect, interviews of former clients in Texas found that roughly 3% of closed FSP cases

may be due to concerns with finger imaging. An additional 4% of former FSP clients perceived

that finger imaging led to a reduction in their benefits. Similar interviews in Los Angeles County

found no one who refused to be finger imaged expressed a concern with the process.
40
41

5. COST ANALYSIS OF FINGER IMAGING IN THE FSP

Several factors limited our ability to establish the cost to implement finger imaging. The

cost of implementing a finger-imaging system depends on how the program is implemented,

whether equipment is purchased or leased, whether other agencies share the cost of the system,

the role of the contractor in providing transitional staff, and the time period over which the system

is introduced. The material we received from the States typically did not include the detail

required to determine the specific implementation procedures. Furthermore, the material often

did not specify the internal costs to the State, in addition to the costs paid to the vendor.

Because of these difficulties, it was impossible to estimate the costs of finger imaging

precisely. Nevertheless, it was possible to describe the kinds of costs involved and their

approximate magnitudes, based on the experiences of the States that have reported costs. In

addition, we were able to quantify some of the benefits in monetary terms, although we could not

quantify the increased program integrity that may be brought about by the introduction of finger

imaging.

As biometric technology has matured and the market for these devices expanded, costs

have decreased substantially. Thus, cost estimates from States that have implemented finger

imaging in one of their assistance programs may not accurately represent current prices or predict

future ones.

5.1 Review of State Costs Estimates

Estimates of the cost of finger imaging were obtained from Arizona, Los Angeles County,

Connecticut, Illinois, Massachusetts, New Jersey, and Texas. The estimates varied greatly in the

level of detail provided and the time period over which the analysis was conducted. Four

States—Arizona, California (for the AFIRM system in Los Angeles County), Connecticut, and

Illinois—provided sufficient detail for us to calculate total cost for implementation and operation

over a three-year period. Table 8 shows these costs, both as a three-year total, and as an annual

cost per case. The average annual cost per case for these four systems was slightly less than

$14.00. The most recent estimates, those for statewide implementation of finger imaging in

Arizona and Illinois, are also the lowest and are substantially less than the actual experience of

Los Angeles County. Although the bulk of this difference is probably due to reduced technology

costs, some part of the difference may be due to differences in estimation methods or specific

program characteristics. For example, Illinois did not consider the cost of temporary staff in their

estimate. Considering this factor would increase the estimate for Illinois by about 10%, based on

the experience of Los Angeles County. In addition, in the Arizona system, the vendor retained

ownership of the equipment and software.

Most of the available cost estimates are based on pilot programs or programs implemented

in a limited area. Statewide implementations benefit from economies of scale that make them

proportionately less costly than more limited implementations. On the other hand, vendors may

offer especially attractive costs of pilot programs in hopes of obtaining future profits on a

statewide implementation. For example, the Illinois DHS (1997) reports that the finger-imaging
42

vendor that they selected reduced its bid by 70% in order to secure the contract for the pilot

implementation. Because vendors set prices based on number of factors, they could not provide

us general formulas for estimating cost, as was indicated by Sticha and Ford (1999).

In reporting the costs shown in Table 8, adjustments in the values reported by the States

were made to improve comparability. The caseload represents the actual or estimated caseload at

the time of implementation.11 The costs for Los Angeles County exclude costs for programming

changes to an existing information system, site preparation, and security guards. The remaining

costs represent 97% of the total costs reported by Ernst & Young (1995a). The values for Illinois

are estimates based on the costs of a smaller pilot implementation, while the other estimates are

based on actual contracted costs. Finally, Texas conducted a detailed cost analysis for their pilot,

but did not estimate the cost for a statewide implementation (Schexnayder et al., 1997).

Consequently, we could not develop a three-year estimate based on their data.

Table 8

Three-Year Cost Estimates for Finger Imaging

STATE DATE COST CASELOAD COST/CASE/

YEAR NOTES

Arizona 3/1999 $2,985,399 104,956 $9.48 Includes 6-month

development cost and 2.5

years of fixed annual fee.

Vendor retains ownership of

equipment and software.

California/LA

County

4/1994 $19,467,232 311,001 $20.86 Includes technology vendor,

temporary staff, and project

staff

Connecticut 2/1996 $3,989,095 76,814 $17.31 Excludes GA database.

Includes hardware, software,

maintenance, temporary staff,

and card production

Illinois 12/1997 $4,742,400 200,000 $7.90 Includes operating system,

supporting hardware, and

three-year maintenance.

Temporary staff not included.

Sources: Arizona cost data from Arizona Department of Economic Security (1999); caseload data from State

interviews reflect December 1998 caseload. Los Angeles County data from Ernst & Young (1995a). Connecticut

data from Connecticut Department of Social Services (1998). Illinois Data from Illinois DHS (1997).

We used the average annual cost per case of approximately $14.00 as a benchmark to

compare to the benefits of finger imaging. Two things should be noted about this estimate. First,

although the estimate covers costs for implementation, operation, and maintenance of a fingerimaging system over a three-year period, it does not include the cost for integrating finger

 

11 This assumption leads to a considerably higher estimate of cost per case than was reported by Connecticut, who

based their estimate on the total number of cases over a three-year period. Although Connecticut’s assumption is

valid, it was not consistent with the assumptions made by the other States.
43

imaging with the existing information system. Although this cost may be substantial, the data

were not provided to us by any of the States interviewed. In addition, they will vary considerably

between States. Second, this estimate amortizes development costs over three years. Use of such

a short period produces a larger cost estimate than would be obtained if a longer period were

used.

5.2 Elements of Implementation and Operating Cost

The documentation received from the States identified specific cost elements that were

considered in planning for the implementation and operation of their finger-imaging system.

Table 9 summarizes and organizes these cost elements. The implementation cost elements

represent the one-time expenses required for planning, procuring, and installing the system, and

for initial enrollment of existing cases. Ongoing operations and maintenance includes those costs

required to operate the system on an ongoing basis. The organization of cost elements does not

distinguish either the source of the funds or the organization performing the activities that incur

costs. Finger imaging systems are supported by a combination of Federal and State funds. The

mix of these two sources varies between projects, and the documentation received from the States

did not allow us separate funding sources. Similarly, many activities can be performed either by

State or contractor personnel. States varied regarding which activities they performed

themselves, and which they assigned to contractors. Although we received some general

information regarding the allocation of effort to State and contractor staff, there was not sufficient

detail to fully describe either the process that was used to make the allocations or its results.

In their feasibility study for the State of Arizona, Ernst and Young (1995b) describe

several factors that can drive the system cost. Several system requirements play a critical role in

determining the cost, including the functions that the system will provide, as well as the required

response time, reliability, and/or backup capabilities. Infrastructure modifications, especially any

required development or modification of the central site and establishment of a communication

network, can have substantial cost implications. Finally, implementation of finger imaging may

require additional staff, either on a short- or a long-term basis.

State staff functions were compiled from the feasibility study conducted for Arizona (Ernst

& Young, 1995b) and supplemented by information obtained by our State interviews and Texas

site visits. States varied substantially in the specific positions in their program management team.

Some of the staff functions, such as training development and evaluation, were performed by the

system vendor or by other contractors in some of the State systems.

The cost of telecommunication, necessary to transmit finger-image information to a central

site for matching, may be substantial, depending on the facilities that are already available to the

States. For example, Texas was able to use an existing statewide network with minimal additional

cost. On the other hand, Illinois required the installation of new telecommunications lines at a

cost estimated to be $134,000, with an annual operating cost estimated to be over
44

Table 9

Cost Elements Included in State Estimates

Implementation Costs

Personnel

State Staff (Salary and fringe benefits)

Program manager

Information specialist

Program specialist

Financial services

Data processing

General services

Contracts

Purchasing

Appeals

Outreach

Regional attorney

Evaluation

Training development

Regional Staff

Supervisor

Security

Local Staff

Training

Extra hours during implementation

Temporary Staff

Finger image operators

Security guards

Infrastructure

Central Site Modifications

Local Site Modifications

Communication Lines

Hardware

Workstations

Image Scanners

Cameras

Central Processing and Storage

Software

Image Analysis

Image Matching

Changes to Existing Caseload

Information System

Communication/Networking

(communication lines included in

infrastructure)

Routers

Network Applications

Other Activities, Materials, and Supplies

Client Mailings

Other Outreach Activities

Training Materials

Ongoing Operations and Maintenance

Personnel

State Staff

Regional Staff

Local Staff

Infrastructure

Central site lease

Communication lines

Vendor Costs

Help Desk

Central System operation

Hardware Maintenance

Minutiae Analyst

Project Management

System Upgrades
45

$13,000 (Illinois DHS, 1997). The costs for telecommunication will depend on the capabilities

that are already available, as well as on the possibility of sharing costs with other State agencies.

Site preparation, security, and training are other costs that should be considered. Costs

for site preparation and security were about 3% of the total costs for Los Angeles County (Ernst

& Young, 1995b). Training is often provided by the vendor, and consequently, may not need to

be considered. However, some States may decide, as Texas did, to develop and deliver some of

its own training, especially training focused on the policies and procedures rather than hardware

operation.

The evaluation of the Texas system conducted by Shexnayder et al (1997) shows that

costs in addition to contract costs must be considered when evaluating the cost effectiveness of

biometric systems. In their analysis, vendor cost represented only 13% of the total costs for the

pilot project. Other major cost drivers were the following:

• System software development. This cost represents time spent by the State information

system department to modify legacy software to work with the biometric system. The

time required to perform these activities can be significant and should be considered in

addition to the cost when planning for the implementation of a finger-imaging system. To

reduce both cost and time, Texas limited the integration between the finger-imaging

system and the State information system. Connecticut deferred the integration until after

the initial implementation of finger imaging.

• State office costs. The costs in the State office to manage the project, conduct client

outreach, and develop training materials can be substantial. In Texas, it was slightly

greater than the vendor costs (State office costs include overhead).

5.3 Quantifying the Benefits of Finger Imaging

Benefits from finger imaging vary with respect to the ease with which they can be

quantified. It is relatively easy to assign a value to a benefit that can be tied directly to a caseload

reduction. The value of other benefits is much more difficult to assess. This section considers

three benefits, reduction of duplicate participation fraud, caseload reduction from other sources,

and enhanced program integrity.

The best controlled estimate of caseload reduction due to reduced duplicate participation

is the 1.3% reduction found by comparing experimental and control groups of AFDC clients in

Los Angeles County (Ernst & Young, 1995b). Our estimate extrapolated this value to the FSP

population and adjusted it so that it did not reflect eligible households that might be deterred from

applying for benefits because of finger imaging. The adjusted estimate of a 1% decline in caseload

reflects a 23% deterrence rate, substantially greater than the rate indicated by the former client

interviews conducted in Texas (Schexnayder et al., 1997). Making this relatively large adjustment

produces a conservative estimated of the fraud reduction rate. However, there is uncertainty in

the estimate, because it is based on limited available data.
46

An estimated 1% reduction in caseload, if due to the elimination of duplicate participation

fraud, would represent a permanent savings to the FSP; consequently, the savings is assumed to

be constant over the three-year analysis period. Based on the average monthly household food

stamp benefit for FY 1998 of $172 (FNS, 1998) and a 1% reduction in caseload, the benefit of

finger imaging due to reduced duplicate participation fraud equates to $1.72/case/month, or

$20.64/case/year. This savings is greater than the $14.00/case/year average cost estimated from

Table 8, and comparable to the cost experienced in Los Angeles County. The relationship

between the savings and the cost indicates that finger imaging is a cost-effective method to reduce

fraud in the FSP. According to these estimates, one dollar expended in implementation,

operation, and maintenance of finger imaging will produce $1.47 in savings, over a three-year

period.

The estimates of cost and savings are based on several key assumptions. First, the savings

are based on the FSP only. If finger imaging is applied to other assistance programs, the savings

will be greater, enhancing the cost-effectiveness of finger imaging. Second, cost estimates do not

include several sources of cost, most notably the costs required to modify existing software to

work with the finger-imaging system. Including these costs could reduce the cost-effectiveness of

finger-imaging substantially. For example, if costs were increased by 50%, then the estimated

savings over a three-year period would no longer be sufficient to justify the technology. Finally,

the estimates assume a linear relationship between cost and caseload. This assumption is clearly a

simplification. Certain cost elements, such as the cost for infrastructure or centralized equipment,

may be relatively independent of caseload. Considering these differences would make smaller

systems less cost-effective than larger ones.

Temporary reductions in caseload may also occur when finger imaging is introduced.

These reductions encompass both reduced undeserved benefits and deterrence or delay of

legitimate requests. Consequently, only some of these reductions should be considered to be a

benefit of finger imaging. These reductions vary considerably between States, and there is

insufficient information to determine what percentage of them reflects true benefits of finger

imaging. Where they are found, these benefits should be considered transitional benefits

occurring over the first few months of implementation, and should be given a value that reflects

their ephemeral nature by incorporating estimates of recidivism to limit the amount of savings that

they imply.

Some of the benefits from finger imaging cannot be easily quantified. For example, the

Texas DHS (1997) describes the benefits of finger imaging in allowing clients to take an active

role in fraud prevention, enhancing the integrity of assistance programs, and enabling cross State

matches to further reduce fraud. These benefits may reduce cost, but existing data are not

sufficient to determine the extent of the reduction.

5.4 Summary

Since there is no reliable estimate of the magnitude of duplicate participation in the FSP,

there is uncertainty regarding the cost effectiveness of finger imaging. Available data are

inadequate to make precise estimates of either the costs or benefits of finger imaging for the FSP.

Calculations using the data that are available, supplemented by a number of assumptions, suggest
47

that reduction in caseload covers the costs of finger imaging technology. However, the

percentage of the caseload reduction due to decreased multiple participation is unclear.

The analysis makes no assumption about how costs or benefits are allocated among Federal

or State agencies. In addition, it does not include the cost required to modify existing software to

make it compatible with the finger-imaging system. Finally, it does not take into account that

certain cost elements, such as the cost for infrastructure or centralized equipment, may be

independent of caseload fluctuation.
48
49

6. SUMMARY, CONCLUSIONS, AND DISCUSSION

When finger-imaging technology was first applied to reduce multiple participation fraud in

assistance programs, there were many concerns about the performance and reliability of the

technology in a social service application, as well as about the potential stigma that a finger-image

requirement would place on potential clients. The experience of eight States that have

implemented finger imaging into the process of applying for welfare assistance suggests that many

of these fears were unfounded. Finger imaging has been readily integrated into the human

services programs of the affected states. However, despite the positive reaction to finger imaging

from the State officials we interviewed, there is still uncertainty regarding the extent to which this

technology can reduce multiple participation fraud.

6.1 Summary of Findings

The information obtained from the states and the results of our analysis have brought to

light several factors that are important to consider in planning for, implementing, and operating a

finger-imaging system to reduce the potential for duplicate participation in the FSP. These factors

cover the planing and implementation process, policy and procedures, and cost-effectiveness

issues.

• State representatives uniformly stressed the importance of involving regional and local

staff in the planning process. Activities that were conducted included informational

meetings, newsletters, and training in both the new policies and procedures and in the

operation of the finger-imaging hardware. Some states, such as Texas, gave regional and

local staff considerable freedom to determine how best to integrate finger imaging into the

application process. State representatives who involved local staff in the planning process

thought that these activities eased the transition to finger imaging and improved

acceptance of the technology.

• All states conducted outreach to clients and community leaders to ensure that information

about finger imaging was disseminated and client concerns were addressed. These

activities were viewed as critical to the acceptance of the system. The facts that reaction

of clients has been predominantly positive, and that few clients have stopped receiving

benefits because of any fear or stigma associated with finger imaging is seen a

demonstration of the success of initial outreach efforts. Some concerns about finger

imaging remain, especially among client advocates, but in general, clients have a positive

impression of the technology and think that it helps to ensure the integrity of the welfare

system.

• Integration of the finger-imaging system with the State automated case management

system represents a major consideration in planning and implementation. The effort and

time required to integrate the two systems was too great for the States to complete in their

initial implementations of finger imaging. In fact, as of September 1999, only Connecticut

had integrated finger imaging with its case management system. As a result, for other

States, the largely manual interface between the two systems led to a substantial
50

proportion of the operational problems, errors, and staff complaints regarding finger

imaging. In addition, entering data and reconciling differences between the two systems

had a substantial impact on staff workload.

• States reported that the rapid turnaround time has not been a critical factor since the

biometric requirement is only one step in a multi-step eligibility determination process that

may require several days to several weeks to complete. The speed with which the central

system accepts individual biometric information and returns a match-no match disposition

to the local office, therefore, turns out not to be of practical significance. A less stringent

turnaround requirement can decrease system cost.

• States uniformly report that the implementation of finger imaging was uneventful and that

the technology had little impact on the operation of local offices. The ease of

implementation speaks well for the States’ planning processes, which were often

conducted under severe time constraints imposed by their respective legislatures. The

technology vendors played an active role in producing a smooth transition to use of the

technology.

• There are substantial differences among States regarding exemptions from the fingerimage requirement. The general opinion of the State representatives seems to be that

more restrictive policies regarding exemptions reduce the number of exemptions that are

requested. For example, in Connecticut, exemptions were possible only at the discretion

of the commissioner of the Department of Social Services. Connecticut credits its more

restrictive policy to an extremely limited number of exemptions pursued by clients in the

first year of operations, and recommends that States not set themselves up for significant

exemption claims by publicizing—via an explicit written policy—those conditions under

which an exemption might be granted.

• There is no clear picture regarding how much duplicate participation fraud can be reduced

by finger imaging. Reduction in existing caseload due to refusals to be imaged varies from

almost none to more than 7%. Other measures give similar, conflicting results. Our

analysis used an estimate of fraud reduction based on the evaluation with the greatest

experimental controls, conducted for the AFIRM system in Los Angeles County. Based

on this estimate of approximately 1%, finger imaging appears to be a cost-effective way to

reduce duplicate participation fraud. However, there are several sources of uncertainty in

the estimates of both cost and savings.

6.2 Biometric Technology, Welfare Reform and Assessment of Duplicate Participation

While there is widespread agreement that duplicate participation exists to some degree—a

reality that is occasionally punctuated by the news of extraordinary cases—it is a peculiar form of

fraud that defies precise measurement and quantification. Because there are no reliable national

estimates, the magnitude of duplicate case fraud and its ensuing costs has been a subject of

unresolved debate.
51

The introduction of biometric identification technology is occurring in an environment

with many changes; in such an environment, it is difficult to determine the effect of any single

change. Some of the following changes may confound attempts to measure the effectiveness of

biometric technology.

• The traditional distribution of responsibility for the design and management of welfare, or

cash assistance, programs has shifted from the federal to the State level.

• The nature of State reform initiatives has become increasingly complex and ambitious and

included combinations of components including time limits, family caps, changes in asset

rules and definitions of work and work-related activities, behavioral contracts, and

provisions regarding child immunizations and school attendance (Center for Law and

Social Policy 1996). States have been transforming the culture within their welfare offices

from “check-writing” operations to employment-focused centers.

• In addition to significantly overhauling the old AFDC program, the Personal

Responsibility and Work Opportunities Reconciliation Act (PRWORA) has had a

considerable impact across the spectrum of support programs for low-income families,

including the Food Stamp Program and Medicaid, as well as health, nutrition, and child

care programs. For example, PRWORA established a new time limit on food stamp

benefits that has been referred to as the “3-in-36” rule (Super 1997a, Super 1997b).

Under this provision, food stamp recipients between the ages of 18 and 50 considered to

be “Able-Bodied Adults Without Dependents” are now subject to a new work

requirement.

• PRWORA also immediately rendered ineligible for food stamps a considerable number of

legal immigrants not covered by the law’s few exemptions (Super 1997c).12

• Over this same period during which substantial changes in the welfare system were first

tested by States, then eventually implemented on a broad scale, unemployment indicators

have been exceptionally low by recent standards, and the overall economy has performed

with a remarkable capacity to absorb new workers. Both of these factors are combining

to create substantial downward pressure on welfare caseloads.

Thus, States began and continue to experiment with biometric identification technology in

their welfare programs during an exceedingly complex moment. Among the States that are

testing and evaluating biometric applications, this ongoing program and caseload volatility further

complicates the natural difficulties of definitively measuring this form of fraud. Meanwhile, while

States begin to enjoy more authority over programs and services, they are simultaneously saddled

with ultimate responsibility for their performance. With uncertainty over future funding, naturally

 

12 Upon the signing of PRWORA in 1996, the Clinton administration promised to move to excise from the new law

these provisions against legal immigrants. On June 23, 1998, the President signed Public Law 105-185, the

Agricultural Research, Extension, and Education Reform Act of 1998 (AREERA), which restored eligibility to

some qualified aliens.
52

States are concerned with tightening and refining operations, conserving resources—in part, by

reserving them for legitimately needy families—and maximizing program integrity.

6.3 Future Developments

States are likely to expand the role of finger imaging within States and increase sharing of

information between States. Arizona, Connecticut, New York, and Texas have implemented

finger imaging statewide, and other States are planing to develop statewide systems in the next

year. Statewide implementation of finger imaging will make it much more difficult for individuals

to obtain duplicate benefits by applying at a nearby office

States that have shared finger-image data, such as Connecticut and New Jersey, have

found matches indicating attempts to obtain benefits in multiple jurisdictions. These States have

been able to share finger-image data because both used the same vendor. In general, sharing

information between systems from different vendors requires compatibility between the data

formats used by the vendors (as pointed out in our companion report, Sticha & Ford, 1999).

Vendors are currently developing standards for fingerprint data structures that allow

communication between systems from different vendors, but do not reveal propriety matching

algorithms. These data structures will facilitate interstate comparisons, which are likely to reduce

duplicate participation fraud further.
53

REFERENCES

Arizona Department of Economic Security (1999). Arizona Fingerprint Imaging Program:

Report to the Legislature 1999. Phoenix, AZ: Author.

Center for Law and Social Policy (May 1996). Updated Waiver Information. Washington, DC:

Author.

Center on Budget and Policy Priorities (1996). The Depth of the Food Stamp Cuts in the Final

Welfare Bill.

Cody, S. & Castner, L. (1999). Characteristics of Food Stamp Households: Fiscal Year 1997.

Alexandria, VA: U.S. Department of Agriculture, Food and Nutrition Service.

Connecticut Department of Social Services. (1996). Connecticut Survey of Clients Who Have

Just Been Digitally Imaged for AFDC [On-line]. Available: http://www.dss.state.ct.us/

faq/disurvey.htm.

Connecticut Department of Social Services (March1998). An Overview of the DSS Digital

Imaging Project Implementation and First Year Results (Report to the General Assemply).

Hartford, CT: Author.

DePompa, Barbara (1997). Fingerprint System Points Out Welfare Fraud.

Ernst & Young (1995a). Los Angeles County DPSS AFDC AFIRM Program: Annual Progress

Report, May 1, 1994-April 30, 1995.

Ernst & Young, (1995b). Fingerprint/Hand Imaging System Feasibility Study Final Report.

Illinois Department of Human Services (December 1997). Evaluation Report: Biometric

Identification Demonstrations.

Maxfield, M., & Allin, S. (April 1995). The Income and Eligibility Verification System (IEVS)

Targeting Demonstration: Findings and Guidelines for State Food Stamp IEVS

Programs, Final Report. Washington, DC: Mathematica Policy Research, Inc.

Mintie, D. (May 1998). The U.S. Human Services Eight State Biometric Tour. Biometrics in

Human Services User Group, 2(2), 20-25.

Nawrot, R. (September 1997). New York State Department of Social Services Automated

Finger Imaging System (AFIS). Biometrics in Human Services User Group, 1(5), 2-6.

Schexnayder, D., Olson, J., O’Shea, D., Norris, D., Schroeder, D, & King, C. (1997). Lone Star

Image System evaluation: Final report. Austin, TX: Center for the Study of Human

Resources.
54

Sticha, P. J., & Ford, J. P. (1999). Introduction to Biometric Identification Technology:

Capabilities and Applications to the Food Stamp Program. Arlington, VA: R. Lewis &

Co., Inc.

Super, David (1997a). Overview of the Food Stamp Time Limits for People Between Ages 18

and 50. Center on Budget and Policy Priorities.

Super, David (1997b). Who Will Lose Food Stamps Under the Three-Month Cut-Off. Center on

Budget and Policy Priorities.

Super, David (1997c). Legal Immigrants’ Eligibility for Welfare, Medicaid, SSI, and Food Stamps

Under the New Welfare Law. Center on Budget and Policy Priorities

Texas Department of Human Services. (1997). Evaluation of the Lone Star Image System.

U.S. Department of Health and Human Services, Office of Inspector General (May, 1996).

Review of the Ongoing Los Angeles County Fingerprinting Demonstration Project

(Report A-09-95-00054).

U.S. Department of Health and Human Services, Administration for Children and Families (1998,

August). Welfare Caseloads: Families and Recipients, 1936-1997. Available at Internet

site http://www.acf.dhhs.gov/news/press/1998/3697.htm (accessed March 3, 1999).

U.S. Food and Nutrition Service (1998, October). Nutrition Program Facts: Food Stamp

Program. Available at Internet site http://www.usda.gov/fcs/stamps/fspfor~1.htm

(accessed March 3, 1999).

U.S. Food and Nutrition Service, Data Base Monitoring Branch (1998, November 25).

Preliminary Summary of Food Assistance Program Results for September 1998. Available

at Internet site http://www.usda.gov/fcs/pid/birdsep.txt (accessed March 3, 1999).

United States General Accounting Office (1994). Food assistance: Potential Impacts of

Alternative Systems for Delivering Food Stamp Program Benefits (GAO/RCED-95-13).

Washington, DC: Author.

United States General Accounting Office (1995). Electronic Benefits Transfer: Use of

Biometrics to Deter Fraud in the Nationwide EBT Program (GAO/OSI-95-20).

Washington, DC: Author.

United States General Accounting Office (1997). Food Stamps: Substantial Overpayments

Result from Prisoners Counted as Household Members (GAO/RCED-97-54).

Washington, DC: Author.

United States General Accounting Office (1998a). Food Stamp Overpayments: Households in

Different States Collect Benefits for the Same Individuals (GAO/RCED-98-53).

Washington, DC: Author.
55

United States General Accounting Office (1998b). Food Stamp Overpayments: Thousands of

Deceased Individuals Are Being Counted as Household Members (GAO/RCED-98-53).

Washington, DC: Author.

U.S. Public Law 104-193 (1996). 104th Congress, 2nd Session, August. Washington, DC: United

States Congress.

Wayman, J. L. (September 1997). Large-scale Civilian Biometric Systems—Issues and

Feasibility. In CTST ’97: The art of implementation (conference proceedings). Bethesda,

MD: CardTech/SecurTech, Inc.

Westin, A. F. (1996). Public Attitudes Toward the Use of Finger Imaging Technology for

Personal Identification in Commercial and Government Programs. Available at Internet

site http://www.nrid.com/privacy.
56
A-1

APPENDIX A. STATE STAFF INTERVIEW GUIDE

Name:__________________________________ State:__________ County:___________

Position:________________________________ Interviewer:_____ Date:_____________

Introduction

Hi, my name is _______________ and I represent Caliber Associates, a public policy research

firm in Fairfax, Virginia. We are currently gathering information for the U.S. Food and Consumer

Service from a number of states which are planning to use or are currently using biometric

technology as a method for reducing client fraud in their human services programs.

______________, our project manager, has spoken with ______________, of your state office

about what we hope to accomplish. S/he agreed to work with us and has referred me to you to

respond to a series of questions which we are asking of all states. We’re anticipating about one to

not more than two hours to complete the interview. Is this a convenient time, or would you

rather schedule a time in the next several days?

I. BACKGROUND

29. What type(s) of biometric technology is your state planning, implementing, or currently

using?

30. In what program environment is the system to be/being implemented (AFDC, food

stamps, both)?

31. Please describe the history and current status of your planning and implementation

process. What activities were undertaken or are anticipated (i.e., trace major milestones,

what stage is your state currently in, number of jurisdictions)? Who/what agencies are

involved?
A-2

32. Please describe the rationale and impetus for using biometric technology (e.g., pressure

from state legislature, etc.).

33. For what reasons was [form of technology] selected over other types of biometric

technology? What other types were considered? In choosing [form of technology], what

are/were your expectations regarding the following:

33.a. Expected time required for [form of technology] to generate a match/non-match

(turnaround time)?

33.b. Expectations regarding the need for human examiners required?

33.c. Expected false positive and/or false negative rate of [form of technology]?

33.d. Expected disability/failure rate of [form of technology]?

34. What were/are the costs of acquiring the technology? Are these the full costs (issue: Is

the state under a temporary special arrangement with the vendor, as in Texas?)?

The following questions explore design, operations, impact, and evaluation issues. Continue

with participating states as appropriate.

II. PROJECT DESIGN

29. What process was/will be used to prepare staff for the implementation of [form of

technology] in your State, both philosophically as well as operationally?

30. What kinds of advance outreach to clients did/will you undertake (e.g., client letter,

promotional material in office, video)?

31. What procedures are you planning/using to administer the technology to clients (i.e.,

where, when, how, who)?

32. Is there a policy for exempting clients? Please describe policies and procedures?

33. Please describe procedures for ensuring client due process (i.e., investigation,

disqualification).

34. How is the [form of technology] interfaced with other management information systems?

How would you describe the extent of technical changes that were required for interface?

What flexibility is there to expand the system to accommodate future needs?

35. What planning or implementation problems have been encountered and how have they

been resolved?
A-3

III. PROJECT OPERATIONS

29. What organization and staffing changes have become necessary to accommodate the

project, if any (new positions created, staff relocations, etc.)? Do you expect these to be

permanent changes?

30. What are your staff reactions to the new technology?

31. What kinds of staff training have been provided (who provided, amount of training,

subjects covered, problems encountered, cost/burden)?

32. How have clients reacted to the system?

33. Is your policy for exempting clients working as intended? Do you suspect any

misuse/abuse of the established exemption policy?

34. Have client due process procedures yet been tested? Please describe any problems

encountered.

35. How has the [form of technology] performed thus far? What operational problems have

been encountered? How have these problems been resolved?

36. Are you anticipating any upcoming changes in the administrative/legal/legislative

environment that might affect project operations?
A-4

IV. PROJECT OUTCOMES AND IMPACT

29. Are you aware of what your current “hit” rate is (during last full quarter, for example)?

What proportion of hits are attributed to client fraud versus administrative error?

30. Is there any available data on the reliability and/or failure rate of [form of technology]?

31. What impact is the project having on the average length of time required to process and

monitor cases?

32. What impact is the project having on general office operations at this point? Is there any

known collateral impact on related operations?

33. Are the initial results of the project meeting your expectations? How so?

34. What, if any, course corrections or alternative approaches are being considered?

35. What should other jurisdictions which may be planning or implementing [form of

technology] be prepared to encounter?

V. EVALUATION AND TRANSITION ISSUES

29. Is an evaluation of the system planned/underway? Please describe methodology (in

general terms).

30. Is a cost analysis anticipated? How are you accounting for project costs and benefits?

How is the analytical model constructed?

31. What were the most difficult research design issues that you faced in developing an

evaluation approach?

32. In what period of time do you expect the evaluation to generate meaningful results? In

what ways do you anticipate the power of the evaluation will be limited?

33. What do you see as the major issues to be addressed in transitioning from demonstration

status to permanent operation of the system in the future?
B-1

APPENDIX B. PROFILES OF STATE FINGER-IMAGING SYSTEMS
B-2

 ARIZONA WESTERN REGION

OVERVIEW

Administering Agency The Department of Economic Security (DES)

administers the Arizona Fingerprint Imaging

Program (AFIP).

Biometric Technology Fingerprint imaging

Contractor(s) North American Morpho Systems, Inc. (Morpho)

Current Status Food Stamp, General Assistance, and TANF

program recipients are imaged statewide. The

programs are state-administered.

PROJECT TIMELINE

PLANNING AND IMPLEMENTATION

Impetus

In 1995, the Arizona Department of Economic Security contracted with Ernst & Young to

conduct a cost-benefit analysis of an early and continuing fraud detection program utilizing

computerized fingerprinting or hand imaging systems in the Aid to Families with Dependent

Children (AFDC) program. The Ernst & Young study consisted of four principal components:

1) a literature search and survey of other states using fingerprinting technology, 2) exploration of

legal issues associated with such technology, 3) interviews with DES employees to assess the

1992 1993 1994 1995 1996 1997 1998 1999

07/95: Ernst & Young's cost-benefit

analysis contract awarded.

05/96: Legislation mandated

fingerprint imaging but funding delayed 1 year.

03/97: RFP issued.

08/97: Signed contract with Morpho.

10/97: Morpho began designing workstations.

06/98: All counties using finger imaging.

01/98: Pilot began in 10 offices in La Paz, Mohave, and Yuma counties.
B-3

current AFDC eligibility process, and 4) collection of cost data on other fingerimaging systems

and from vendors. Enabling legislation followed in May 1996.

Implementation

Morpho began designing workstations in October 1997 and established its central unit in Austin,

Texas, co-located with Morpho’s Texas operations. Implementation began in January 1998 with

a three-month pilot in 10 offices located in District IV, a rural district on the State’s western

border with California, beginning with La Paz, Mohave, and Yuma counties. It took

approximately 30 days to prepare and 4 days to bring the system on line. Implementation in

Maricopa County was completed in April 1998, followed by Pima County in early May 1998.

The State’s 88 local offices were operational by June 1998 under a system that included 89

enrollment stations, 3 investigative workstations, and 92 portable workstations.

Staffing

At the State office level, six existing employees were transferred to AFIP under special two-year

transfers. At the local office level, no new operators were hired; fingerimaging responsibilities

were absorbed by existing positions.

POLICIES AND PROCEDURES

Administering Procedures

All adults receiving benefits must be imaged, including minor parents. For TANF,

recertification occurs every six months.

Exemption Policy

No formal statement of exemption, but illness, arthritis, or the absence of any imageable fingers

can result in a temporary or permanent exemption.

Investigation and Due Process

In the event of a potentially fraudulent match, the local office or the caseworkers are not notified

until after Morpho's minutiae experts have sent a match to the Office of Special Investigation

(OSI) and OSI validates the fraud. No fraud matches have yet been found with finger imaging.

If fraud were to be alleged, the client would receive standard administrative due process. Under

existing standards, OSI examines a case file, conducts a visit to the home, and notifies the client

of a right to a hearing.

PROJECT OPERATIONS

Staff reported experiencing operating problems within the normal range (e.g., some problems

downloading from portable/phone lines), concluding that the fingerimaging technology has

performed well. Morpho maintained two technical support staff on site to assist with such
B-4

problems. Interviewed during their roll-out process, staff also reported that the intent of their

pilot was not to “prove” anything, but only to identify and correct operating bugs. The State

purchased a complete, proven system from Morpho and staff are, therefore, able to concentrate

their energies on installing the workstations and training staff. Assured that the State is not

sharing biometric information with other agencies or States, clients are reportedly accepting of

the technology. As in Texas as well as some other States, terminals are positioned such that

clients can observe the imaging process, which tends to have a calming effect.

PROJECT OUTCOMES AND IMPACT

Office Operations

Minimal impact because the turnkey system of Morpho rolls out quickly.

Clients

Positive impact. The monitor is often turned around during the process for the client to see the

system work. Assurances of no information sharing help those imaged to focus on the benefits

of positive identification, such as the removal of certain social stigma.

Caseload

Presently 75,000 records in the database (with room for another "free" 525,000). The State has

closed at least ten cases because of failure to comply with the imaging requirement.

Operating Costs

No cost impact information available.

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

The cost analysis is still incomplete. Breaking even should be relatively easy since a low 1.3%

savings goal was used to calculate the break-even figure. Since $300 to $400 million are

disbursed per year in Arizona, saving or cost-avoiding a little over 1% may not be difficult in

today's welfare environment.

Long-term Issues and Actions

While the State of Arizona has an EBT pilot in the works, no links presently exist, or are

planned, between the finger imaging programs and EBT, or, for that matter, with any point-ofsale efforts.
B-5

CALIFORNIA WESTERN REGION

OVERVIEW

Administering Agency The California Department of Social Services

(CDSS) administers the Statewide Fingerprint

Imaging System (SFIS).

Biometric Technology Fingerprint imaging

Contractor(s) Not yet chosen.

Current Status Food Stamp, General Assistance (at the county's

option), and TANF (CalWORKs) program

recipients are imaged in several county offices. The

programs are state-supervised and countyadministered.

PROJECT TIMELINE

PLANNING AND IMPLEMENTATION

Impetus

SB 1780 requires fingerprint imaging to deter and detect multiple-aid welfare fraud. Fingerprint

imaging technology was selected based on the demonstrated results of AFIRM in Los Angeles

County, as well as known and recognized properties of the technology, including its maturity,

cost, and accuracy.

1992 1993 1994 1995 1996 1997 1998 1999

Fall '93: Strategic planning group meeting.

12/97: Intent to award the

SFIS contract to Morpho

was issued until EDS filed

a timely protest.

03/98: SFIS procurement was

cancelled and had to be rebid

without the state's M/WBE

requirements.

06/98: Second RFP issued.

03/99: Contract to be awarded.

09/99: Implementation of Phase 1 to begin.

01/00: Implementation of Phase 3 to begin.

11/99: Implementation of Phase 2 to begin.
B-6

Information Gathering

California has a number of expectations of a qualified vendor. The vendor must be able to

provide expert fingerprint examiners who are capable of providing testimony in a legal

proceeding. These examiners will be responsible for verifying every open-search “hit” and every

closed-search “miss” before the match/no match results are forwarded to the originating county

office. The State has also established specific performance thresholds for a qualified vendor.

For example, for a two-finger open search (two corresponding records exist), the system must be

able to produce a correct “hit” indication at least 96% of the time; where no corresponding

records exist, the system must be able to produce a “no candidates found” indication at least 80%

of the time (other 20% includes a group of close matches).

Implementation

California has encountered legal challenges that continue unresolved. When the State is ready to

proceed with implementation, SFIS is expected to be implemented in three phases over a fivemonth period. Phase I will include approximately 10 percent of county sites and will operate for

two months prior to the beginning of Phase II. Phase II will add an additional 30 percent of

county sites (bringing total to approximately 40%) and will operate for two months prior to the

beginning of Phase III. Phase III will complete the statewide roll-out. SFIS will absorb the

systems currently operating independently in seven other counties.

Staffing

Several positions were created at the state level to provide oversight and management of the

project. The counties will be responsible for securing operators to take the fingerprint images of

the clients and support personnel; counties will have flexibility in obtaining staff (e.g., existing

staff, new county employees, contract staff). The State will reimburse the counties for operator

and support personnel costs based on caseload. The contractor will be responsible for providing

staff to operate the central site system, perform validation, and operate a help desk.

POLICIES AND PROCEDURES

Administering Procedures

All adults receiving benefits must be finger imaged. The policy on when to be finger imaged

varies. Existing clients will be added to the SFIS via a call-in. For TANF, the existing clients

will be fingerprint imaged during the eligibility process within 6 months of the county coming

on-line with SFIS. For Food Stamps, clients will be imaged prior to issuance of food stamps,

within twelve months of the county coming on-line with SFIS. For those exempt from the

process in either program, the household is certified by an out-of-office interview. However,

attempts to obtain fingerprint images are made when a household member is in the office for any

reason.
B-7

Exemption Policy

Proposed Food Stamp regulations exempt a household member who has no fingers, who has a

medically verified physical condition which renders him/her unable to comply, or who has not

reached the age of 18, unless applying for Food Stamps as his/her own household. Proposed

TANF regulations temporarily exempt persons with both hands damaged and persons with other

medically verified physical conditions which preclude them from coming into the office.

Proposed TANF regulations permanently exempt persons missing all ten fingers. Exemptions in

the GA program are left to every county's option.

Investigation and Due Process

In the event of a potentially fraudulent match, the local office or the caseworkers are not notified

until after the Contractor's minutiae experts have verified any open-search "hit" or any closedsearch "miss." If necessary, the SFIS Contractor will be responsible for providing expert

fingerprint examiners to testify in court. If fraud were to be alleged, the client would receive

standard administrative due process. These investigation and due process procedures, regarding

finger imaging in particular, are still under development.

PROJECT OPERATIONS

The system is not yet operational; no data available.

PROJECT OUTCOMES AND IMPACT

Office Operations

The impact of finger imaging on pilot office operations has been positive. Since the technology

has been in use for several years in some California counties, all indications are that county

welfare directors, as well as state level staff, are impressed and confident in fingerprint imaging.

Clients

No client impact information available.

Caseload

No caseload impact information available.

Operating Costs

No cost impact information available.
B-8

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

California's largest concern is selecting a vendor and rolling out the finger imaging program to

all counties. SFIS will be implemented statewide in three phases over a five month period.

Phase 1 will consist of approximately 10% of county sites and will operate for two months prior

to Phase 2. Phase 2 will add an additional 30% of county sites (bringing the total to

approximately 40%) and will operate for two months prior to Phase 3. Phase 3 will complete the

statewide rollout.

Long-term Issues and Actions

No long term issues at this point.
B-9

CONNECTICUT NORTHEAST REGION

OVERVIEW

Administering Agency The Department of Social Services (DSS)

administers the Digital Imaging System.

Biometric Technology Finger imaging

Contractor(s) Polaroid Corporation (formerly NBS Imaging

Systems, Inc.) and SAFlink Corporation (a

subsidiary of the National Registry, Inc.)

Current Status General Assistance and TANF (Connecticut's

Temporary Family Assistance, or, TFA) program

recipients are imaged statewide. The programs are

state-administered.

PROJECT TIMELINE

PLANNING AND IMPLEMENTATION

Impetus

Legislation (Substitute House Bill 7010) was signed in July 1995 requiring DSS to implement a

“biometric identifier system” with the following stipulations: 1) review existing technology and

to the greatest extent possible, select a system that is compatible with systems in place in

surrounding states, 2) DSS commissioner authorized to enter into memorandum of understanding

with commissioner of DMV. Connecticut was “looking to kill two birds with one stone:” 1) to

deter fraud and, therefore, reduce General Assistance expenditures, and 2) to establish a single,

1992 1993 1994 1995 1996 1997 1998 1999

07/95: Enabling legislation signed into law.

07/95: Invited contractors for demonstrations.

10/95: Conducted site visits to NJ and NY.

09/96: Completed statewide rollout.

01/96: Signed contract with Polaroid.

01/96: Implemented finger imaging in one office.

08/95: Formed a statewide Digital Imaging Workgroup.

08/95: Initiated a review of existing biometric systems.
B-10

statewide automated database to house all data (manual or automated) on the GA caseload, with

a uniform identification system.

Information Gathering

In addition to finger imaging, DSS looked at voice verification, hand geometry, and retina

scanning; did not look at signature verification. Tested voice verification, but demonstrations

did not work. Invited a number of vendors in for demonstration (Morpho, Printrak, National

Registry, Iriscan). DSS also looked at New York and New Jersey, where they observed field

operations and talked with State personnel. Finger imaging was found to be accurate, clean, and

quick. An important consideration to DSS was the desirability of human examiners to certify

results.

NBSI was under contract with the state Department of Motor Vehicles at the time. DSS

piggybacked on the contract so that, while upgrading DMV's hardware and software, NBSI

would create a similar platform for DSS. DSS and DMV negotiated an amendment to DMV’s

contract with NBSI, which included a three-year agreement to operate the DSS system and attain

technological compatibility with the DMV digital license system.

Implementation

DSS attempted to build internal support within the agency first, in recognition of the difficulties

of building external support without it. DSS then formed a statewide Digital Imaging Workshop

with representation from each of the DSS regional offices, all major departments within DSS's

administrative organization, and from some of the State’s 169 towns.

The State's five regional offices were divided into 3 phases for enrollments. Implementation

began with the North Central Region DSS office. Within the first two months, permanent

workstations and communications with the central site were established in 16 DSS offices and 20

General Assistance sites. As in Texas, DSS conducted a mass call-in to bring in the existing

caseload for enrollment, while also using portable equipment in some towns.

DSS implemented the system with no connection to Legacy, primarily due to a combination of

the fact that DSS had only 6 months to implement and that such interfacing is typically labor

intensive and would consumed more time than was available. The most significant

implementation problem was the logistics and and planning that were necessary to set up and

operate the mass enrollment centers across the State’s 169 towns. Each office was given latitude

to incorporate the new procedures within their own office routines.

For the convenience of clients, and to get the system up as quickly as possible, DSS set up

temporary workstations in various locations, including an empty state hospital and office

building. The portable workstations were relatively convenient, and fold up in a suitcase.
B-11

Staffing

DSS hired 40-50 new enrollment operators, drawn from candidates identified by a temporary

agency, as well as qualified AFDC recipients identified by DSS staff. No new titles or

bureaucratic changes were required. The finger imaging requirement created the need for an

additional person in some of the local offices because staff would otherwise have been taken

away from other important functions.

POLICIES AND PROCEDURES

Administering Procedures

Both index fingers imaged and photo taken. No challenges to compliance by recipients. The

system is closed; operators image themselves to log onto the system.

Exemption Policy

No specific exemption policies. At the discretion of the regional managers. Two exemptions in

two years. Had only one or two recipients ask for a religious exemption.

Investigation and Due Process

Have human examiners. Potential matches of fraud are referred to DSS's fraud unit for a fair

hearing. Since the inception of the program, 32 cases have been referred to the unit for review.

PROJECT OPERATIONS

DSS encountered standard and expected operating problems initially. The system has had

minimal impact on office operations and was institutionalized quickly. It perhaps adds

approximately 15 minutes to the application process.

PROJECT OUTCOMES AND IMPACT

Office Operations

Minimal impact as the new process only adds 15 minutes to the typical application process.

Institutionalized quickly. Although DSS hired approximately 40-50 enrollment operators, it did

not engage in any title or bureaucratic changes. Mixed reaction from staff. Fraud staff very

enthusiastic.

Clients

To measure clients' satisfaction with the new system, DSS conducted a survey of 327 GA and

TFA clients. 88.4% felt that they had not been inconvenienced by the new system. 85.1% did

not object to the process, and 87.1% felt that the system would help prevent cheating.
B-12

Additionally, 0.6% said they knew of someone who was prevented from cheating by finger

imaging.

Caseload

GA and TFA caseloads declined by 7,568 and 6,359, respectively in 1996. To date (as of

February 1998 interview), 1,206 total "hits," of which 708 were administrative error, 467 nonfraud, and 31 fraud referrals (of which 2.6% attributed to fraud, or, 8 cases).

Operating Costs

In 1997, combined savings on both programs were estimated at $6.0 million. In addition, the

State estimates that the initial start-up costs for the Digital Imaging System and GA database

were $5.1 million for three years. Savings may have been realized in the first year.

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

After two years of statewide operation, Connecticut is looking at "dual" or "layered" biometrics

as another possibility for client identification. Specifically, the state is considering the use of

facial imaging to better identify clients who are difficult to fingerprint.

Long-term Issues and Actions

No long-term issues at this time.
B-13

ILLINOIS MIDWEST REGION

OVERVIEW

Administering Agency The Department of Human Services (DHS)

administers finger imaging's Automated

Identification and Match System (AIMS) and the

Illinois Retinal Identification System (ISCAN).

Biometric Technology Retinal scanning (recently discontinued) and finger

imaging

Contractor(s) Printrak International, Inc., for finger imaging, and

EyeDentify, Inc. for retinal scanning

Current Status Finger imaging presently used on TANF program

recipients only, in three offices. Retinal scanning

discontinued. TANF is state-administered.

PROJECT TIMELINE

PLANNING AND IMPLEMENTATION

Impetus

In August 1994, the Illinois General Assembly passed Public Act 88-554, which required the

Department of Public Aid to implement a 12-month project to determine the cost effectiveness of

electronic fingerprint imaging in detecting and deterring multiple case fraud. The Automated

1992 1993 1994 1995 1996 1997 1998 1999

07/94: Legislation

mandated a 12

month pilot.

02/96: Waiver

granted, for 36

months.

05/96: Alton & Granite City began retinal scanning.

02/97: AIMS began (contractor

procurement delayed start).

06/97: Legislation extended pilots from 12 to 36 months.

07/97: Reorganization of State human services

agencies (DHS took over DPA biometric projects).

03/98: Retinal

scanning

discontinued.

06/98: Report sent

to Secretary with

recommendation

for rollout

expansion across

the State.
B-14

Identification and Match System (AIMS) was designed to test electronic fingerprint imaging in

three metropolitan Chicago offices, including DuPage, Western, and West Suburban, which were

prescribed by the law based on county population size. The Act also allowed for the testing of

retinal scanning identification (ISCAN), which was operated in East Alton and Granite City, two

Madison County local offices.

Information Gathering

In its March 1998 report on the AIMS and ISCAN projects, Illinois reported that it had

uncovered 36 cases of multiple case fraud, costing taxpayers more than $326,000 in illegally

obtained welfare benefits. Extrapolating from a 1993 estiamte of the national cost of fraudulent

welfare schemes, Illinois estimated (based on caseload size) that its share off the loss could be in

excess of $1 billion per year.

Implementation

The AIMS and ISCAN projects were implemented in metropolitan Chicago and in Madison

County, respectively, as described earlier. In February 1996, a waiver of federal regulation was

granted to permit Illinois to proceed with the projects, but with the stipulation that the projects

continue for a period of three years, rather than only 12 months.

Staffing

No new positions were created or staff hired to support either the AIMS and ISCAN projects;

new functions were added to existing positions.

POLICIES AND PROCEDURES

Administering Procedures

The general policy for who must be finger imaged or retinal scanned is that all adult TANF

applicants and recipients (including second and minor parents) must be finger imaged. The

policy on when to be finger imaged or scanned coincides with the standard redetermination

period. TANF clients come in face-to-face at least once a year and are at least finger imaged

then. If clients are at the six-month point when a mail-in redetermination usually suffices, they

are also asked to go to a DHS office for biometric processing.

Exemption Policy

Exemptions differ in the finger imaging and retinal scanning programs. Temporary exemptions

apply in finger imaging when the system is not working or the client has bandages on the fingers.

A permanent exemption is recognized for those missing fingers. Temporary exemptions apply in

retinal scanning when the system is not working or the client has eye sickness. A permanent

exemption is recognized for those who are blind or diabetic.
B-15

Investigation and Due Process

In the event of a potentially fraudulent match, the local office or the caseworkers are not notified

until after the Contractor's secondary examiners have verified the match. Administrative

matches sometimes occur because a case number is incorrectly keyed the first time a person is

scanned or because a person has more than one case. After the administrative matches, there has

been only one match so far. In that case though, the client may not have been trying to defraud

and may have lacked the required "intent." If fraud were to be alleged, the client would receive

the standard administrative due process of 15-day notice and a hearing.

PROJECT OUTCOMES AND IMPACT

Office Operations

Retinal scanning has been discontinued. Because it was slower and less reliable than finger

imaging, the pilot was halted after about one year. Finger imaging has had a minimal impact on

office operations. Staff have been receptive due to being on the cutting edge of welfare fraud.

Clients

Clients have been receptive, too. In client surveys, 82% of clients think requiring a print is

acceptable.

Caseload

No caseload impact information available.

Operating Costs

Retinal scanning was discontinued because it takes three times as long to do a retinal scan versus

a fingerprint image (personnel cost-wise). Personnel costs for retinal scanning would have

increased by $.75M if rolled out across the State. Any financial impact because of either

biometric will be difficult to predict since multiple enrollments constitute less than one percent

of the TANF caseload in Illinois. New hire legislation confounds any conclusions because it has

cut down the fraud figure, too.

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

The full rollout of finger imaging across the State is likely and would probably take one year

from RFP issuance through completion, since just a small workstation needs to be added to many

of the offices. Cook County, with 60% of the caseload probably would be rolled out first. The
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Food Stamp program will very likely join the finger imaging effort at some point during or

shortly after the TANF rollout.

Long-term Issues and Actions

No long-term issues at this time.
B-17

MASSACHUSETTS NORTHEAST REGION

OVERVIEW

Administering Agency The Department of Transitional Assistance (DTA)

administers the Image Identification System (IIS).

Biometric Technology Finger imaging and facial matching

Contractor(s) The contractor for both technologies is Viisage

Technology (formerly Lau Technologies). The

National Registry, Inc., is also a subcontractor for

the finger imaging project.

Current Status Finger imaging is used on TANF program

recipients only. Facial matching is used in

conjunction with the TANF program, too, as well as

the Food Stamp and General Assistance programs.

The assistance programs are state-administered.

The biometric systems are both in the test phase in

three offices.

PROJECT TIMELINE

PLANNING AND IMPLEMENTATION

Impetus

The fingerprint imaging demonstration was mandated by the Massachusetts legislature. A

demonstration of the facial imaging technology was proposed by the vendor, which was offered

to the Department of Transitional Assistance at a reasonable cost.

1992 1993 1994 1995 1996 1997 1998 1999

09/94: Over-the-counter instant issuance Image ID System pilot.

04/95: Finger imaging and facial matching

computer system installed in 39 local offices in 30 days.

04/96: Fingerprint imaging pilot began in 3

offices (facial matching already statewide).

??/??: Release of IIS RFP.

?
B-18

Implementation

The facial/finger image computer system was installed in the local offices beginning in April

1995. Installation was completed in all 39 local offices on a staggered basis in a 30-day period,

at which point the facial imaging component was available statewide. The Massachusetts

legislature also selected three offices—Springfield/State, Springfield/Liberty, and Lawrence—to

pilot test the finger imaging system, which continues in a pilot stage.

Staffing

Each of the 39 offices has an ID operator and one or more back-up operators. Office operations

are supported by a number of EDP coordinators, who are available to address technical matters.

The objective is to eventually have one EDP coordinator per office.

POLICIES AND PROCEDURES

Administering Procedures

All adults receiving benefits must comply including minor parents.

Exemption Policy

For fingerprint imaging, a temporary exemption exists for a documented illness, but that

exemption ultimately expires. An exemption for a documented inconsistency with religious

beliefs also exists. No exemptions have been granted in fingerprint imaging to date. Facial

matching has these exemptions as well as an SSI exemption for the elderly.

Investigation and Due Process

So far there has been only one referral to the Bureau of Special Investigation (BSI) in which a

multiple locations suspect disappeared. If fraud were to be alleged, the client would receive

standard administrative due process.

PROJECT OUTCOMES AND IMPACT

Office Operations

In an independent evaluation that was done for both biometrics, staff gave a positive reaction

because of not having to confront recipients when fraud is alleged.

Clients

Client advocates came out against finger imaging. Facial matching has been an easier sell (one

client advocate clearly favors facial). Have had photo IDs since 1982, so facial matching is
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"business as usual" for the client. The fact that images are being used in a new way (matching)

is completely behind the scenes and transparent to the operators.

Caseload

No caseload impact information available.

Operating Costs

No cost impact information available.

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

Facial matching may not be as far along in accuracy as contractors are suggesting.

Massachusetts is considering two biometrics to have 100% accuracy.

Long-term Issues and Actions

Both programs are offshoots of on-site EBT cards. While the EBT and biometric systems are

presently separate, a link will ultimately be created between the biometric eligibility system and

the demographic information on the EBT cards.
B-20

NEW JERSEY MID-ATLANTIC REGION

OVERVIEW

Administering Agency The Department of Human Services, Division of

Family Development, administers the Recipient

Identification Program (RIP).

Biometric Technology Finger imaging

Contractor(s) SAFlink Corporation (a subsidiary of the National

Registry, Inc.)

Current Status General Assistance program recipients in 104

municipalities are finger imaged. General

Assistance is state-supervised and countyadministered.

PROJECT TIMELINE

PLANNING AND IMPLEMENTATION

Impetus

Assembly Bill No. 2953 was introduced in October 1993, which required high technology finger

imaging identification of public assistance recipients. The New Jersey Department of Human

Services, Division of Family Development, was mandated through language contained in the

Appropriations Committee Budget to issue a Request for Proposal for a pilot project to test the

1992 1993 1994 1995 1996 1997 1998 1999

10/93: Assembly Bill introduced, requiring finger imaging.

03/94: Planning process began, to create an RFP.

09/94: RFP distributed to interested contractors.

11/94: Bidding conference held.

03/95: National Registry won contract.

07/95: Began finger imaging.

11/98 Contract due to expire (all 4 extensions have been utilized).
B-21

feasibility of fingerprinting recipients of General Assistance (GA) in order to positively identify

applicants and prevent the fraudulent duplication of benefits or other misuse of the GA program.

Information Gathering

The information gathering process began in March 1994 with the creation of a work group with

representation from various areas of the division. An RFP was finalized to which four vendors

responded. The three lowest bidders were selected to complete a benchmark test, during which

100 cards were examined by each vendor. Performance on the test was evaluated on the basis of

both response time and match parameters.

Implementation

The pilot area consists of 104 municipalities within approximately 15 miles of Newark, New

Jersey, representing approximately 50 percent of the State’s GA population. Of the 104

municipalities, 14 were deemed automated offices and 90 were deemed manual offices, which

have very small caseloads. The manual offices take prints (3 of each finger) using non-staining

ink pads and photographs with polaroid cameras. The prints and photos are sent to Trenton State

office, where they are scanned into the system. The system determines the quality of the prints,

selecting the best of the three.

Staffing

The Trenton State office is staffed by a project leader, an administrative assistant, and a

computer repair technician. A remote site is also maintained in Newark. Back-up staff provide

database support from an office in Tampa, Florida, from which they can manipulate the system

remotely.

POLICIES AND PROCEDURES

Administering Procedures

All adults receiving benefits must comply including minor parents. Clients will need to be finger

imaged every three months, as that is when the GA checks are mailed from the counties.

Exemption Policy

The general policy for who must be finger imaged is that there are no exemptions. If the client is

homebound, a manual imager visits the home. If fingers are bandaged and cannot be imaged,

that is acceptable for two months, but the client is taken off the rolls after two months if the

bandage is not removed. If the client is an amputee, the General Assistance office will keep a

facial image on file, to be used for matching purposes.
B-22

Investigation and Due Process

In the event of a potentially fraudulent match, the municipality where the client attempts to

obtain benefits will initiate an inquiry. Once they are compared and believed to be a match with

another municipality, the contractor is called. The contractor then informs the municipality

where the client’s prints were first taken. Manual sites call Trenton and then Trenton in turn

calls the municipality where the client may already be receiving benefits. Disqualification is

determined after an investigation. Less then a dozen matches since implementation on July 10,

1995 have been attributed to client fraud attempts, however. If fraud is alleged, the decision as

to who confronts the client with match information is left to county-level supervisors. As a

result, some offices like immediate confrontation, particularly those with on-site investigators,

while others do not. The client receives standard administrative due process, and can request a

Fair Hearing.

PROJECT OUTCOMES AND IMPACT

Office Operations

According to the contractor, finger imaging has had no impact on general office operations.

While no hard data is available, all directors from the agencies involved were in favor of its

implementation, and no adverse problems have resulted from the use of finger imaging.

Processing takes very little time and has not affected the processing and monitoring of cases. It

takes about 2-3 minutes for an experienced operator to process a client, assuming the client is

cooperative.

Clients

Likewise, no hard data is available on client reaction to the technology. The closest real

evidence to client acceptance is the fact that of 5,173 images obtained in five working days at

one point, only 3 did not want to be imaged (2 because their hair was not “right” for the

accompanying photo). Acceptance seems to be the norm, in part, because imaging removes the

stigma of receiving benefits.

Caseload

The initial use of the system was, of course, to stop “double dippers.” The number of clients

dropped from the rolls because of this technology has not been measured, but New Jersey

believes the benefits of imaging can be addressed on its deterrent factor and its positive

identification of the clients.

Operating Costs

When the 18,000 on the rolls of the finger imaging pilot were matched with those of New York

State, 338 hits resulted. To date, investigation of these hits has resulted in roughly $8,300 in

annual savings and a caseload reduction of approximately 20.
B-23

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

The largest problem in the near future is moving from issuing the RFP to rolling out statewide.

Long-term Issues and Actions

The State definitely plans to expand to TANF and food stamps, though that expansion is likely to

wait until the State converts to county control, and other welfare reform changes can be

implemented. New Jersey may also put finger imaging in its Unemployment Insurance program

to facilitate matches of employment records with welfare program participation records (i.e.,

when a person has a job and when not).
B-24

NEW YORK NORTHEAST REGION

OVERVIEW

Administering Agency The Department of Social Services (DSS)

administers the Automated Finger Imaging System

(AFIS).

Biometric Technology Finger imaging

Contractor(s) North American Morpho Systems, Inc. (Morpho)

Current Status Food Stamp, Emergency Assistance, General

Assistance, Medicaid, TANF, and Safety Net

program recipients are imaged statewide. The

programs are state-supervised and countyadministered, except Safety Net (a program unique

to New York State).

PROJECT TIMELINE

PLANNING AND IMPLEMENTATION

Impetus

Legislation was passed in 1992 establishing a two-county demonstration, which ran from

October 1992 through March 1994. Subsequent legislation expanded the demonstration to

include 12 counties of the State’s 58 total counties. When the State named the 12 counties that

were selected to participate, it also gave the remaining counties the option to join; 26 other

counties did so, bringing the total participating counties to 38.

1992 1993 1994 1995 1996 1997 1998 1999

03/96: TANF added to AFIS.

06/98: Food Stamp, Emergency Assistance, and Safety Net programs added to AFIS.

09/98: Medicaid added to AFIS.

08/95: Implementation began in rest of State.

10/92: Two-county

General Assistance

demonstration

began.

Summer '94: RFP issued.

11/94: Morpho selected as contractor.

06/95: Implementation began in 38 counties.

01/96: All counties using finger imaging.
B-25

Implementation

A Request for Proposal was issued in June 1994, the vendor was selected in November 1994, and

a contract was executed and approved in March 1995. Implementation in these 38 counties

began in June 1995 and was completed in August. The governor mandated that the system be

expanded statewide, and by January 1996 all counties were operational.

The fingerimaging project began with the State’s General Assistance program in 1995 and

expanded to include AFDC cases in March 1996. In June 1998, the project expanded to include

food stamp only cases, emergency assistance, as well as the State’s Safety Net program for legal

immigrants. By September 1998, Medicaid cases were expected to be incorporated into the

system.

Staffing

No new staff were added to support the project at the local level; utilized existing staff and

dedicated them to the project.

POLICIES AND PROCEDURES

Administering Procedures

One must be fingerprint imaged if 18 years of age or older or if less than 18 and the head of

household (minor parent). The cutoff for Medicaid is currently 21, but that age limit may come

down in the near future.

Exemption Policy

There are exemptions to imaging at county option and state approval. Exemptions exist for the

homebound and for general good cause. Because of the portable fingerprint equipment at some

locations though, few, if any, homebound exemptions have been granted. Likewise, not too

many good cause exemptions have been granted, but four unsuccessful religious exemption

lawsuits have been filed.

Investigation and Due Process

In the event of fraud, standard administrative due process includes investigation, client notice,

and administrative hearings.

PROJECT OUTCOMES AND IMPACT

Office Operations

The impact on office operations has been minimal since imaging adds only two minutes to the

in-office experience.
B-26

Clients

The impact on clients has been positive overall, as evidenced by an independent client attitudinal

survey. (Of 4,700 randomly sampled, the majority expressed comfort with the imaging.)

Caseload

The caseloads have dropped due to any number of factors in today's changing welfare

environment, including imaging, possibly. New York State has closed 46,000 cases in recent

history.

Operating Costs

The impact on the costs should be released in a cost-benefit analysis soon (second half of an

ongoing study). Benefit-cost analysis generated a 20 to 1 ratio of benefits to costs ($274 million

in savings, $13 million in expenditures).

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

In the short-term, imaging information has been shared with New Jersey already (once only so

far). After processing Connecticut’s tapes, the State will decide if information sharing will occur

quarterly or semiannually. (A monthly demographic match is already made with all contiguous

states to catch some double dippers.)

Long-term Issues and Actions

In the long-term, New York is pursuing legislation to match images against a separate database

of fugitive felons and parole violators. Presently, by law, imaging information cannot be used in

any criminal proceeding or shared with outside agencies. The State is also actively pursuing

legislation to use fingerprint images for EBT (in lieu of a PIN) for approving medical services at

the point of service. Finally, a secondary biometric for individuals with poor fingerprints, e.g.,

the elderly, is also being sought.
B-27

PENNSYLVANIA MID-ATLANTIC REGION

OVERVIEW

Administering Agency The Department of Public Welfare (DPW)

administers the Pennsylvania Automated Recipient

Identification System (PARIS).

Biometric Technology Finger imaging

Contractor(s) Not yet chosen.

Current Status Food Stamp, General Assistance, medical benefits,

and TANF program recipients will be imaged,

starting in July 1999. The programs are stateadministered.

PROJECT TIMELINE

PLANNING AND IMPLEMENTATION

Impetus

In 1994, Act 1994-49 amended the Pennsylvania Public Welfare Code by adding Section 414,

which authorized the Department of Public Welfare to create a Pennsylvania Assistance

Recipient Identification System (PARIS) in three geographic areas. The demonstration,

however, never occurred due to passage of Act 20 in 1995, which added the stipulation that the

system be implemented in areas where it is “cost effective.”

1992 1993 1994 1995 1996 1997 1998 1999

01/97: Initial RFP released.

01/99: Revised RFP to be released.

07/99 PARIS operations to begin.

1992 1993 1994 1995 1996 1997 1998 1999

01/97: Initial RFP released.

07/97: RFP canceled, thereby eliminating a legal action by PIBH.

01/99: Revised RFP to be released.

07/99 PARIS operations to begin.
B-28

Implementation

The original request for proposals was released in January 1997. However, Pennsylvania

experienced legal challenges pertaining to State Use law that have delayed implementation of

both PARIS as well as the State’s EBT system, which were envisioned as a joint operation

because of the economies such an arrangement offers. As a consequence of legal action, the

Department of Public Welfare canceled the RFP in July 1997. The EBT project was eventually

separated from the fingerimaging component and proceeded independently; EBT is now in Phase

6 of its implementation. A revised RFP is anticipated for January 1999, with implementation

expected to follow by July 1999.

PROJECT OPERATIONS

The vendor is expected to operate from a state hospital campus, while the central processing unit

will be established in a departmental computer facility, both in Harrisburg.

If a match is determined by a vendor minutiae examiner, the information will be forwarded to a

front-end investigator in the Office of the Inspector General (OIG), where the case will be

handled in accordance with existing procedures.

POLICIES AND PROCEDURES

Administering Procedures

All adults receiving benefits must comply, including emancipated minors and minor parents.

PARIS will take clients as they come in for new certification or when come in to recertify, so a

one-year rollout will be necessary to image everyone.

Exemption Policy

Food Stamp exemptions include an exemption "for religious reasons." The medical assistance

program recognizes exemptions only if the recipient is over 65. In TANF, there are no

exemptions.

Investigation and Due Process

No specific investigation or due process information available.

PROJECT OUTCOMES AND IMPACT

Office Operations

No office impact information available.
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Clients

No client impact information available.

Caseload

No caseload impact information available.

Operating Costs

No cost impact information available.

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

No short-term issues at this time.

Long-term Issues and Actions

Not interested in using biometrics at the point-of-sale.
B-30

TEXAS SOUTHWEST REGION

OVERVIEW

Administering Agency The Texas Department of Human Services (TDHS)

administers the Lone Star Imaging System (LSIS).

Biometric Technology Finger imaging

Contractor(s) North American Morpho Systems, Inc. (Morpho)

Current Status Approximately 33% of Food Stamp and TANF

program recipients are imaged. The programs are

state- administered.

PROJECT TIMELINE

POLICIES AND PROCEDURES

Administering Procedures

Household members in both programs must have a finger image code (and photo) on file or

provide a finger image at the time of application or review/recertification, if they are 18 years of

age or older on the day of the interview. In the Food Stamp program, this includes a minor who

is head of the household. For TANF, a minor parent with a dependent child on the same case

must be imaged.

Exemption Policy

Exemptions in both programs include those certified "out of the office" (e.g., physically

homebound or residing in a treatment center), those physically unable to have at least one finger

imaged, those exempted for religious reasons, and those who cannot be imaged because of

1992 1993 1994 1995 1996 1997 1998 1999

05/95: Legislation mandated a pilot project

10/96: 10-office pilot began.

08/97: 10 office pilot ended.

Fall '99: Statewide rollout to be complete.
B-31

equipment failure. The Food Stamp program also exempts ineligible students and boarders for

whom the household is not receiving benefits. TANF's special exemptees include SSI recipients

and non-parental payees.

Investigation and Due Process

In the event of fraud, standard administrative due process includes investigation by DHS's Office

of the Inspector General, client notice, and administrative hearings.

PROJECT OUTCOMES AND IMPACT

Office Operations

No office impact information available.

Clients

As in the other eight States, Texas clients overwhelmingly favored the use of finger imaging to

reduce fraud in their assistance programs.

Caseload

A 1997 evaluation by the University of Texas could not find any significant reduction in

caseload due to finger imaging.

Operating Costs

Additionally, the UT study could not identify any savings in benefit payments attributable to

deterring duplicate benefits through finger imaging.

FUTURE ISSUES AND DIRECTIONS

Anticipated Short-term Actions

A pilot integrating finger imaging and EBT cards will be launched in the near future.

Long-term Issues and Actions

Texas has no long-term issues at this time.
B-32
C-1

APPENDIX C. REPORT OF CLIENT ADVOCATE INTERVIEWS

Introduction

The 74th Texas Legislature directed the use of finger imaging to help detect and deter

duplicate participation in the Food Stamp and Temporary Assistance to Needy Families (TANF)

programs in Texas. On October 24, 1996, the Texas Department of Human Services (DHS)

implemented the Lone Star Image System (LSIS) pilot project. The pilot project involved ten

DHS offices in 2 of 254 counties in Texas—Bexar and Guadalupe counties. All adults and minor

heads of household receiving food stamp benefits in the pilot counties were required to be finger

imaged (Texas Department of Human Services, 1997).

This report includes the results of client advocate interviews conducted--as part of an

evaluation of the food stamp portion of the LSIS project--by R. Lewis and Company for the Food

and Nutrition Services (FNS) of the U.S. Department of Agriculture. There is a brief overview of

the Texas DHS evaluation of the LSIS pilot project. We compare results from the client advocate

interviews and the DHS client and community leader surveys. In addition, we present some

recommendations based on the client advocate interviews.

Background: DHS Process Evaluation

The Texas DHS conducted a process evaluation of the first three months of the LSIS pilot

project (October 24, 1996 through January 23, 1997; Texas Department of Human Services,

1997). The evaluation included surveys and interviews of staff, clients, and community leaders.

DHS Community Leader Survey. DHS sent a three-question survey to 104 community

leaders in Bexar and Guadalupe counties on January 2, 1997 to collect community opinions about

the LSIS pilot program. Community leaders included “state legislators, city council members, and

[directors of] non-governmental, community-based agencies that serve public assistance clients

(including neighborhood centers and religious and non-sectarian social services)” (p. E-1, Texas

Department of Human Services, 1997). Forty-two surveys were returned by February 1, 1997.

The three questions asked by DHS were:

1. How would you compare the response you have received since finger imaging started

to the response you receive on other issues?

2. Overall, how have these people viewed finger imaging?

3. Do you think finger imaging will help keep people from getting benefits they should

not receive?

LSIS Client Interviews. DHS conducted client interviews with 49 food stamp and

TANF recipients and applicants. Approximately five interviews at each of the ten DHS sites were

conducted. Interviews were conducted from November 25, 1996 through January 6, 1997.

Interviewers asked five questions:
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1. Did you receive this letter [Form 1089, finger image notification letter] in the mail?

2. Did you hear about finger imaging any other way?

3. Do you think finger imaging is a good idea, bad idea, or neither good nor bad idea?

4. Do you think finger imaging will keep people from getting benefits they should not

get?

5. Is there anything else you would like to say about finger imaging?

LSIS Client Satisfaction Cards. DHS distributed 2,600 client satisfaction cards in the

DHS offices participating in the LSIS pilot program. Cards were distributed between January 9,

1997 and February 10, 1997. Cards were returned in special reply boxes in each office; 2,378

cards were completed. Clients were asked two questions:

1. What do you think about finger imaging?

2. Do you think finger imaging will help people be more honest when applying for

benefits?

Method

We conducted an evaluation of the food stamp portion of the Texas LSIS program for the

FNS. As part of the evaluation, we interviewed client advocates of food stamp recipients and

applicants in Texas. Nine client advocates from San Antonio (n=7) and Austin (n=2), Texas were

interviewed by phone, using a 20-question interview protocol (Appendix D). We conducted the

interviews from October 17 to October 28, 1997, approximately one year after the LSIS pilot

project began. Finger imaging was still in effect in Bexar and Guadalupe counties at the time of

data collection. The client advocate interviews emphasized advocate and client concerns about

finger imaging and the LSIS pilot program.

The Texas DHS provided us with their LSIS community leaders mailing list of 104

government and non-government leaders. We asked DHS to identify 9 non-government leaders

for interviews. Seven of the nine community leaders we interviewed were from that list. We

added the name of a community leader who was an outspoken critic of the finger-imaging

requirement. He provided two additional names for potential interviews. We interviewed one of

those persons. Although we did not ask participants if they had previously completed a survey

about the LSIS pilot project, one respondent noted that she had completed a survey received in

the mail.

Client Advocate Interview Results

Results of the nine client advocate interviews are reported in this section. Reflecting the

emphasis of the interview questions, the results identify advocate and client concerns with finger

imaging. In addition, responses indicated that there are some misunderstandings about the use of

finger imaging in the Food Stamp program.
C-3

Misunderstanding the LSIS pilot project. Five of the nine leaders had some

misunderstanding of the finger-imaging requirement. Several of those interviewed thought the

program required a finger image at the point-of-sale. They believed that the finger-imaging

requirement would prevent people from using another person’s lone star card or from stealing

lone star cards. One participant indicated that his clients wonder if only the head of the household

will be able to use the food stamp card. Some of the leaders had heard very little of the program.

One person said that he had heard that people were required to give a “thumbprint image.”

Another participant suggested a need for positive public announcements about the finger-imaging

requirement; “they have not publicized [the program] enough....I hope to hear more about it.”

Some did not realize that the finger-imaging pilot project had begun. Results of the interviews

should be interpreted with the knowledge that misconceptions and misunderstandings of the

nature of the food stamp finger-imaging requirement may influence some answers.

Client advocates’ open-ended comments on LSIS. Following introductions, we asked

client advocates to tell us what they had heard about finger imaging in Texas. The responses

were open-ended and unprompted. Comments were categorized as positive, negative, neutral,

and misunderstandings about finger imaging in the Food Stamp program.

As is often the case in interviews or surveys, individuals with negative comments were

more vocal than individuals with positive comments. Thus, there were fewer positive comments

than negative responses. Two positive issues were cited--prevention of fraud and saving taxpayer

dollars. A variety of negative issues associated with finger imaging were reported, including:

finger imaging is seen as a degrading or demeaning process, finger imaging is identified with

criminal activity, the cost and inconvenience of finger imaging outweigh catching fraudulent

applicants, the LSIS pilot project has resulted in false matches and uncovered few cases of fraud,

some applicants have religious objections to being imaged, and clients are mad and upset. Some

comments were neutral, including haven’t heard much about the finger-imaging program, saw a

program on television, and the media tries to portray finger imaging objectively.

Client advocates had heard and reported a variety of concerns and issues about finger

imaging and the food stamp finger-imaging pilot project. We followed the open-ended,

unprompted questions with a series of prompted questions to identify specific concerns associated

with finger imaging.

Is Finger Imaging in the Food Stamp Program a Good or Bad Idea? Five of the

leaders thought finger imaging in the Food Stamp program was a bad idea and focused on

negative aspects of finger imaging. One of these respondents noted that finger imaging, per se, is

not a bad idea. He believed that there are appropriate applications for the use of biometrics, such

as law enforcement. However, he deemed the use of finger imaging in a food and nutrition

program as inappropriate. The other four interviewees thought finger imaging was a good idea

and generally focused on its use in the prevention of fraud and consequent saving of money in the

Food Stamp program.

Concerns About Finger Imaging. We asked all participants if they had heard any of 14

different concerns about finger imaging from any source (e.g., clients, colleagues, and media).

Two had not heard any concerns. The others had heard from 1 to 12 different concerns. The
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most cited objections about finger imaging included the unjust treatment of poor people and their

invasion of privacy. The inconvenience of making extra trips to the food stamp office, the

association of finger imaging with criminality, and fears of information sharing with the INS were

also at the top of the list. Other concerns added to the list included the cost of the finger-imaging

program, a degrading process, and religious objections to imaging. Table 1 shows the number of

interviews, out of nine, in which community leaders had heard each of the objections or concerns.

Table 1. Number of Community Leaders Who Heard Specific Concerns About Finger

Imaging

Unjust treatment of poor people 6

Invasion of privacy 6

Inconvenience of extra trips to the Food stamp Office 6

Fears of the Immigration and Naturalization Service (INS) 5

Discomfort about associations with criminality 5

Inconvenience of appearing in food stamp office 5

Cost of extra trips to the food stamp office 4

Unnecessary withholding of benefits 4

Fears of interagency sharing 3

Cost of appearing in food stamp office 3

Potential embarrassment in front of family members 2

Potential embarrassment in front of friends/neighbors 2

Time required at application 1

Time required at recertification 1

Other: Cost of finger-imaging program 1

Other: Degrading process 1

Other: Religious objection 1

We also asked respondents if they had heard the same list of concerns from their clients.

More than half (five) had not heard concerns from their clients. The four who had heard client

objections, noted concerns about unjust treatment of poor people and assumption of criminal

behavior among poor people. Other concerns on the minds of clients include fears of information

sharing with the INS and other agencies and embarrassment of providing a finger image. Table 2

shows how many leaders indicated hearing specific concerns from their clients.

Respondents elaborated on some of the concerns that they or their clients had about finger

imaging in general and finger imaging used in the Food Stamp program. One of the community

advocates voiced a recurring concern, that finger imaging makes a person feel like a criminal and

presumes that the person is a criminal. One comment was actually a series of questions, “Is there

fraud [in the Food Stamp program]?” If so, “How is it being perpetrated?” and “Is finger imaging

the way to detect or deter [the fraud]?” A common thread among those who were against the

food stamp finger-imaging requirement was the belief that there was little fraud in the Food Stamp

program. Following this line of thought, was a concern about the cost of the finger- imaging
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Table 2. Number of Community Leaders Who Heard Specific Concerns About Finger

Imaging from Clients

Discomfort about associations with criminality 4

Unjust treatment of poor people 4

Fears of the Immigration and Naturalization Service (INS) 3

Fears of interagency sharing 3

Cost of extra trips to the food stamp office 3

Potential embarrassment in front of family members 3

Potential embarrassment in front of friends/neighbors 3

Invasion of privacy 2

Cost of appearing in food stamp office 2

Inconvenience of appearing in food stamp office 2

Inconvenience of extra trips to the food stamp office 2

Unnecessary withholding of benefits 2

Time required at recertification 1

Other: Cost of the finger-imaging program 1

Other: Religious objection 1

Time required at application 0

Other: Degrading process 0

program and the belief that the money could be spent for other programs, such as outreach or job

training. One respondent indicated that the finger-imaging program was costing a lot of money to

implement, but it wasn’t finding duplicate applicants. Further, he believed that the benefits

offinger imaging were not worth the cost, since finger imaging conveys an attitude of distrust and

slows down the production of the food stamp office. Another participant had similar comments,

saying that the cost of establishing and running the finger-imaging program and the inconvenience

to the food stamp recipients and applicants outweigh the catching of fraudulent applicants.

A community leader indicated that unjust treatment of poor people has always been an

issue, and the finger-imaging program is no different than the general treatment of people in this

population. Some immigrants, even legal aliens, are concerned that their finger image could be

shared with authorities in their native country or that their legal status in the United States might

be affected if they refuse to have their finger image taken at the food stamp office.

Favorable Comments About Finger Imaging. The majority of the questions asked

during the interview addressed concerns and negative issues about finger imaging. However, we

did ask individuals if they had heard favorable things about finger imaging, what they had heard,

and if they thought finger imaging was a good or bad idea. We received far more negative

comments and concerns than positive comments about the food stamp finger-imaging program.

One respondent praised finger imaging and any other programs that can reduce illegal use of

benefits and save taxpayer money. Another praised the program, saying that it “should have been

done a long time ago.” And another said that with the finger-imaging requirement she wouldn’t
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see food stamp recipients driving Cadillacs anymore. A number of individuals said that they had

heard, from public officials and the media, that finger imaging is supposed to prevent fraud.

We asked the client advocates if they had heard favorable things about the finger-imaging

process in the state and what were some of those things. We used an unprompted check list,

including finger imaging will keep food stamps going to the right people, finger imaging will

prevent cheating, finger imaging will prevent double-dipping, finger imaging will keep people

honest, finger imaging will prevent fraud, finger imaging is no big deal, and other. We counted all

favorable comments mentioned in each interview. The results are displayed in Table 3.

Table 3. Number of Community Leaders who Heard Favorable Comments about Finger

Imaging

Total Favorable comments 9

 Keep food stamps going to the right people 0

 Prevent cheating 1

 Prevent double-dipping 1

 Keep people honest 0

 Prevent fraud 5

 Finger imaging is just no big deal 0

 Other: Prevent people from using another’s card 2

We found that seven of nine respondents said that they thought finger imaging would keep

people from getting food stamps on more than one case. Nobody knew any clients who would

not apply for food stamps because of the finger-imaging requirement. One client advocate said

that he had heard of people, but not clients, who would not apply for food stamps if they had to

give their finger image. One commented that only those who have something to hide wouldn’t

apply for food stamps.

Comparison of Client Advocate Interview Results to DHS Survey Results.

Comparisons of the client advocate interview results and the DHS community leader

survey, client interviews, and client comment cards are presented in this section. The client

advocate interviews were conducted approximately nine months after the DHS surveys and

interviews. Questions asked and response options provided were not identical, but in many cases

were comparable.

Community Leaders. Only three months after finger imaging began, it might be

expected that some community leaders had not yet heard about the finger-imaging requirement.

Comments from three DHS survey respondents revealed several individuals who had not heard of

the program. One respondent said, “We are not aware of anything having to do with finger

imaging” and another said “I have not heard anything about it.”

Each of the client advocates interviewed one year after the LSIS pilot project began had

heard something about finger imaging and the Food Stamp program. However, we heard a
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number of misconceptions about how the program worked (e.g., a point-of-sale program) and

individuals who did not think that the finger-imaging program had started.

Of the 41 respondents to the DHS community leader survey, more than half (n=25) had

not heard anything from their clients or constituents about the finger-imaging requirement and five

had not heard any opinions about finger imaging from their clients. Of those who had heard

opinions from their clients or constituents (n=11), five had heard positive comments about the

program and three had heard negative comments. Three had heard neither good nor bad

comments. In the client advocate interviews, seven of the nine participants had heard concerns

about finger imaging from any source, including media reports. However, only four of the client

advocates had heard concerns or negative comments about finger imaging from their clients.

Of the 41 DHS respondents, 27 believed that finger imaging would keep people from

getting benefits they should not receive. Only two respondents believed that finger imaging

would not prevent people from getting benefits they should not receive. Twelve respondents said,

“I don’t know” in response to the question. In the client advocate interviews, we asked a slightly

different question--”Do you think finger imaging will keep people from getting food stamp

benefits on more than one case?” Seven of nine client advocates thought that finger imaging

would keep people from getting benefits on two or more cases.

The DHS community leader survey results from three months after the start of the LSIS

pilot project are similar to our client advocate interview results from one year after the

implementation of finger imaging. Clients and constituents had mostly positive opinions about

finger imaging and most community leaders believed that finger imaging could prevent the

issuance of duplicate food stamp benefits.

Clients. Our evaluation did not include client interviews. However, in the client advocate

interviews we asked the advocates to provide information about client concerns. Four of the nine

client advocates had heard negative comments about finger imaging from clients. Further, as

might be expected, the clients had fewer concerns than the client advocates did. In the DHS client

interviews, clients were positive about finger imaging. All but two clients believed that finger

imaging was a good idea. Most clients (33 of 47) believed that finger imaging would reduce

fraud.

Consistent with the DHS client interview results, the DHS client comment cards indicate

that most clients are positive about finger imaging. Most think finger imaging is a good idea

(90%) and will help people be more honest when applying for benefits (88%). Similarly, 88% of

clients in the Connecticut Digital Imaging system (for TANF) felt they had not been

inconvenienced and 87% thought that finger imaging would help prevent cheating (Connecticut

Department of Social Services, 1996).

Client responses were overwhelmingly positive. In the client advocate interviews, we did

not measure client opinion directly. However, five of the nine advocates reported no client

concerns with finger imaging. And, although client advocates voiced numerous concerns with

finger imaging, most thought that it was a good idea. Our interview results are consistent with

the DHS client interview and comment card results.
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Summary

Client Advocate and Client Concerns: Differences. Results of the client advocate

interviews show that there are differences in the level of concern of clients and client advocates.

In the role of advocates, community leaders focus on the potential problems and disadvantages

versus the benefits of finger imaging to a greater extent than clients do. In the client advocate

interviews, seven of the nine advocates had heard some concerns about finger imaging from either

clients or other sources such as colleagues or the media. Only four of the nine advocates had

clients with concerns about finger imaging in the Food Stamp program.

Misunderstandings of the LSIS Pilot Project. Even one year after the LSIS pilot

project had been in place, some client advocates had not heard much about the project. Along

with the limited knowledge that some individuals had about the project were misconceptions

about the nature of the finger-imaging requirement. Four of nine client advocates thought that

finger imaging was used at the point-of-sale. Two advocates didn’t realize that finger imaging

had begun.

Concerns About Finger Imaging. The types of concerns most frequently voiced by

clients and their advocates fall into three categories: unjust treatment of poor people, cost and

inconvenience of being finger imaged, and fears of interagency sharing, especially with the INS.

Some clients associate finger imaging with criminality and clients may be embarrassed about

giving their finger image. The finger-imaging requirement is considered degrading and as unjust

treatment of poor people.

For the program to work, all adult members of a household are required to be finger

imaged. The cost and inconvenience of going to the food stamp office is a concern for some who

must make child care arrangements or pay for transportation to the office or take time off from

work. With finger imaging, more individuals must make trips to the food stamp office, increasing

the cost or inconvenience to household members. Further, delays in getting all members of a

household imaged may result in delays in receiving benefits.

Some clients expressed concerns about sharing information with other agencies, especially

the INS. These fears stem from a lack of information about the INS process, leading to

uncertainty about the status of immigration cases, according to client advocates.

Recommendations. In the client advocate interviews, we asked how could the fingerimaging program be improved or promoted to provide better service to clients.

Recommendations included public relations and increased access to finger-imaging units for

clients. Given the misunderstandings about the finger-imaging requirement, it might be useful to

develop a public relations campaign addressed to community leaders and provide a fact sheet of

information to educate and inform community leaders about the LSIS pilot project. The

campaign should clarify the use of finger imaging at application and not at the point-of-sale. With

the facts readily available, client advocates can correctly address client concerns without

perpetuating some of the misunderstandings that currently exist. Another recommendation

addresses the cost and inconvenience of trips to the food stamp office. An advocate suggested
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providing mobile finger- imaging units that can be used in the community centers and other

locations throughout the community to increase access for household members.

References

Connecticut Department of Social Services. (1996). Connecticut survey of clients who have just

been digitally imaged for AFDC [On-line]. Available: http://www.dss.state.ct.us/faq/

disurvey.htm.

Texas Department of Human Services. (1997). Evaluation of the Lone Star Image System.
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APPENDIX D. CLIENT ADVOCATE INTERVIEW PROTOCOL

Introduction

Hello, my name is ________________ and I am from R. Lewis & Co. Inc., a research

company in Alexandria, Virginia. We are conducting a study of Finger Imaging for the

United States Department of Agriculture’s Food Stamp Program.

As part of that study, we are talking to community leaders about the new finger-imaging

requirements and their clients’ feelings about the changes.

We received your name from the Texas Department of Human Services. DHS let us

know that you represent the community affected by the new regulations.

This interview will take about 15 minutes. If you agree to participate, we can guarantee

that your name will not be connected with your answers, and your responses will not

affect your clients in any way. You don’t have to answer any questions you don’t want to

answer.

Do you have any questions about our study?

May I ask you the questions now? I’ll be taking notes as you answer the questions.

1. For our records, can you describe for me in general terms, your link to people

who receive food stamps?

2. Can you tell us in your own words, but as specifically as possible, what you

hear about finger imaging in the state?
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3. Would you say that finger imaging is an important issue or one that is not so

important?

q Important

q Not so important

q Other (please specify): _____________________________________________

4. Others in Texas and the nation at large have raised some concerns about

finger imaging. Have you personally heard any objections regarding: [Mark

“Y” for yes; “N” for no.]

q Fears of the Immigration and Naturalization Service (INS )

q Fears of interagency information sharing (e.g. identification of outstanding traffic

violations)

q Discomfort about associations with criminality

q Unjust treatment of poor people

q Invasion of privacy

q Cost of appearing in food stamp office

q Cost of extra trips to the Food stamp Office

q Inconvenience of appearing in food stamp office

q Inconvenience of extra trips to the Food stamp Office

q Time required at application

q Time required at recertification

q Unnecessary withholding of benefits

q Potential embarrassment in front of family members

q Potential embarrassment in front of friends/neighbors

q Other
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5. Have you heard those concerns from your own clients?

q Yes

q No

6. Which concerns have your clients addressed?

q Fears of the Immigration and Naturalization Service (INS )

q Fears of interagency information sharing (i.e. identification of outstanding traffic

violations)

q Discomfort about associations with criminality

q Unjust treatment of poor people

q Invasion of privacy

q Cost of appearing in food stamp office

q Cost of extra trips to the Food stamp Office

q Inconvenience of appearing in food stamp office

q Inconvenience of extra trips to the Food stamp Office

q Time required at application

q Time required at recertification

q Unnecessary withholding of benefits

q Potential embarrassment in front of family members

q Potential embarrassment in front of friends/neighbors

q Other 
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7. About how many of your clients specifically raised those issues with you?

(Mark estimates)

___ Fears of the Immigration and Naturalization Service (INS)

___ Fears of interagency information sharing (i.e. identification of outstanding traffic

violations)

___ Discomfort about associations with criminality

___ Unjust treatment of poor people

___ Invasion of privacy

___ Cost of appearing in food stamp office

___ Cost of extra trips to the food stamp office

___ Inconvenience of appearing in food stamp office

___ Inconvenience of extra trips to the Food stamp Office

___ Time required at application

___ Time required at recertification

___ Unnecessary withholding of benefits

___ Potential embarrassment in front of family members

___ Potential embarrassment in front of friends/neighbors

___ Other 

8. Can you clarify for us what your clients specifically said about that issue

(those issues)?
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9. So we can be even more clear about your client concerns, can you explain for

us how their concern (concerns) would materialize?

[Continue writing on back, if necessary)

10. Have you also heard favorable things about the finger imaging process in the

state?

q Yes

q No

11. What were some of those things?

q Finger imaging will keep food stamps going to the right people

q Finger imaging will prevent cheating

q Finger imaging will prevent double-dipping

q Finger imaging will keep people honest

q Finger imaging will prevent fraud

q Finger imaging is just no big deal

q Other
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12. Do you have a personal feeling about finger imaging?

q Yes

q No

q Don’t Know

13. Do you think finger imaging is a:

q Good idea?

q Bad idea?

q Neither good nor bad idea?

14. Why?

15. Do you think finger imaging will keep people from getting food stamp

benefits on more than one case?

q Yes

q No

q Don’t Know

16. Could you please tell me a little about why you feel that way?
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17. Do you personally know of clients who would not apply for food stamp

benefits because of the finger-imaging requirement?

q Yes

q No

18. Can you tell me anything about why they would not apply?

19. How do you think the finger-imaging program can be improved or promoted

to provide clients with better service?

20. Is there anything else you would like to say about finger imaging?