1

Department of the Treasury

2015 Annual Privacy and Data Mining Report
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Message from the Deputy Assistant Secretary for Privacy, 

Transparency, and Records

On behalf of the Department of the Treasury Senior Agency Official 

for Privacy and Chief Privacy and Civil Liberties Officer, I am 

pleased to present Treasury’s Annual Privacy and Data Mining 

Reports for Fiscal Year 2015, as required by Section 522 of the 

Consolidated Appropriations Act of 2005 and the Federal Agency 

Data Mining Reporting Act of 2007. For the third year in a row, 

Treasury is combining these two separate reporting requirements into 

a single report. 

Inquiries about this report may be directed to privacy@treasury.gov. 

This report, as well as previous annual reports, can be found on the 

Department’s Privacy Act website at: 

www.treasury.gov/privacy/annual-reports.

Helen Goff Foster

Deputy Assistant Secretary 

for Privacy, Transparency, and Records

U.S. Department of the Treasury
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2015 Annual Privacy and Data Mining Reports

TABLE OF CONTENTS

Table of Contents.......................................................................................................................... 3

Statutory Requirements ............................................................................................................... 5

Section One:

Department of the Treasury 2015 Annual Privacy Report....................................................... 7

Background ................................................................................................................................... 7

The Role of the Treasury Chief Privacy and Civil Liberties Officer.......................................... 7

The Role of the Office of Privacy, Transparency, and Records (OPTR).................................... 9

Oversight and Compliance........................................................................................................... 9

System of Records Notices (SORN)........................................................................................... 9

Privacy Impact Assessments..................................................................................................... 11

Federal Information Security Management Act of 2002 .......................................................... 11

Section 803 of the Implementing Recommendations of the 9/11 Commission Act of 2007.... 11

PII Holdings and Reduction....................................................................................................... 12

Elimination of the Unnecessary Use of Social Security Numbers .......................................... 12

Internal Revenue Service (IRS)................................................................................................. 12

The Alcohol and Tobacco Tax and Trade Bureau (TTB) ......................................................... 12

Privacy Awareness and Training .............................................................................................. 13

A Culture of Privacy Awareness............................................................................................... 13

Internal Revenue Service (IRS) Privacy Training..................................................................... 13

IRS Advancements in Privacy Policy ....................................................................................... 13

Leadership and Coordination within Treasury ....................................................................... 14

Treasury Directive 25-06, The Treasury Data Integrity Board................................................. 14

Treasury Directive 81-08: Certification Process for the Use of Web Measurement and 

Customization Technologies on Treasury Websites................................................................. 14

Executive Order (E.O.) 13636: Improving Critical Infrastructure Cybersecurity .................... 14
4

Treasury’s Privacy Website ...................................................................................................... 15

U.S.-EU Data Privacy and Protection in Law Enforcement, Criminal Justice, and Public 

Security Matters...........................................................................................15

Treasury Computer Matching Programs................................................................................. 15

Section Two:

Department of the Treasury 2015 Data Mining Report.......................................................... 16

Background ................................................................................................................................. 16

Definitions.................................................................................................................................... 16

FinCEN Data Mining Activities................................................................................................. 17

IRS Data Mining Activities........................................................................................................ 26

TTB Data Mining Activities....................................................................................................... 33

Conclusion....................................................................................................................................38
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STATUTORY REQUIREMENTS

In this report, Treasury consolidates the following two reporting requirements to reduce 

duplication and to provide Congress and the public with a more comprehensive overview of 

Treasury’s privacy compliance and oversight activities: 

(1) The annual privacy report required by Section 522(a) of the Consolidated 

Appropriations Act of 2005; and,

(2) The Data Mining Reporting Act requirement contained in the Section 803 of the 

Implementing Recommendations of the 9/11 Commission Act of 2007, 42 U.S.C. § 

2000ee–3.

THE REPORTING PERIOD

This report covers Treasury activities within the 2015 fiscal year (the reporting period).

THE ANNUAL PRIVACY REPORT

The Annual Privacy Report has been prepared in accordance with Section 522(a) of the 

Consolidated Appropriations Act of 2005, which includes the following requirement:

Privacy Officer—

Each agency shall have a Chief Privacy Officer to assume primary responsibility for 

privacy and data protection policy, including—

* * *

(6) preparing a report to Congress on an annual basis on activities of the 

Department that affect privacy, including complaints of privacy 

violations, implementation of section 552a of title 5, 11 United 

States Code, internal controls, and other relevant matters;

* * *

THE DATA MINING REPORT

The Federal Agency Data Mining Reporting Act of 2007, 42 U.S.C. § 2000ee-3, includes the 

following requirement:

(c) Reports on data mining activities by Federal agencies

(1) Requirement for report - The head of each department or agency of the Federal 

Government that is engaged in any activity to use or develop data mining shall submit 

a report to Congress on all such activities of the department or agency under the 

jurisdiction of that official. The report shall be produced in coordination with the 

privacy officer of that department or agency, if applicable, and shall be made 

available to the public, except for an annex described in subparagraph (3).

(2) Content of report - Each report submitted under subparagraph (A) shall include, for 

each activity to use or develop data mining, the following information:

(A) A thorough description of the data mining activity, its goals, and, where 

appropriate, the target dates for the deployment of the data mining activity.
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(B) A thorough description of the data mining technology that is being used or 

will be used, including the basis for determining whether a particular pattern 

or anomaly is indicative of terrorist or criminal activity.

(C) A thorough description of the data sources that are or will be used.

(D) An assessment of the efficacy or likely efficacy of the data mining activity in

providing accurate information consistent with and valuable to the stated goals 

and plans for the use or development of the data mining activity.

(E) An assessment of the impact or likely impact of the implementation of the 

data mining activity on the privacy and civil liberties of individuals, including 

a thorough description of the actions that are being taken or will be taken with 

regard to the property, privacy, or other rights or privileges of any individual 

or individuals as a result of the implementation of the data mining activity.

(F) A list and analysis of the laws and regulations that govern the information 

being or to be collected, reviewed, gathered, analyzed, or used in conjunction 

with the data mining activity, to the extent applicable in the context of the data 

mining activity.

(G) A thorough discussion of the policies, procedures, and guidelines that are in 

place or that are to be developed and applied in the use of such data mining 

activity in order to—

(i) protect the privacy and due process rights of individuals, such as

redress procedures; and

(ii) ensure that only accurate and complete information is collected, 

reviewed, gathered, analyzed, or used, and guard against any harmful 

consequences of potential inaccuracies.
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SECTION ONE:

DEPARTMENT OF THE TREASURY 2015 ANNUAL PRIVACY REPORT

BACKGROUND

The Role of the Treasury Chief Privacy and Civil Liberties Officer 

Section 522 of the Consolidated Appropriations Act of 20051requires the Department of the 

Treasury (Treasury or Department) to appoint a Chief Privacy Officer to assume primary 

responsibility for privacy and data protection policy. Similarly, Section 803 of the Implementing 

Recommendations of the 9/11 Commission Act of 20072requires the Department to appoint a 

senior officer to serve as its Privacy and Civil Liberties Officer. In addition, Office of 

Management and Budget (OMB) Memorandum 05-08, Designation of Senior Agency Officials 

for Privacy, February 11, 2005 (OMB M-05-08), directs agency heads to designate a Senior 

Agency Official for Privacy (SAOP) with agency-wide responsibility for ensuring 

implementation of information privacy protections and full compliance with information privacy 

laws, regulations, and policies.

Consistent with these requirements, Treasury Directive 25-09, Privacy and Civil Liberties 

Activities Pursuant to Section 803 of the Implementing Recommendations of the 9/11 

Commission Act of 2007 (TD 25-09), assigns all of these responsibilities to the Treasury Chief 

Privacy and Civil Liberties Officer (CPCLO). TD 25-09 designates the Assistant Secretary for 

Management (ASM) as the Department’s CPCLO.3 

In his role as Treasury’s CPCLO, the ASM is responsible for:

 assuring that the use of technologies sustain, and do not erode, privacy protections 

relating to the use, collection, and disclosure of information in identifiable form;4

 assuring that technologies used to collect, use, store, and disclose information in 

identifiable form allow for continuous auditing of compliance with stated privacy policies 

and practices governing the collection, use and distribution of information in the 

operation of the program;5

 assuring that personal information contained in Privacy Act systems of records is handled 

in full compliance with fair information practices as defined in the Privacy Act of 1974; 6

 evaluating legislative and regulatory proposals involving collection, use, and disclosure 

of personal information by the federal government;7

 conducting a privacy impact assessment of proposed rules of the Department on the 

privacy of information in an identifiable form, including the type of personally 

identifiable information (PII) collected and the number of people affected;8

 

1

Pub. L. No. 108-447, Section 522(a)(1).

2

Pub. L. No. 110-53, § 803(a)(1).

3

TD 25-09 (and all TDs and TOs) are available at http://www.treasury.gov/about/role-of-treasury/orders-directives/.

4 Consolidated Appropriations Act of 2005, Pub. L. No. 108-447, Section 522(a)(1).

5

Id. at Section 522(a)(2).

6

Id. at Section 522(a)(3).

7

Id. at Section 522(a)(4).

8

Id. at 522(a)(5).
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 preparing a report to Congress on an annual basis on activities of the Department that 

affect privacy, including complaints of privacy violations, implementation of section 

552a of title 5, 11 United States Code, internal controls, and other relevant matters;9

 ensuring that the Department protects information in an identifiable form and information 

systems from unauthorized access, use, disclosure, disruption, modification, or 

destruction;10

 training and educating employees on privacy and data protection policies to promote 

awareness of and compliance with established privacy and data protection policies;11

 ensuring compliance with the Department’s established privacy and data protection 

policies;12

 assisting the head the Department and other officials of such department, agency, or 

element in appropriately considering privacy and civil liberties concerns when such 

officials are proposing, developing, or implementing laws, regulations, policies, 

procedures, or guidelines related to efforts to protect the Nation against terrorism;13

 periodically investigating and reviewing department, agency, or element actions, policies, 

procedures, guidelines, and related laws and their implementation to ensure that such 

department, agency, or element is adequately considering privacy and civil liberties in its 

actions;14

 ensuring the Department has adequate procedures to receive, investigate, respond to, and

redress complaints from individuals who allege the Department has violated their privacy 

or civil liberties;15

 considering certain factors when providing advice on Department proposals to retain or 

enhance a particular governmental power, including whether the proponent has 

established16

a. that the need for the power is balanced with the need to protect privacy and civil 

liberties;

b. that there is adequate supervision of the use by such department, agency, or 

element of the power to ensure protection of privacy and civil liberties; and

c. that there are adequate guidelines and oversight to properly confine its use.

 reviewing and updating privacy procedures;17

 ensuring implementation of information privacy protections, including compliance with 

applicable information privacy laws, regulations, and policies;18

 ensuring employees and contractors receive privacy training;19

 having a role in Treasury’s development and evaluation of legislative, regulatory, and 

other policy proposals that implicate information privacy issues.20

 

9

Id. at 522(a)(6).

10 Id. at § 522(a)(7).

11 Id. at § 522(a)(8).

12 Id. at § 522(a)(9).

13 Implementing Recommendations of the 9/11 Commission Act of 2007, Pub. L. No. 110-53, § 803(a)(1).

14 Id. at § 803(a)(2).

15 Id. at § 803(a)(3).

16 Id. at § 803(a)(4).

17 OMB M-05-08, Designation of Senior Agency Officials for Privacy, February 11, 2005.

18 Id.

19 Id.

20 Id.
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The Role of the Office of Privacy, Transparency, and Records (OPTR)

Treasury Directive 25-04, The Privacy Act of 1974, As Amended, January 27, 2014 (TD 25-04), 

designates the Deputy Assistant Secretary for Privacy, Transparency, and Records (DASPTR) as 

the ASM’s principal advisor on issues related to privacy and civil liberties. The DASPTR 

ensures Treasury collects, maintains, and discloses PII in a manner consistent with legal and 

policy requirements. The DASPTR leads OPTR and provides the ASM with day-to-day support 

in executing the privacy and civil liberties duties entrusted to her in her capacity as the 

Department’s CPCLO. 

OPTR supports Treasury’s mission through three core functions:

 Safeguarding the privacy and civil liberties of individuals when Treasury collects, 

maintains, and discloses personal information;

 Providing transparency and accountability to the public with respect to Treasury 

policies, activities, and functions; and,

 Preserving and providing access to Treasury’s institutional knowledge, records, and 

information resources. 

OPTR is responsible for monitoring and overseeing privacy and civil liberties compliance 

throughout the Department. This includes working closely with Treasury leadership and 

Treasury bureaus to develop, implement, and monitor agency-wide privacy policies and 

procedures in compliance with the U.S. Constitution and applicable federal statutes, Executive 

Orders, OMB memoranda and guidance, as well as other relevant policy, standards, and 

regulations. Some of OPTR’s operations include: 

 Ensuring consistent application of privacy and civil liberties safeguards in all Treasury 

activities through Treasury-wide policy and oversight;

 Reviewing and publishing system of records notices;

 Conducting and reviewing Privacy Impact/Threshold Assessments;

 Analyzing and reporting on paper and electronic incidents involving PII; and,

 Developing and conducting privacy and civil liberties training.

OVERSIGHT AND COMPLIANCE

For Treasury to accomplish its mission, it must collect PII from its employees and the public, as 

well as acquire it from various organizations and other government agencies. The Department is 

responsible for managing and protecting the information it collects, maintains, and discloses. 

Federal law, regulations, and policies regulate these activities and are designed to maintain the 

public’s trust. 

System of Records Notices (SORN)

A system of records is a grouping of paper or electronic records maintained by a federal agency 

from which information about an individual is retrieved by the name of the individual or another 

unique identifier assigned to the individual (e.g., Social Security number). Pursuant to 5 U.S.C. 

§ 552a (e)(4), agencies are required to publish a SORN in the Federal Register for each system 

of records. Treasury has published regulations describing how it collects, maintains, and 
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discloses records about individuals that are maintained in a system of records. These regulations 

provide procedures by which individuals may request access to their information maintained by 

Treasury.21 

During FY 2015, the Department published four new SORNs in the Federal Register: 

 Bureau of Engraving and Printing.050, Use of Shredded U.S. Currency System, March 

17, 2015 (80 FR 13955);

 Treasury .017, Correspondence and Contact Information, June 18, 2015 (80 FR 34963);

 Office of the Comptroller of the Currency.800, Office of Inspector General Investigations 

System, July 06, 2015 (80 FR 31095); and,

 United States Mint.014, Denver Public Tour and Outreach Reservation System, October 

27, 2015 (80 FR 65870). 

In FY 2015, Treasury also published 89 reissued and renewed SORNs in the Federal Register:

 Treasury.015, General Information Technology Access Account Records, January 14, 

2015 (80 FR 1988);

 The Alcohol and Tobacco Tax and Trade Bureau, TTB .001, Regulatory Enforcement 

Record System, January 28, 2015 (80 FR 4637); and, 

 Treasury .016, Reasonable Accommodations Records, February 24, 2015 (80 FR 9853).

In addition, the Internal Revenue Service republished its systems of records inventory, including 

86 SORNs, in the Federal Register on September 8, 2015 (80 FR 54063). These republished 

SORNs are available online at: https://www.treasury.gov/privacy/issuances/Documents/2015-

21980,%20IRS%20SOR,%2020150908,%2080%20FR%2054063.pdf.

During FY 2015, Treasury terminated one system of records, Departmental Offices .318,

Consumer Financial Protection Bureau (CFPB) Implementation Team Correspondence 

Tracking Database (79 FR 73700). Treasury no longer holds these records, they are now 

covered under CFPB .011 Correspondence Tracking Database (December 17, 2013 at 78 FR 

76286), (https://www.federalregister.gov/articles/2013/12/17/2013-29969/privacy-act-of-1974-

as-amended). Treasury has purged these files in accordance with Treasury Directive 80-05, 

‘‘Records and Information Management Program.’’

Treasury also published one proposed rule and one final rule in the Federal Register in FY 2015: 

 The Departmental Offices (DO) Proposed Rule, DO.411 Intelligence Enterprise, October 

3, 2014 (79 FR 59699); and,

 Internal Revenue Service (IRS) Final Rule IRS 37.111, Preparer Tax Identification 

Number Records, March 17, 2015 (80 FR 13764).

Treasury maintains approximately 271 systems of records, nearly 54 percent of which are 

maintained by the Internal Revenue Service (IRS). A complete list of the Department’s SORNs 

is available online at: https://www.treasury.gov/privacy/issuances/Pages/default.aspx.

 

21 See 31 C.F.R. §§ 1.20-1.36.
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Privacy Impact Assessments 

A Privacy Impact Assessment (PIA) is an analysis of how information is handled to ensure 

compliance with legal, regulatory, and policy privacy requirements. It assesses the risks and 

effects of collecting, maintaining and disseminating information and discusses the mitigation 

strategies agencies use to address those risks. Section 208 of the E-Government Act of 2002 (EGov Act) requires agencies to conduct PIAs for electronic information systems and collections 

that involve the collection, maintenance, or dissemination of information in identifiable form 

from or about members of the public. In FY 2015, Treasury reviewed 167 PIAs. Pursuant to the 

E-Gov Act, agencies are required to make PIAs publicly available through the agency website, 

the Federal Register, or other means. The Department’s PIAs are available online at: 

http://www.treasury.gov/privacy/PIAs. 

Federal Information Security Management Act of 2002

The Federal Information Security Management Act of 2002 (FISMA) requires each agency to 

develop, document, and implement an agency-wide program to provide security for the 

information and information systems that support its operations. In addition, FISMA requires 

Chief Information Officers, Inspectors General, and SAOPs to report to OMB on information 

security questions that address areas of risk. Federal agencies must report performance metrics 

related to the management of their privacy programs. This entails tracking and reporting the 

number of Treasury systems that contain PII, and the number of systems that require and/or have 

completed a PIA and/or SORN.

For FY 2015, the Department reported a total inventory of 305 FISMA systems containing 

personal information in identifiable form. 

Section 803 of the Implementing Recommendations of the 9/11 Commission Act of 2007

Pursuant to Section 803 of the Implementing Recommendations of the 9/11 Commission Act of 

2007, agencies must ensure that adequate processes exist to receive, investigate, respond to, and 

redress complaints from individuals who allege privacy or civil liberties violations. To meet the 

requirement, Treasury issued Treasury Directive (TD) 25-09, which directs heads of bureaus and 

relevant offices to establish internal procedures to ensure accurate and complete reporting to 

OPTR. 

The ASM, with the support of OPTR, continues to provide timely Section 803 metrics to 

Congress on behalf of the Department. For FY 2015, Treasury bureaus and its offices performed 

363 reviews, provided advice 12 times, and responded to five privacy and civil liberties 

complaints. The types of reviews the Department and its bureaus conducted included:

 Conducted 77 Privacy Threshold Assessments (to determine whether a Privacy Impact 

Assessment was required).

 Conducted 134 Privacy Impact Assessments.

 Eliminated/redacted or masked Social Security Numbers from 78 forms or programs.

 Approved or extended 63 computer Matching Agreements.

 Received one privacy complaint which was resolved in favor of the government

 Received four civil liberties complaints all of them were resolved in favor of the 

government.
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PII HOLDINGS AND REDUCTION

Treasury maintains an inventory of its PII holdings in its PII Holdings Database. Treasury 

completed the PII Holdings Database in FY 2013 to comply with OMB Memorandum 07-16, 

Safeguarding Against and Responding to the Breach of Personally Identifiable Information, 

(OMB M-07-16). During the 2015 reporting period, Treasury updated the PII Holdings 

Database to ensure accuracy and comply with OMB requirements. This update added links to 

additional privacy documentation to the database and the development of a revised user manual.

ELIMINATION OF THE UNNECESSARY USE OF SOCIAL SECURITY 

NUMBERS

Internal Revenue Service (IRS)

In FY 2015, The IRS made substantial progress reducing and eliminating the use of unnecessary 

Social Security Numbers (SSN) through its Social Security Number Elimination and Reduction 

(SSN ER) and SSN ER Two-Dimensional Barcode Electronic Check Presentment (2DB/ECP) 

Programs. The IRS conducted a comprehensive analysis to identify additional opportunities to 

reduce or eliminate SSNs. Part of this analysis included an inventory and review of all forms 

containing an SSN and weekly reports listing newly created and obsolete forms to ensure the 

SSNs are absolutely required. In addition, IRS implemented a new process to ensure all newly 

created correspondence is reviewed to determine if the use of an SSN is necessary, noting there 

are instances where use of the complete SSN is necessary or required by statute.

IRS continues implementation of 2D barcodes to provide the information necessary to process 

notices and mask the full display of the SSN in the body of the notices by exposing only the last 

four digits of the SSN. In FY 2015, thirty-five additional notices with an annual volume of 

17.5M contained masked SSNs. In addition, IRS added a barcode to 22 Automated Collection 

notices with an annual volume of 5.2M, replacing previously masked SSNs to further protect 

identities. 

The Alcohol and Tobacco Tax and Trade Bureau (TTB)

In FY 2015, TTB began a review of SSN use across the bureau to verify that continued use is 

absolutely required to achieve mission and business requirements. TTB is leveraging some of 

the information gathered in an initial review from 2007. Most applications and processes that 

require the SSN for specific transactions do not require its use for every transaction and TTB

closely scrutinizes the use of SSNs to determine if some alternative form of identification may 

suffice. There are some instances where TTB previously determined that the SSN is 

required. TTB is revisiting those instances to determine whether the SSN is still required. In 

some other cases where SSN use is justified, TTB uses alternatives to counteract the 

vulnerability of SSN use. These alternatives include: truncated SSN, encryption, and other ways 

to mask the data. TTB will continue to monitor its systems and processes to evaluate SSN use 

and eliminate when possible.
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PRIVACY AWARENESS AND TRAINING

A Culture of Privacy Awareness

OMB M-07-16 requires agencies to train employees on their privacy and security responsibilities 

before granting them access to agency information and information systems. Additionally, 

agencies must provide at least annual refresher training to ensure employees continue to 

understand their responsibilities. Ninety nine percent of all Treasury employees completed 

annual privacy awareness training during the reporting period.

Pursuant to OMB A-130, Management of Federal Information Resources, Appendix I, Section 

3.a(6), OPTR conducted a review of the Department’s training practices during the reporting 

period. This review resulted in an updated version of the departmental privacy training course, 

entitled “A Culture of Privacy Awareness.”

Internal Revenue Service (IRS) Privacy Training

Privacy and Unauthorized Access to Taxpayer Accounts (UNAX) training is mandatory for all 

IRS employees. In FY 2015, the IRS conducted an analysis to assess the specific demographics 

associated with various UNAX violations, such as: job series, geographic location, length-ofservice categories, and others. IRS also held focus group meetings with IRS managers and 

employees to make sure UNAX training met employee needs. IRS combined the data to enhance 

training and communications and streamline the existing mandatory briefing process. The IRS 

also created three new scenarios depicting real-life workplace dilemmas and resulting UNAX 

violations that IRS incorporated into the service-wide virtual training. 

The IRS also expanded its privacy training courses for technical employees. In 2015, IRS 

launched a new, “Privacy Foundational Overview Training,” course and developed four new 

role-based Privacy Training Courses: Project Managers, Privacy & Civil Liberties Impact 

Assessment Preparers, Business Subject Matter Experts, and Adaptive Privacy Impact 

Assessments Preparers. 

IRS Advancements in Privacy Policy 

The IRS takes a proactive approach to privacy policy development by identifying emerging 

issues, identifying gaps, issuing policy and establishing accountability. In 2015, the IRS updated 

employee policy and guidance on sending personally identifiable information (PII) through 

email. The IRS issued Interim Guidance on “Sending Sensitive But Unclassified (SBU) 

Information and/or Work-Related Documents to External (non-IRS) Email Addresses.” The 

interim guidance clarified the rule on sending work-related documents to external email 

addresses and created limited exceptions to the rule that prohibits IRS employees, contractors 

and vendors from sending SBU in emails without using approved encryption technology. 

Through collaboration of IRS Information Technology and Privacy organizations, IRS 

implemented a, “Safeguarding Personally Identifiable Information Data Extracts” (SPIIDE) 

automated tool to monitor outgoing unencrypted employee email (including attachments) and 

web traffic. The SPIIDE tool provides significant systemic accountability and oversight and 

helps ensure employee compliance with email security guidance. IRS has conducted a PIA on 

the SPIIDE tool to assess the privacy risks and mitigations associated with the data loss 
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prevention tool. The PIA was approved on March 31, 2015 and is available online at: 

https://www.irs.gov/pub/irs-utl/SPIIDEDLP-pia.pdf

LEADERSHIP AND COORDINATION WITHIN TREASURY 

Treasury Directive 25-06, The Treasury Data Integrity Board

In January 2015, OPTR revised Treasury Directive 25-06, The Treasury Data Integrity Board.

This directive establishes a Treasury Data Integrity Board (DIB), pursuant to the Privacy Act of 

1974, as amended. It authorizes the issuance of Treasury Directive Publication (TD P) 25-06, 

“Computer Matching Handbook.” It also sets forth the policy for the DIB membership, 

operations, and responsibilities, as well as the procedures for engaging in computer matching 

activities. The current version of TD 25-06 is available at: https://www.treasury.gov/about/roleof-treasury/orders-directives/Pages/td25-06.aspx

Treasury Directive 81-08: Certification Process for the Use of Web Measurement and 

Customization Technologies on Treasury Websites

In April 2015, OPTR revised the Treasury Directive 81-08: Certification Process for the Use of 

Web Measurement and Customization Technologies on Treasury Websites. This Directive 

establishes the process for obtaining certification for the use of Web Measurement and 

Customization Technologies, including “Cookies,” on Treasury’s publicly accessible websites. 

In accordance with Office of Management and Budget Memorandum 10-22, “Guidance for 

Online Use of Web Measurement and Customization Technologies,” the Directive also 

establishes the required steps for obtaining approval from the Deputy Assistant Secretary for 

Information Systems and Chief Information Officer for the use of Tier 3 multi-session 

technology that collects Personally Identifiable Information (PII). The current version of TD 81-

08 is available at: https://www.treasury.gov/about/role-of-treasury/orders-directives/Pages/td81-

08.aspx

Executive Order (E.O.) 13636: Improving Critical Infrastructure Cybersecurity

On February 12, 2013, the President signed E.O. 13636, Improving Critical Infrastructure 

Cybersecurity, stating: “[i]t is the policy of the United States to enhance the security and 

resilience of the Nation’s critical infrastructure and to maintain a cyber-environment that 

encourages efficiency, innovation, and economic prosperity while promoting safety, security, 

business confidentiality, privacy, and civil liberties.”

To ensure the inclusion of privacy and civil liberties protections in activities under the Order, 

section 5(a) of the E.O. required federal agencies to coordinate E.O. 13636-related cybersecurity 

activities with their SAOP. Section 5(b) further required the SAOP to conduct an assessment of 

their agency’s activities under the Order. As required, OPTR conducted a privacy and civil 

liberties assessment of the Department’s cybersecurity activities under the E.O. As directed

under the E.O., Treasury submitted its assessment to the Department of Homeland Security for 

inclusion in a consolidated public report. The consolidated report is available here: 

http://www.dhs.gov/sites/default/files/publications/2015%20EO%2013636%20Assessment%20

Report-FINAL04-10-2015.pdf
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Treasury’s Privacy Website

In FY 2015, OPTR completed substantial improvements to the privacy page on the Treasury 

website. The website, www.treasury.gov/privacy, now provides visitors with easier access to 

PIAs, SORNs, computer matching agreements, reports, and more. In addition to making 

information easier to find on the website, OPTR leveraged technical upgrades to the Federal 

Register website, which now allows users to review notices online more easily. OPTR also 

completed updates to the Treasury.gov privacy policy. These updates include information about 

Treasury’s use of social media and provide notice to individuals about Treasury’s collection of 

information with “The New 10” website. “The New 10” is Treasury’s own social media website 

that solicits public feedback about the design of the 10 dollar bill. The website is available here: 

https://thenew10.treasury.gov/

U.S.-EU Data Privacy and Protection in Law Enforcement, Criminal Justice, and Public 

Security Matters

In FY 2015, OPTR continued to participate in the negotiations between the United States and the 

EU on the Data Protection and Privacy Agreement (DPPA). The DPPA negotiations are an 

effort to establish standard data protection provisions for future personal information sharing for 

law enforcement purposes between the United States, the EU, and EU member states.

TREASURY COMPUTER MATCHING PROGRAMS

Pursuant to the Computer Matching and Privacy Protection Act of 1988,

22 Treasury maintains a 

Data Integrity Board (DIB) to oversee Treasury computer matching programs. Computer

matching programs provide a direct benefit to the public by assisting in the elimination of errors 

and in monitoring waste, fraud, and abuse.

In FY 2015, the Treasury DIB reviewed and approved sixty-one extensions of computer 

matching programs and renewed two of the Department’s ongoing computer matching programs. 

A new matching agreement may exist for eighteen months; this agreement can be extended for 

an additional 12-months. After an extension expires, an agreement may be renewed for an 

additional eighteen months. 

Published notices for all of Treasury’s ongoing computer matching programs are available online 

through the Treasury Privacy Act page at: http://www.treasury.gov/privacy/computer-matchingprograms.

The DIB’s actions included:

Agreement Title Agencies Involved Action Date of Action

Medicare Part B Premium 

Reduction

Internal Revenue Service -

Social Security Administration

Extension October 1, 2014 

Data Loss Prevention Program Internal Revenue Service Extension November 1, 2014 

Taxpayer Address Request 

Program

Internal Revenue Service -

Department of Justice

Renewal October 6, 2014

 

22

 Pub. L. No. 100-503.
16

Disclosure of Information to 

Federal, State, and Local Agencies

Internal Revenue Service -

Social Security Administration

Extension January 1, 2015

Disclosure of Information to 

Federal, State, and Local Agencies

Internal Revenue Service -

Department of Veteran Affairs

Extension January 1, 2015

Disclosure of Information to 

Federal, State, and Local Agencies

IRS- (50) States

*This includes 50 separate 

agreements.

Extension January 1, 2015

CMA 1038-Supplemental Security 

Income

Bureau of the Fiscal Service -

Social Security Administration

Extension April 1 , 2015

CMA 1304-Medicare Part D 

Prescription Benefit Program

Bureau of the Fiscal Service -

Social Security Administration

Extension April 1 , 2015

Verification of Household Income 

and Family Size for Insurances 

Affordability Programs and 

Exemptions

Internal Revenue Service -

Department of Health and 

Human Services

Extension April 2, 2015

Medicare Secondary Payer 

Program

Internal Revenue Service -

Social Security Administration 

- Department of Health and 

Human Services

Extension May 1, 2015

Medicare Prescription Drug 

Subsidy Program

Internal Revenue Service -

Social Security Administration

Renewal May 11, 2015

SECTION TWO:

DEPARTMENT OF THE TREASURY 2015 DATA MINING REPORT

BACKGROUND

The Role of the Treasury Chief Privacy and Civil Liberties Officer (CPCLO)

The Department of the Treasury (Treasury or the Department) is providing this report to 

Congress pursuant to Section 803 of the Implementing Recommendations of the 9/11 

Commission Act of 2007 (9/11 Commission Act), entitled the Federal Agency Data Mining 

Reporting Act of 2007 (Data Mining Reporting Act or the Act). This report discusses activities 

currently deployed or under development in the Department that meet the Data Mining 

Reporting Act’s definition of data mining. The report also provides the information the Act 

requires with respect to each data mining activity.

DEFINITIONS

(1) DATA MINING. The term “data mining” means a program involving pattern-based 

queries, searches, or other analyses of one or more electronic databases, where:
17

a. a department or agency of the Federal Government, or a non-Federal entity acting 

on behalf of the Federal Government, is conducting the queries, searches, or other 

analyses to discover or locate a predictive pattern or anomaly indicative of 

terrorist or criminal activity on the part of any individual or individuals;

b. the queries, searches, or other analyses are not subject-based and do not use 

personal identifiers of a specific individual, or inputs associated with a specific 

individual or group of individuals, to retrieve information from the database or 

databases; and 

c. the purpose of the queries, searches, or other analyses is not solely—

i. the detection of fraud, waste, or abuse in a Government agency or 

program; or

ii. the security of a Government computer system.

(2) DATABASE. The term “database” does not include telephone directories, news 

reporting, information publicly available to any member of the public without payment of 

a fee, or databases of judicial and administrative opinions or other legal research 

sources.23

Three Treasury bureaus maintain systems using applications that meet the definition of data 

mining: the Financial Crimes Enforcement Network (FinCEN), the Internal Revenue Service 

(IRS), and the Alcohol and Tobacco Tax and Trade Bureau (TTB). These IRS, FinCEN, and 

TTB systems were discussed in previous Treasury data mining reports. 

FINCEN DATA MINING ACTIVITIES

(A) A thorough description of the data mining activity, its goals, and, where appropriate, the 

target dates for the deployment of the data mining activity.

FinCEN’s mission is to safeguard the financial system from illicit use, combat money 

laundering, and promote national security through the collection, analysis, and dissemination of 

financial intelligence and strategic use of financial authorities. To accomplish its mission, 

FinCEN provides financial intelligence, data stewardship, and support for law enforcement. 

FinCEN also engages in the detection of trends and the ascertainment of typologies of money 

laundering and terror finance. FinCEN strives to respect privacy and civil rights and the exercise 

of civil liberties while overseeing the data it maintains and uses in fulfillment of its mission as 

set forth under the USA PATRIOT Act, Public Law 107-56, October 26, 2001. 

In furtherance of this goal, FinCEN is required to maintain a government wide data access 

service with a range of financial transactions information; to conduct analysis and dissemination 

of information in support of law enforcement at the Federal, State, Local, and International 

levels; to identify emerging trends and methods in money laundering and other financial crimes; 

to serve as the Financial Intelligence Unit of the United States; and, to carry out other delegated 

regulatory responsibilities. FinCEN’s legal authorities are codified at 31 U.S.C. § 310. FinCEN 

 

23 42 U.S.C § 2000ee-3(b)(1). “[T]elephone directories, news reporting, information publicly available to any 

member of the public without payment of a fee, or databases of judicial and administrative opinions or other legal 

research sources” are not “databases” under the Act. § 2000ee-3(b)(2).
18

works to achieve its mission while avoiding the collecting and indexing of information on 

persons exercising their constitutional rights and civil liberties. 

FinCEN’s analysts use various data analysis techniques and trend spotting algorithms for 

generating leads, meaning, locating groups of subjects or institutions whose activities as revealed 

by the analysis and algorithms warrant outreach, investigation, or other statutorily mandated 

activities. 

FinCEN has successfully developed algorithms designed to identify activity associated with 

specific types of financial crimes, such as check cashing activity associated with health insurance 

fraud. The term “algorithm” refers to a sequence of steps and instructions that are applied to data, 

including FinCEN’s data, to extract and sort data to achieve FinCEN’s goals.

FinCEN also uses text-mining capabilities in conjunction with structured field searches to 

examine filing patterns across financial sectors. This analysis is designed to support a broad 

range of objectives from the identification of trends and patterns of illicit financial activity to the 

detection of institutions that may require additional regulatory attention. 

FinCEN continues to develop and expand the use of automated business rules to rapidly surface 

potentially high value illicit financial activity on a daily basis. The term “business rule” refers to 

automated queries or algorithms designed to screen incoming Bank Secrecy Act (BSA) findings 

against predictive criteria to identify high priority filings likely to require further review or 

analysis. Rule findings are reviewed internally by FinCEN and distributed to external 

stakeholders, such as law enforcement and our foreign financial intelligence unit (FIU) partners. 

FinCEN’s business rules play a vital role in the identification and dissemination of timely 

financial intelligence to combat threats such as terrorist financing. 

(B) A thorough description of the data mining technology that is being used or will be used, 

including the basis for determining whether a particular pattern or anomaly is indicative 

of terrorist or criminal activity

FinCEN leverages two principle methods for deriving information relevant to illicit financial 

activity from the BSA data. The first is content driven, that is, searching for specific entity 

names, or term combinations used in reporting that are associated with various types of illicit 

financial activity. The second method is pattern driven and can take various forms. Patterns 

may be derived from searches for a particular type of subject in the data. FinCEN then identifies 

subjects that fit that pattern and have certain filing profiles. Matching filing patterns across 

different types of statutorily required BSA reports highlights anomalous behavior that leads to 

the identification of new investigation subjects. 

For its data analysis activities, analysts leverage FinCEN’s Advanced Analytics system, which is 

an environment comprised of commercial off-the-shelf (COTS) and custom developed tools 

with capabilities including statistical, social network, and geospatial analysis, data modelling and 

visualization, and text analytics that aid in the analysis of BSA data.
19

(C) A thorough description of the data sources that are being or will be used 

BSA reports administered by FinCEN, e.g., a report by a financial institution of a suspicious 

transaction relevant to a possible violation of law or regulation,

24 form the underlying data for 

FinCEN’s manual and automated proactive search methods and trend analysis activities. 

In order to accomplish its mission and give context to the data, FinCEN extracts from its BSA

database, FinCEN must consider other information available to it through a variety of sources, 

including open source material, law enforcement information, other government information, 

and subscription services. This information is used to support or amplify conclusions or 

hypotheses derived from the analysis of BSA data. For example, commercially available 

databases are used to support or further identify information and to aid in the identification of 

potential illicit activity based on suspicious trends, patterns, or methods. FinCEN’s trend 

analysis uses any records available to FinCEN in fulfilling its mission, including subpoenaed 

financial records, public source information, commercial database information, and third party 

data sources, such as Census Bureau, Social Security Administration25, and Office of Foreign 

Assets Control data. 

(D) An assessment of the efficacy or likely efficacy of the data mining activity in providing 

accurate information consistent with, and valuable to, the stated goals and plans for the 

use or development of the data mining activity

FinCEN provides strategic and tactical products for several audiences: law enforcement, foreign 

Financial Intelligence Unit (FIU) partners, financial regulators, the financial industry, and the 

general public. Each of these sets of consumers has different restrictions or guidelines under 

which FinCEN can provide BSA data or BSA derived analysis. 

In FY 2015, FinCEN produced a total of 889 intelligence products for law enforcement partners 

and responded to 916 requests for BSA information from foreign FIU partners. For domestic and 

foreign law enforcement partners, FinCEN provides high value data analytics. FinCEN annually 

receives the results of surveys of its foreign Egmont member counterparts and domestic law 

enforcement agencies regarding the utility of its analytical products. For FY 2015, these survey 

results reflect positive responses in the mid-90th percentile. FinCEN also receives feedback on 

individual reports from law enforcement and regulatory efforts to combat terrorism financing, 

healthcare, mortgage, and government programs fraud, southwest border narcotics, and bulk cash 

smuggling. Examples of several analytical projects that received significant positive feedback 

are outlined below: 

 To combat money laundering threats along the southwest border, FinCEN employed 

advanced analytic methodologies and data-matching algorithms to trace financial flows 

between Mexico and the United States. By matching Reports of International 

Transportation of Currency or Money Instruments (CMIR), Currency Transaction 

Reports (CTR), and Suspicious Activity Reports (SAR) data, FinCEN was able to 

 

24 31 U.S.C. § 5318(g).

25

 The Death Master File is Social Security Administration (SSA) information used by medical researchers, 

hospitals, medical programs, and law enforcement agencies and other government agencies to verify a person’s 

death and to prevent fraud. Although it is SSA information, the National Technical Information Service in the 

Department of Commerce maintains the database. For more information see: http://www.ntis.gov/products/ssadmf.aspx.
20

successfully identify the physical transportation of funds across the southwest border that 

were subsequently deposited into US financial institutions. FinCEN was further able to 

trace the repatriation of these funds back to Mexico via electronic funds transfers 

described in the narratives of SARs. The ability to successfully trace these financial 

flows provided FinCEN with visibility into the scale of financial flows between the US 

and Mexico, supported assessments on the vulnerabilities created by such transactions, 

and identified networks of actors leveraging these types of transactions to launder the 

proceeds of illicit activities.

 FinCEN developed a series of business rules and algorithms designed to identify actors 

engaged in illicit financial activity who may conduct transactions by moving from 

institution to institution to avoid detection. The project examined the migration of actors 

engaged in illicit activity through US financial institutions in order to identify targets for 

law enforcement action, provide guidance to regulators and the financial industry on the 

vulnerability of institutions to the migration of illicit actors, as well as identify financial 

institutions that may be (knowingly or unknowingly) facilitating money laundering 

activities. Initial results from the project received significant positive feedback from US

 law enforcement agencies and district attorneys’ offices.

 To combat terrorist financing threats, FinCEN has developed more than 65 business rules 

designed to identify and disrupt these organization’s revenue streams, target their 

financial support networks, and identify foreign terrorist fighters who may be seeking to 

travel to or from conflict regions. These rules generate more than 1,250 leads per month 

that FinCEN disseminates to the law enforcement, intelligence, and FIU communities via 

expedited “Flash Reporting.” Flash Reports are designed to provide critical intelligence 

to FinCEN’s stakeholders on a timely basis. Since the inception of the program in late 

2014, FinCEN has disseminated more than 500 counter terrorist financing Flash Reports. 

Feedback on these reports has been extremely positive, with stakeholders noting that the 

reports helped corroborate information related to investigations and provided new leads, 

assisted investigators in identifying targets, cultivated sources, resulted in the 

identification of more than 30 previously unknown foreign terrorist fighters who were 

added to the US no-fly list, and assisted in the real-time interdiction of an outbound 

shipment of concern.

In addition, FinCEN designs its business rules so they are narrowly tailored to achieve FinCEN’s 

mission, and each rule is developed, tested, implemented and re-tested for efficacy. The Office 

of Chief Counsel and the Technology Division are engaged during the development of all 

business rules. FinCEN continues to receive strong positive feedback both from our domestic 

and international partners on the value of the intelligence derived from our business rules 

program. In the most recent customer satisfaction survey results received in June 2015, 80 

percent of respondents indicated they found BSA data useful and impactful. 

Finally, FinCEN provides annual aggregated statistics on SAR data by sector to the public in a 

publication titled “SAR Stats.” The most recent version of SAR Stats was published on 

FinCEN’s website in October 2015. Data indicate that the previous version of SAR Stats, 

published in June 2014, was accessed more than 500,000 times by readers, an indication of the 

publication’s high utility.
21

(E) An assessment of the impact, or likely impact, of the implementation of the data mining 

activity on the privacy and civil liberties of individuals, including a thorough description 

of the actions that are or will be taken with regard to the property, privacy, or other rights 

or privileges of any individual as a result of implementing the data mining activity

The impact of FinCEN’s congressionally mandated mission on the privacy and civil liberties of 

individuals has been and will continue to be minimal. As a threshold matter, the Supreme Court 

has ruled that the financial information that banks and other financial institutions hold, and that 

FinCEN collects and analyzes pursuant to its authority in 31 U.S.C. § 310 and the BSA 

(discussed in more detail in item (F) below), carries no constitutionally protected “expectation of 

privacy.” Moreover, the Right to Financial Privacy Act of 1978 expressly provides that it gives 

no protection for financial records or information required to be reported in accordance with any 

federal statute or regulation, which includes information contained in BSA reports. 

Significantly, FinCEN takes no adverse actions against individuals based on the existence of, or 

information contained in BSA data. Since a BSA report itself is not necessarily indicative of 

criminal activity, it is only useful when viewed in conjunction with other evidence. Therefore, 

FinCEN provides the data, or analytical products analyzing the data, to outside agencies where 

the information may be relevant to current or potential investigations or proceedings under the 

jurisdiction of those agencies.

During the development of all business rules, analytical models, and algorithms, FinCEN

documents a description of why the analytics will not adversely affect an individual or entity’s 

privacy or civil liberty rights. This documentation is shared with both FinCEN’s Technology 

Division and the Office of Chief Counsel. 

The BSA provides standards for proper use of the financial data collected by FinCEN. The 

collected information is also generally subject to the Privacy Act of 1974, discussed in more 

detail under item (F) below. FinCEN has developed extensive policies and procedures to ensure, 

to the extent reasonably possible, that: (1) the analyzed information is used for purposes 

authorized by applicable law; and (2) the security of the information is adequately maintained. 

Analytical products produced by FinCEN are subject to clearly specified restrictions regarding 

use and further dissemination of the products to ensure that the products will only be used by 

appropriate agencies for statutorily authorized purposes. To the extent such products reference 

information collected pursuant to the BSA, FinCEN has issued guidelines requiring user 

agencies to attach warning language to such products and to follow specific procedures for 

further dissemination of the BSA information. These procedures aim to ensure that: (1) only 

appropriate agencies will have access to the information; (2) the information will be used for 

statutorily authorized purposes; (3) agencies with access are aware of the sensitivity of the 

material; and (4) FinCEN will be able to track which agencies have such materials in their 

possession.

FinCEN posts Privacy Impact Assessments (PIA) on their public website, which informs the 

public of FinCEN activities and practices related to the collection, processing, retention, and 

distribution of personally identifiable information (PII).26 The PII handled by these systems is 

 

26 For more information about FinCEN PIAs, see: https://www.fincen.gov/foia/pia.html
22

necessary to properly assist regulators and law enforcement in identifying and monitoring the 

financial activities of individuals who are potentially committing financial crimes.

(F) A list and analysis of the laws and regulations that govern the information being 

collected, reviewed, gathered, analyzed, or used in the data mining activity 

1. The Bank Secrecy Act, 31 U.S.C. § 5311, et seq. (BSA) and Implementing Regulations, 

31 C.F.R. Chapter X, et seq:

31 U.S.C. § 5311— Declaration of Purpose 

This section specifies that the purpose of the recordkeeping and reporting requirements in the 

BSA is to, “require certain reports where they have a high degree of usefulness in criminal, tax, 

or regulatory investigations or proceedings, or in the conduct of intelligence or 

counterintelligence activities, including analysis, to protect against international terrorism.” 

FinCEN strives to ensure that all uses of information are consistent with this purpose. 

31 C.F.R. § 1010.301— Determination by the Secretary 

This regulation provides the determination that the reports collected pursuant to the BSA have a,

“high degree of usefulness,” in the areas covered by 31 U.S.C. § 5311. 

31 U.S.C. § 5319 — Availability of Reports 

This section makes it clear that, upon request, the Secretary (as delegated to FinCEN) is required 

to provide BSA information for the purposes specified in 31 U.S.C. § 5311, to agencies 

including state financial institutions supervisory agencies, United States intelligence agencies, or 

self-regulatory organizations registered with the Securities and Exchange Commission or the 

Commodity Futures Trading Commission. This list of types of agencies is not exhaustive, but 

those listed are clearly covered. This section also provides that reports collected pursuant to the 

BSA are exempt from disclosure under the Freedom of Information Act, 5 U.S.C. § 552. 

31 C.F.R. § 1010.950 — Availability of Information 

This section authorizes the Secretary to make BSA information available to appropriate agencies 

for purposes specified in the BSA, and specifies that the requesting agency is to receive the 

information, “in confidence.” 

31 U.S.C. § 5313 — Reports on domestic coins and currency transactions

This section provides for the reporting by financial institutions of reports of certain currency 

transactions involving more than an amount specified by the Secretary (as delegated to FinCEN). 

31 C.F.R. §§ 1010.311; 1021.311 — Reports of transactions in currency 

These regulations implement the reporting requirement of 31 U.S.C. § 5313 and specify the 

amount of reportable transactions in currency at more than $10,000. 
23

31 U.S.C. § 5316 — Reports on exporting and importing monetary instruments 

This section requires reports by those that transport currency or other monetary instruments of 

more than $10,000 at one time from outside the United States into the United States, or from the 

United States outside the United States. 

31 C.F.R. § 1010.340 — Reports of transportation of currency or monetary instruments 

This regulation implements the reporting requirement of 31 U.S.C. § 5316 with respect to 

currency or other monetary instruments of more than $10,000 imported into the United States or 

exported outside the United States.

31 U.S.C. § 5314 — Records and reports on foreign financial agency transactions 

This section authorizes the Secretary (as delegated to FinCEN) to prescribe regulations requiring 

the reporting of certain types of foreign transactions and relationships with foreign institutions. 

31 C.F.R. § 1010.350 — Reports of foreign financial accounts 

This regulation, implementing 31 U.S.C. § 5314, requires that U.S. persons file reports of foreign 

bank accounts. 

31 U.S.C. § 5318(g) — Reporting of suspicious transactions 

This section authorizes the Secretary (as delegated to FinCEN), to require the reporting of 

suspicious transactions relevant to a possible violation of law. The section also provides for the 

confidentiality of such reports, barring financial institutions from notifying anyone involved in 

the transaction that the transaction has been reported. Government employees are subject to the 

same confidentiality restrictions, except as “necessary to fulfill the official duties” of such 

employees. The policies and procedures detailed above in response to item (E) are aimed, in 

large part, at maintaining the confidentiality of these reports. 

31 C.F.R. §§1010.320;1020.320; 1021.320; 1022.320; 1023.320; 1024.320; 1025.320; 1026.320 

— Reports of Suspicious Transactions 

These regulations implement 31 U.S.C. § 5318(g), requiring covered financial institutions to file 

suspicious activity reports and requiring the maintaining of strict confidentiality of the reports. 

31 U.S.C. § 5331— Reports relating to coins and currency received in nonfinancial trade or 

business 

This section provides for the reporting of currency transactions of more than $10,000 by 

businesses other than financial institutions. 
24

31 C.F.R. § 1010.330 — Reports related to currency in excess of $10,000 received in a trade or 

business

This regulation implements 31 U.S.C. § 5331. 

2. The Privacy Act of 1974 (Privacy Act), 5 U.S.C. § 552a 

Generally, the Privacy Act protects reports that FinCEN collects pursuant to the BSA as these

reports are “records” contained in a “system of records.”27 The Privacy Act provides that records 

that are covered may be disclosed without the written permission of the individual to whom the 

record pertains if they are disclosed pursuant to a “routine use.”28 FinCEN includes sets of 

routine uses in its published Systems of Records Notices (SORNs) as the Privacy Act requires. 

These routine uses identify the individuals and organizations external to Treasury with which 

FinCEN routinely shares BSA information. Sharing with these specified recipients is consistent 

with the purposes for which the information is collected, as specified in the BSA. 

FinCEN has three SORNs that cover the information it collects under the BSA: 

 (1) Treasury/FinCEN .001, FinCEN Investigations and Examinations System29;

 (2) Treasury/FinCEN .002, Suspicious Activity Report (SAR) System30; and,

 (3) Treasury/FinCEN .003, Bank Secrecy Act (BSA) Reports System.

31

FinCEN followed Privacy Act procedures (including appropriate public notice and comment 

periods) to exempt certain records maintained in the SARs and BSA systems of records from 

specific provisions of the Privacy Act, including those allowing for subject’s access to the 

reports, notification to the subject when reports are shared, requests for correction of the contents 

of such reports by the subject, and the civil remedies covering these areas. These exemptions 

prevent individuals who are planning crimes from avoiding detection or apprehension or 

structuring their operations to avoid detection or apprehension.

3. Other Relevant Provisions 

31 U.S.C. § 310— Financial Crimes Enforcement Network 

This section establishes FinCEN as a bureau in the Department of the Treasury, sets out the 

duties and powers of the Director, and empowers the Director to administer the BSA to the 

 

27 5 U.S.C. § 552a(a)(3) (defining a “record” to mean any item, collection, or grouping of information about an 

individual that is maintained by an agency, including, but not limited to, his education, financial transactions, 

medical history, and criminal or employment history and that contains his name, or the identifying number, symbol, 

or other identifying particular assigned to the individual, such as a finger or voice print or a photograph and a 

“system of records” to mean a group of any records under the control of any agency from which information is 

retrieved by the name of the individual or by some identifying number, symbol, or other identifying particular 

assigned to the individual);

28 5 U.S.C. § 552a(b)(3).

29 79 Fed. Reg. 20969 (April 14, 2014).

30

 Id. at 20972.

31 Id. at 20974.
25

extent delegated by the Secretary of the Treasury.32 This section also requires FinCEN to 

maintain a “government-wide data access service” for the information collected under the BSA, 

as well as records and data maintained by other government agencies and other publicly and 

privately available information.33 FinCEN is required to “analyze and disseminate” the data for 

a broad range of purposes consistent with the law.34 These purposes include identifying possible 

criminal activity; supporting domestic and international criminal investigations (and related civil 

proceedings); determining emerging trends and methods in money laundering and other financial 

crimes; supporting the conduct of intelligence and counterintelligence activities, including 

analysis, to protect against international terrorism; and supporting government initiatives against 

money laundering. 

The section further requires that FinCEN furnish research, analytical, and informational services 

to financial institutions and domestic and foreign law enforcement agencies for the, “detection, 

prevention, and prosecution of terrorism, organized crime, money laundering and other financial 

crimes,” and provide, “computer and data support and data analysis to the Secretary of the 

Treasury for tracking and controlling foreign assets.”35 The section also provides for the 

establishment of standards for making the information available through efficient means, and to 

screen appropriate users and appropriate uses.36 The activities and procedures described in this 

report adhere to the requirements of this statute.

(G) A thorough discussion of the policies, and guidelines that are in place or that are to be 

developed and applied in the use of such data mining activity in order to: 

(i) Protect the privacy and due process rights of individuals, such as redress procedures 

A description of the policies, procedures, and guidance in place to ensure the privacy and due 

process rights of individuals that are the subject of FinCEN data mining activities is provided in 

subsection (E) above. 

(ii) Ensure that only accurate and complete information is collected, reviewed, analyzed, 

or used and guard against any harmful consequences of potential inaccuracies 

FinCEN, through its data perfection procedures, ensures that information contained in the 

database of BSA reports is accurate and complete. In addition, as discussed in item (E) above, 

FinCEN does not take adverse actions against individuals (outside the context of enforcing the 

requirements of the BSA itself) based on the information contained in BSA reports. In addition, 

because user agencies only use BSA information in conjunction with other evidence, a BSA 

report in itself is not used as the sole basis for adverse actions by user agencies. Accordingly, 

there is an inherent system of, “checks and balances,” in the use of BSA information that greatly 

reduces the risk of harmful consequences from inaccuracies that may be contained in BSA 

reports.

 

32 Treasury Order 180-01, Financial Crimes Enforcement Network (July 1, 2014) (delegating to the Director of 

FinCEN various duties and responsibilities, including the authority to administer, implement, and enforce the BSA).

33 31 U.S.C.§ 310(b)(2)(B)

34 Id. at § 310(b)(2)(C)(i)-(vii).

35 Id. at § 310(b)(2)(E), (G).

36 Id. at § 310(c)(1) and (c)(2). 
26

As noted earlier in this report, FinCEN’s BSA data contains no constitutionally protected,

“expectation of privacy” and FinCEN takes no adverse actions against individuals based on the 

BSA data collected. Therefore, FinCEN’s BSA analyst training does not focus on civil liberties. 

However, FinCEN has mandatory training for its data users that includes the privacy component 

of secure handling and safeguarding of the information. FinCEN provides on-line training for all 

external users as a requirement for system access. Biennially, at a minimum, users must 

complete training as a requirement of continued system access. In addition to this online 

training, FinCEN hosts webinars as requested. All FinCEN staff are required to annually 

complete Privacy Awareness training which includes the staff’s civil liberties responsibilities. 

Accountability for the security and confidentiality of the BSA data and its handling are 

prominently articulated in each of these courses’ materials

IRS DATA MINING ACTIVITIES

(A) A thorough description of the data mining activity, its goals, and, where appropriate, the 

target dates for the deployment of the data mining activity.

Three divisions of the IRS are engaged in data mining activities covered by the Act: IRS 

Criminal Investigation organization (IRS-CI); the IRS Small Business/Self-Employed Division 

(SB/SE); and the IRS Wage and Investment Division (W&I). Each of these IRS divisions uses 

one or more of six available data mining applications to search for specific characteristics that 

are indicators of potential criminal activity:

 Reveal;

 Investigative Data Analytics (IDA);

 Lead and Case Analytics (LCA);

 Electronic Fraud Detection System (EFDS); 

 Return Review Program (RRP); and,

 FinCEN Query

IRS-CI is tasked with protecting IRS revenue streams by detecting fraudulent activity and 

preventing recurrences. IRS-CI uses the Reveal, IDA, LCA, EFDS and RRP systems to support 

this work. Data uncovered using these systems may be reflected in indictments and criminal 

prosecutions. 

Reveal is a data query and visualization tool that allows CI analysts and agents to query and 

analyze large and potentially disparate sets of data through a single access point. This enhances 

the analyst’s ability to develop a comprehensive picture of suspicious or criminal activity. The 

program presents information to the user visually, exposing associations between entities in the 

data that might otherwise remain undiscovered. The VisuaLinks tool within Reveal builds 

visualization diagrams. IRS-CI Lead Development Centers (LDC), Scheme Development 

Centers (SDC), and field offices all use the system to identify and develop leads for refund 

frauds, counterterrorism, money laundering, offshore abusive trust schemes, and other financial 

crime. Recently, CI began the initiative to consolidate and streamline the data analytics program,

with the goal to shut down Reveal, by ensuring the data sets and the features are consolidated 

with the IDA and LCA. IRS anticipates completion of this activity within a year (September 

2016). 
27

IDA is a data query tool currently in use at the LDCs, SDCs, and field offices, and it provides CI 

analysts and special agents with the ability to query and analyze large and potentially disparate 

sets of electronic data through a single access point. IDA enhances these search results by 

linking relationships and exposing associations with events and other individuals. By using the 

IDA application, special agents and investigative analysts can proactively identify patterns 

indicative of illegal activities. This tool enhances investigation selection and supports 

investigative priorities in tax law enforcement, counterterrorism, and other high-priority criminal 

investigations. 

The IDA application uses data for both reactive and proactive queries. Reactive queries are a

result of specific, targeted investigations; proactive queries are the result of pattern matching to 

generate leads. Data available in the IDA application enable users to detect suspicious financial 

transactions indicative of money laundering, terrorism, and other financial crimes. IDA query 

results are used exclusively for the purpose of generating leads. Any investigative process that 

results from these leads uses the corresponding data from the originating systems.

LCA is a data query and visualization application that allows CI investigative analysts and agents 

to query and analyze large and disparate sets of data through a single access point. This 

enhances the analyst’s ability to develop a comprehensive picture of suspicious or criminal 

activity. The LCA application uses data for both reactive and proactive queries. Reactive 

queries are a result of specific, targeted investigations; proactive queries are the result of pattern 

matching to generate leads. Data available in the LCA application enable users to detect 

suspicious financial transactions indicative of money laundering, terrorism, and other financial 

crimes. The application presents information to the user visually, exposing associations between 

entities in the data that might otherwise remain undiscovered. The Palantir software used to 

create LCA allows users from the LDCs, SDCs, and field offices to visualization diagrams, 

graphs, spreadsheets, reports, timelines and maps to enhance investigation selection and supports 

investigative priorities to proactively identify and develop leads for refund fraud, identity theft, 

counterterrorism, money laundering, offshore abusive trust schemes, and other financial crime, 

as well as Bank Secrecy Act (BSA) Suspicious Activity Report (SAR) reviews and Financial 

Crimes Task Force activity. 

IRS-CI and W&I use RRP and EFDS to maximize detection of tax return fraud, tax 

noncompliance, and identity theft. EFDS compiles, cross-references, and verifies information 

indicative of potentially fraudulent tax returns. As EFDS receives returns, it loads and assigns a 

score to each tax return. Scores range from 0.0 to 1.0, with a higher score indicating a greater 

potential for fraud. RRP expands on EFDS’ capabilities by providing multiple model scores, rule 

breaks, and linking characteristics. In both RRP and EFDS, IRS-CI does not directly examine the 

scores, but does use returns that W&I determines to be potentially fraudulent as a basis for its 

criminal investigations. 

IRS-CI and SB/SE users access the FinCEN Query system (see FinCEN report) as the system of 

record for Bank Secrecy Act (BSA) data.

(B) A thorough description of the data mining technology that is being used or will be used, 

including the basis for determining whether a particular pattern or anomaly is indicative 

of terrorist or criminal activity
28

Reveal, IDA, and LCA do not provide IRS with the ability to determine indicators of terrorist or 

criminal activity. Special agents and investigative analysts use “canned queries” based on 

experience. Agents and analysts determine indicators of fraudulent activity based on previous 

successful investigations of money laundering, counterterrorism, and BSA violations. 

W&I employees use RRP and EFDS to identity potentially fraudulent, noncompliant, and 

identity theft activity. IRS-CI uses the fraudulent tax returns identified by W&I as a basis for its 

criminal investigations. Paper refund returns come to EFDS from the Generalized Mainline 

Framework (GMF) and Questionable Refund Program. Paper returns come into RRP via 

multiple feeds from GMF. This allows W&I and SDC employees to review those returns for 

suspicious activities. 

EFDS employs a data mining technology called IBM SPSS Modeler. Using this tool, EFDS 

creates rule sets using a standard built-in algorithm called C5.0. Using examples of current and 

prior year verified fraud and non-fraud data, the machine-learning model discerns patterns or 

rules indicative of fraud. The output of the model is a score where a higher score (in the range of 

0.0 to 1.0) represents a higher risk or a higher likelihood of a return being fraudulent. 

If a return meets designated score tolerances and other criteria, W&I and IRS-CI personnel 

examine the return for fraudulent activity. Once a return is verified to be false via screening, 

Taxpayer Protection Program authentication and/or the wage verification process, the fraudulent 

returns are added via EFDS systemically or by W&I and CI-IRS users to the Scheme Tracking 

and Retrieval System (STARS) component. IRS-CI investigative analysts review the returns in 

STARS to find possible schemes, or fraudulent patterns, which may result in a referral to a CI 

field office for investigation.

RRP employs multiple technologies for data mining activities. Each of these technologies use 

current and prior year examples of identity theft (IDT), non-IDT tax fraud, and non-fraud to 

develop supervised models, unsupervised models, rules, and network analytics:

 SAS – RRP uses SAS as the workbench for developing and evaluating supervised and 

unsupervised models as well as for data exploration activities. RRP uses multiple SAS 

machine learning algorithms (e.g., decision trees, neural networks, logistic regression) to 

uncover patterns in the data associated with fraud. RRP also includes components of 

SAS’ High Performing Analytics (e.g., SAS Grid, SAS in-database analytics) to develop 

and deploy models with greater complexity than what could be built on a traditional 

infrastructure. Greater complexity allows RRP models to display greater accuracy and 

robustness. Supervised models produce a score from 0.000 to 1.000 where a higher score 

represents a higher likelihood of a return being fraud.

 Greenplum Data Computing Appliance (DCA) – All RRP models are deployed and run 

directly in the database. Deploying models directly to the database removes the network 

latency required to move data to a separate application tier server containing the models. 

Moreover, the Greenplum DCA provides massively parallel processing capabilities 

across multiple segment servers. In addition to models developed using SAS, RRP also 

develops models in the form of custom user-defined functions in the Greenplum DCA. 

o RRP’s network analytics tool – Linked Return Analysis (LRA) – uses multiple 

custom built Greenplum functions to link returns that display common, suspicious 

characteristics.
29

o RRP builds “identity theft filters” using Greenplum functions. These functions 

combine the outputs of RRP models, rules and LRA to flag suspicious cases of 

identity theft treatment

 FICO Blaze Advisor (FICO BA) – RRP builds and maintains business rules using FICO 

Blaze Advisor. FICO BA provides transparency into the logic that drives business 

decisions. FICO BA houses the logic that drives RRP’s Systemic Verification process –

the rule logic that matches taxpayer submitted Income Documents (IDOCs) to the 

document submitted by withholding parties (e.g., employer submitted W-2s containing 

income and withholding information).

(C) A thorough description of the data sources that are being or will be used 

The IRS-CI applications Reveal, IDA and LCA leverage the following data sources. 

 Taxpayer: The source is the electronically filed return (as transmitted through the MeF or 

a paper filed tax return. 

 Employers/Payers: Information from employers/payers captured on various forms as 

stored in the Information Returns Master File (IRMF).

 Other Treasury sources: BSA data provided by FinCEN, Specially Designated 

Nationals’ data provided by the Office of Foreign Assets Control.

 Other IRS sources: Tax Exempt Organizations data, Voluntary Disclosures, Criminal 

Investigations data.

The EFDS and RRP application leverages the following data sources.

 Taxpayer: The source is the electronically filed return (as transmitted through the MeF) 

or a paper filed tax return. EFDS and RRP also load taxpayer data contained on the IRS 

Master File.

 Employers/Payers: Information from employers/payers captured on Form W-2 and/or 

form 1099 as stored in the IRMF.

 Other federal agencies: Federal Bureau of Prisons for prisoner information; BSA data;

HHS Services for information on new hires; Social Security Administration for National 

Accounts Profile data for dates of births and deaths.

 State and local agencies: All states and the District of Columbia prisons deliver 

prisoner-listing information annually to IRS-W&I in electronic format.

(D)An assessment of the efficacy or likely efficacy of the data mining activity in providing 

accurate information consistent with, and valuable to, the stated goals and plans for the 

use or development of the data mining activity

The data uncovered during the query searches are only leads and require additional investigative 

steps for quality verification. There is no empirical data on the efficacy of searches by the 

Reveal, IDA and LCA applications. 

The efficacy of the data mining on EFDS can be measured in terms of fraud detection. A key 

overall measure of efficacy is “hit: scan,” which represents the number of returns selected for 

verification that, upon inspection by IRS employees, are found to be fraudulent. The overall 
30

“hit: scan” for the EFDS system is 1:1.5 for FY 2015. This means that the data mining program 

accurately predicts fraudulent returns in 10 of 15 cases.

The efficacy of RRP can be measured in terms of identity theft detection. Two key metrics are 

used to assess RRP’s efficacy: lead generation and True Positive Rate. In 2015, RRP generated 

over 785,000 identity theft leads at a true positive rate of 81.4%. This means that over 8 out of 

every 10 returns flagged as IDT by RRP never receive a legitimate taxpayer identity 

authentication via the IRS’ web, phone, or in-person authentication processes.

The efficacy of the FinCEN Query system is discussed in Section (D) of that report.

(E) An assessment of the impact, or likely impact, of the implementation of the data mining 

activity on the privacy and civil liberties of individuals, including a thorough description of 

the actions that are or will be taken with regard to the property, privacy, or other rights or 

privileges of any individual or individuals as a result of implementing the data mining 

activity

Once evidence of fraud is discovered, laws and administrative procedures, policies, and controls 

govern the ensuing actions. Reveal, IDA and LCA applications use personally identifiable 

information (PII) for pattern matching, but the results of a query are used for further 

investigation. IRS-CI follows the IRS security and privacy IRM standards and regulations for

the use and protection of PII.

The impact or likely impact of the EFDS and RRP data mining activities on privacy and civil 

liberties of individuals is governed by 26 U.S.C. § 6103, which provides general rules of 

maintaining confidentiality and permissible disclosures. Under this statute, all taxpayer data are 

private and confidential and protected from disclosure except under specific conditions. 

Additional laws provide for civil and criminal penalties for any unauthorized disclosure of 

taxpayer data. The penalties include (1) felony for the willful unauthorized disclosure of tax 

information, (2) misdemeanor for the unauthorized inspection of tax information, and (3) civil 

cause of action for the taxpayer whose information has been inspected or disclosed in a manner 

not authorized by Section 6103. The CI Special Agents receive periodic training on maximum 

sentencing and penalties for each criminal violation. Access to the system requires a background 

check. IRS has a system, Online 5081, that governs program access authorization.

Further, EFDS and RRP data mining activities, including its machine learning and scoring 

process, do not use any PII in determining whether a return is likely to be fraudulent. Scoring 

occurs on the characteristics of the return in question, not on the PII. When performing 

investigative techniques, PII associated with the return is pulled in to assist in validating the 

return was filed using the taxpayer account in question and to determine venue of the 

investigation. 

The tax returns that IRS-CI reviews are the subjects of criminal investigations and actions based 

on tax laws, policies, and criminal procedures. Other tax returns are subjected to IRS civil 

treatments and examination procedures that provide for due process and redress procedures 

through taxpayer notification, appeals, and tax court options.
31

(F) A list and analysis of the laws and regulations that govern the information being collected, 

reviewed, gathered, analyzed, or used in the data mining activity.

The use of all tax data is governed by 26 U.S.C. § 6103. Subsection (a) sets out the general rule 

of confidentiality. Subsection (b) sets forth definitions of terms commonly used throughout 

Section 6103. Subsections (c) through (o) of Section 6103 contain exceptions to the general rule 

of confidentiality. These subsections permit disclosures as described generally below: 

 Section 6103(c) – Disclosures to taxpayer’s designees (consent); 

 Section 6103(d) – Disclosures to state tax officials; 

 Section 6103(e) – Disclosures to the taxpayer and persons having a material interest; 

 Section 6103(f) – Disclosures to committees of Congress; 

 Section 6103(g) – Disclosures to the President and White House; 

 Section 6103(h) – Disclosures to Federal employees and the courts for tax 

administration purposes; 

 Section 6103(i) – Disclosures to Federal employees for non-tax criminal law 

enforcement purposes and to combat terrorism, as well as the Government 

Accountability Office; 

 Section 6103(j) – Disclosures for statistical purposes; 

 Section 6103(k) – Disclosures for certain miscellaneous tax administration purposes; 

 Section 6103(l) – Disclosures for purposes other than tax administration; 

 Section 6103(m) – Disclosures of taxpayer identity information (generally for Federal 

debt collection purposes); 

 Section 6103(n) – Disclosures to contractors for tax administration purposes; and

 Section 6103(o) – Disclosures with respect to wagering excise taxes. 

In addition to disclosures permitted under the provisions of Section 6103, other provisions of the 

Code also authorize disclosure of tax information. For example, Section 6104 authorizes 

disclosure of certain tax information regarding tax-exempt organizations, trusts claiming 

charitable deductions, and qualified pension plans. Section 6110 authorizes disclosure of certain 

written determinations and their background files. 

(G)A thorough discussion of the policies, procedures, and guidelines that are in place or that 

are to be developed and applied in the use of such data mining activity in order to:

(i) protect the privacy and due process rights of individuals, such as redress procedures.

All tax information is protected as required in 26 U.S.C. § 6103 (see E and F above). All 

employees who interact with tax return and other protected information are required to undergo 

yearly refresher training that details their responsibilities with respect to information protection 

and disclosure. In addition to covering 26 U.S.C. § 6103 disclosure provisions, this training 

module also includes information on the Privacy Act, E-Government Act, Freedom of 

Information Act, and policies related to protecting PII and other sensitive information. The use 

of BSA information is strictly controlled under the statute that directs its collection.

The data uncovered during query in Reveal, IDA and LCA applications are used as a lead and 

requires additional investigative steps to verify the quality of the information, as discussed 
32

above. IRS maintains an audit trail on all users’ access to case data. In addition, a full system 

log is maintained for any system level activities, including new data loads to the IDA and LCA 

application.

Neither EFDS nor RRP determines whether a return is fraudulent or whether a person is going to 

be subject to criminal prosecution. Once fraud is suspected, laws and administrative procedures, 

policies, and controls govern criminal investigations or any other ensuing actions. Due process 

is provided during any ensuing criminal investigation or civil action.

(ii) ensure that only accurate and complete information is collected, reviewed, analyzed, or 

used and guard against any harmful consequences of potential inaccuracies.

An individual/entity self-reports tax data when submitting the information to the government. 

FinCEN’s data are gathered from information compiled by the reporter based on information 

provided by their customer or based on the reporter’s personal experience. Investigators 

scrutinize the Suspicious Activity Reports filed by the subject companies and request grand jury 

subpoenas for the underlying documentation. The supporting records are examined and 

individuals of interest are identified. 

The Reveal, IDA and LCA applications are not the authoritative owners of data. However, the 

data is used for investigative analysis purposes under the IRS Internal Revenue Manual (IRM) 

standards and guidelines. The data uncovered during query searches are only used as a lead and 

require additional investigative steps to verify the quality of the information. Therefore, IRS-CI 

uses this data for generating leads and the special agents verify this information through further 

investigative work. 

The tax return information and other information stored in EFDS and RRP used for data mining 

are based on outside data sources. The only data generated directly in EFDS are the processing 

steps and the results of examinations of possibly fraudulent returns. The only data generated in 

RRP are for system monitoring and diagnostics. Through a series of test case procedures 

executed through Application Qualification Testing (AQT), Systems Acceptability Testing 

(SAT), and Final Integration Test (FIT), the IRS verifies that the data loaded into EFDS and RRP 

match the data from the input source and that the system accurately displays the data in the 

EFDS and RRP end user applications. AQT, SAT, and FIT perform verification with each 

release of the system. IRS applications are required to have internal auditing capabilities. The 

internal audits track user access and queries performed with checks against misuse. 
33

TTB DATA MINING ACTIVITIES

(A) A thorough description of the data mining activity, its goals, and, where appropriate, the 

target dates for the deployment of the data mining activity.

TTB’s analytics program performs three types of activities that, together, qualify as data mining 

as defined by the Federal Agency Data Mining Reporting Act of 2007:

 Queries of commercial transactions recorded by tax and trade databases maintained by 

TTB and other federal agencies;

 Searches of public records and law enforcement databases for indications of illicit 

dealings; and,

 Link analysis of connections between businesses and individuals.

TTB conduct’s these activities primarily for the purpose of discovering or locating patterns or 

anomalies indicative of activity by individuals or businesses that violate federal regulations 

administered by TTB. The data used in these activities is, for the most part, gathered with queries 

of registered individuals or businesses. However, subsequent analysis of the data is primarily 

pattern-based, seeking anomalies in compiled records. The data mining activities also include 

some queries and searches that are solely pattern-based, e.g., queries of all tobacco product 

imports over a given time period. 

The goals of TTB’s data mining activity are to automate certain routine oversight processes, and 

improve detection of violations. The activity supports predictive models and business 

intelligence that identifies compliance risks and potential fraudulent or criminal activity that may 

be subject to further field review and action. TTB has predictive models in place that score the 

risk of tax diversion in the tobacco industry, and evaluate businesses seeking a TTB permit.

TTB also compiles business intelligence that highlights patterns in tax and trade data. The 

models and business intelligence are in regular use today with improvements and expansions 

planned for fiscal year 2016. 

(B) A thorough description of the data mining technology that is being used or will be used 

including the basis for determining whether a particular pattern or anomaly is indicative 

of terrorist or criminal activity.

TTB uses commercially available data mining technologies to access and analyze information. 

The experience of intelligence analysts and investigators provides the basis for determining 

whether a particular pattern or anomaly is indicative of violations. The ability to identify patterns 

and anomalies is supplemented with statistical analysis and machine learning techniques. 

Most data mining is conducted with a combination of SAS statistical analysis software and 

Oracle relational database systems. Data are retrieved with SAS data step programming and/or 

Structured Query Language (SQL) queries. Data fields are transformed with procedures that 

aggregate, correlate, cluster, and otherwise simplify available variables. The procedures include 

parsing unstructured text for entity extraction and topic modeling to find similarities between 

text documents. 

Once data are collected and transformed, predictive models use the data to estimate the expected 

violation risk of a particular individual, business, or incident. The estimates today are primarily 
34

based on business rules and templates defined by experienced analysts (and implemented in the 

SAS programming language). Analysts are also discovering new patterns based on analysis of 

historical violations using machine learning classification algorithms such as logistic regression, 

decision trees, and neural networks. Patterns identified through these methods are vetted with 

experienced analysts and evaluated against randomized test cases. 

(C) A thorough description of the data sources that are being or will be used.

TTB uses data from its own databases, the databases of other federal agencies, and commercial 

data providers. The data sources include:

Internal Data:

1) Integrated Revenue Information System (IRIS) – tax data submitted by TTB industry 

members;

2) Permits Online (PONL) –application data from businesses requesting a TTB permit; 

3) AutoAudit – data from TTB’s audits and investigations; 

External Data:

4) Automated Commercial Environment (ACE) / Automated Commercial System (ACS) / 

Automated Export System (AES) – data regarding imports and exports of products regulated 

by TTB; 

5) Census Export Data – data regarding exports of products regulated by TTB;

6) Financial Crimes Enforcement Network Query (FinCEN Query) – data submitted in 

compliance with the Bank Secrecy Act transcripts such as Suspicious Activity Reports 

(SARs), Currency Transaction Reports (CTRs), etc.; and,

7) LexisNexis Accurint – public records data of court proceedings (including some criminal 

cases), property holdings, licenses, and registrations. 

These databases are either in use today or being evaluated for inclusion in predictive models. 

Further integration of the sources is ongoing, as is identification of new data sources.

(D) An assessment of the efficacy or likely efficacy of the data mining activity in providing 

accurate information consistent with, and valuable to, the stated goals and plans for the 

use or development of the data mining activity.

TTB’s data mining activity is valuable for automating certain routine oversight processes, and 

improving detection of compliance violations. Initial evaluations indicate that data mining 

enables more regular oversight and produces indicators for further field review, including 

investigation and audit. This evaluation is continuing and generating new improvements as the 

data mining activity matures. 

The data mining activity, models and business intelligence supported by the activity have been 

effective at helping to automate oversight processes. Predictive models automatically screen 

approximately 2,000 original permit applications, 2,000 active tobacco businesses, and 2,100 
35

active distilled spirits manufacturers. The models verify information and monitor patterns in 

operations, tax payments, and international trade activity. The models also automatically monitor 

financial and trade databases for indications of activity by unregistered businesses. Automating 

basic screens enables TTB to provide oversight to a wider section of its regulated industries. 

The ability of predictive models to detect compliance violations depends greatly on the accuracy 

of the source data available for the models. Data quality and mining techniques continue to 

improve with increased use and scrutiny over data. Predictive models that rely on data mining 

activity are showing promise in detecting violations, though the evaluation is still ongoing. The 

Tobacco Importer Risk Model (TIRM) has been in use for three years and demonstrated 

precision of approximately 0.60, i.e. 6 out of 10 cases recommended by the model result in the 

detection of previously undisclosed tax liability that also provided a positive return on 

investment. Initial evaluations of the Tobacco Diversion Model (TDM) show precision measures 

above 0.80, i.e. 8 out of 10 leads uncover a compliance issue though not necessarily an 

undisclosed tax liability. The Alcohol Diversion Risk Model, which focuses on high risk distilled 

spirits plant activity, is currently being tested and refined to determine tolerance thresholds. 

Evaluation of these and other models will continue as part of TTB’s ongoing effort to improve 

model accuracy. 

(E) An assessment of the impact, or likely impact, of the implementation of the data mining 

activity on the privacy and civil liberties of individuals, including a thorough description of 

the actions that are or will be taken with regard to the property, privacy, or other rights or 

privileges of any individual or individuals as a result of implementing the data mining 

activity.

TTB’s data mining activity has little impact on the privacy and civil liberties of individuals. 

Insights gained from the activity only result in actions against property, or the privilege to 

operate in regulated industries, after thorough review by experienced specialists with oversight 

authorities mandated by federal laws and regulations. The data sources mined are also limited to 

include only tax records, commercial records, and law enforcement records authorized for use in 

oversight and enforcement. 

Any data concerning individuals or businesses is vigorously protected against unauthorized use 

and disclosure. Policies and procedures prohibit the search of any database for reasons other than 

providing authorized oversight or enforcement. In cases when patterns in data are thought to be 

indicative of compliance issues the data and circumstances are carefully reviewed by 

experienced staff before any adverse action is taken. TTB also continues to protect data against 

any unauthorized disclosure through all investigation and enforcement actions. 

Data gathered in data mining activities is considered private and confidential and protected from 

disclosure by 26 U.S.C. § 6103. TTB governs its use of this data consistent with the authorities 

described in the subsections of 26 U.S.C. § 6103. Privacy protections are further assured by 

additional laws that provide for civil and criminal penalties for any unauthorized disclosure of 

taxpayer data. There are criminal penalties including: (1) felony for the willful unauthorized 

disclosure of tax information; (2) misdemeanor for the unauthorized inspection of tax 

information; and (3) civil cause of action for the taxpayer whose information has been inspected 

or disclosed in a manner not authorized by Section 6103.
36

(F) A list and analysis of the laws and regulations that govern the information being collected, 

reviewed, gathered, analyzed, or used in the data mining activity.

TTB administers the provisions of the Internal Revenue Code (IRC) relating to distilled spirits, 

wine, and beer (26 U.S.C. Chapter 51), firearms and ammunition excise taxes (26 U.S.C. 

sections 4181, 4182, and related portions of chapter 32), and the general rules of tax procedure 

with respect to these commodities (including related criminal provisions at 26 U.S.C. Chapters 

68 and 75). In addition, TTB administers the Federal Alcohol Administration Act (27 U.S.C. 

chapter 8, subchapter I), which covers basic permits, unfair trade practices, and labeling and 

advertising of alcohol beverages; the Alcoholic Beverage Labeling Act of 1988 (27 U.S.C. 

chapter 8, subchapter II), which requires a specific “Government Warning” statement on alcohol 

beverage labels; and the Webb-Kenyon Act (27 U.S.C. sections 122-122b), which prohibits the 

shipment of liquor into a state in violation of state law.

The IRC establishes qualification criteria to engage in the businesses relating to manufacturing 

and importing or exporting tobacco products, and manufacturing or importing processed tobacco, 

and require that persons obtain permits to engage in these activities. (26 U.S.C. § 5713). A 

permit qualification requirement also applies to the production of distilled spirits and wine, as 

well as to the wholesaling and importation of all beverage alcohol products. (26 U.S.C. §§ 

5171(c) and (d), 5271, see also 27 U.S.C. §§ 201 et seq.) 

Through an agreement with FinCEN, dated May 3, 2005, TTB is granted direct electronic access 

to data collected pursuant to provisions of the Bank Secrecy Act, 31. U.S.C. §5311 et seq. The 

direct access is granted for tax or regulatory purposes relevant to the mission of TTB.

The authority to collect excise taxes on imported alcohol and tobacco products was originally 

retained by the Secretary of the Treasury through the Homeland Security Act of 2002. See 6 

U.S.C. §§ 212 and 215. Through Treasury Order 100–16, the Secretary of the Treasury 

delegates authority over “Customs revenue functions” to the Secretary of the Department of 

Homeland Security. “Customs revenue functions” are defined by the Homeland Security Act of 

2002 as “assessing and collecting customs duties (including antidumping and countervailing 

duties and duties imposed under safeguard provisions), excise taxes, fees, and penalties due on 

imported merchandise, including classifying and valuing merchandise for purposes of such 

assessment.” 6 U.S.C. § 215(a) (1).

TTB is authorized pursuant to the Homeland Security Act of 2002, Pub. L. 107-296; Executive 

Order 13439, July 18, 2007; the Internal Revenue Code of 1986 (IRC); and the Federal Alcohol 

Administration Act, 27 U.S.C. chapter 8 (FAA Act) to access data within Customs and Border 

Protection (CBP) data systems necessary to fulfill its statutory mission. TTB is working in 

conjunction with CBP to fulfill its statutory mission as it relates to imported products subject to 

various taxes and to ensure taxpayers understand their tax responsibilities related to these 

products. Cooperative efforts across Federal agency lines will accommodate the collection of 

data as it relates to imported commodities subject to Federal taxes including but not limited to 

retail, excise, manufacturers, and environmental taxes. 

When the data analyzed by the models consists of taxpayer information, the use of all tax related 

data is governed by 26 U.S.C. § 6103. Subsection (a) sets out the general rule of confidentiality. 

Subsection (b) sets forth definitions of terms commonly used throughout Section 6103. 
37

Subsections (c) through (o) of Section 6103 contain exceptions to the general rule of 

confidentiality. The use of confidential commercial, financial or trades secrets information is 

governed by the Trade Secrets Act, 18 U.S.C. § 1905, which prohibits the unlawful disclosure of 

this information by any federal official, employee, or contractor. 

(G) A thorough discussion of the policies, procedures, and guidelines that are in place or that 

are to be developed and applied in the use of such data mining activity in order to:

(i) protect the privacy and due process rights of individuals, such as redress 

procedures.

All of TTB’s information collections are subject to the OMB review process and any forms that 

request personal information include a Privacy Act Statement. In addition, TTB’s privacy policy 

is posted on ttb.gov (http://www.ttb.gov/about/privacy_policy.shtml) and is referenced on TTB’s 

Online Applications. TTB’s systems of record notice can be found in the Federal Register at 

http://www.gpo.gov/fdsys/pkg/FR-2011-12-01/pdf/2011-30898.pdf35.

TTB data mining activities do not determine whether a person or entity will be subject to 

administrative enforcement action or criminal prosecution. Any audit or investigation that is 

initiated based, in part, upon data from the activities are governed by the laws, administrative 

procedures, policies and controls that govern criminal investigations or any other ensuing 

actions. 

Information generated and accessed by the data mining activities is protected by internal controls 

that limit access to persons whose official duties require inspection of such information for tax 

administration purposes. The information is further protected by 26 U.S.C. § 6103 governing the 

confidentiality of returns and return information and the Trade Secrets Act, 18 U.S.C. § 1905, 

which protects confidential commercial, financial, or trades secrets information collected by the 

federal government. 

TTB notifies system operators of the requirements and legal consequences of accessing 

predictive models in production. The message states: 

26 U.S.C. 6103 Data Warning. Information contained in this report is tax 

return information protected from disclosure by 26 U.S.C. 6103. By accessing 

this report, you hereby certify that your official duties require you to inspect 

such information for tax administration purposes. 

Users of predictive models in production receive training in the proper handling of information. 

Users receive system demonstrations of the model and have access to a user guide. The same 

process will be followed for future models when successful testing and evaluation has been 

completed. Field Operations staff receive 26 U.S.C. § 6103 and disclosure training. In addition, 

all TTB employees complete the annual Privacy Awareness and Cyber Security Awareness 

training. Finally, system sponsors and IT staff supporting development, maintenance, and 

operations of IT systems are required to take additional specialized security training each year.
38

(ii) ensure that only accurate and complete information is collected, reviewed, analyzed, 

or used and guard against any harmful consequences of potential inaccuracies.

The data mining activities rely on information collected through systems that have their own 

accuracy related checks and balances. TTB does not rely solely on information gathered through 

predictive models to take any adverse action against any individual or entity. Rather, the models 

are the first step in gathering data and this information is verified through subsequent research 

and audits of companies and importers before any adverse action is taken. 

TTB documents and manages all data sets associated with TTB’s systems using the TTB 

Systems Development Life Cycle (SDLC). Checks and balances are inherent to the data 

correction process ensuring different teams handle different steps of the effort and include 

oversight by the Office of the Chief Information Officer Quality Assurance (OCIO QA) Team. 

When the system owner identifies inconsistencies with data, TTB’s OCIO QA Team may initiate 

a data correction. All changes are documented via the Request for Change process managed by 

the Configuration Management Team and work orders track the correction through its lifecycle 

(from request to development and through implementation), which includes confirmation of 

successful completion by the system owner. The process includes specific identification of the 

data to be corrected along with rationale for the change. SDLC artifacts (e.g., database scripts) 

supporting data corrections conform to Data Management (DM) standards. The Software 

Maintenance Team verifies analysis, development, and testing through a quality review process 

conducted by the DM Team to ensure the data correction is thoroughly documented. Once the 

DM Team has approved the data correction, the Operations Team executes the correction and the 

system owner verifies the correction. 

The Memorandum of Understanding with CBP contains language that both parties will notify 

one another if either agency discovers data issues. Also, the ACS and ACE data import 

processes in support of the Tobacco Importer Risk Model were documented and tested using 

TTB’s SDLC. For all available governmental data sources, users must sign a non-disclosure 

agreement before receiving access.

CONCLUSION

The Department of the Treasury is pleased to provide to Congress its Annual Privacy and Data 

Mining Reports for Fiscal Year 2015. OPTR has reviewed the activities and programs described 

in this combined report and continues to work closely with all Treasury bureaus and offices to 

protect individual privacy and civil liberties in all Treasury activities.