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HELPING CONSUMERS OBTAIN

THE CREDIT THEY DESERVE

HEARING

BEFORE THE

SUBCOMMITTEE ON 

FINANCIAL INSTITUTIONS AND CONSUMER CREDIT

OF THE

COMMITTEE ON FINANCIAL SERVICES

U.S. HOUSE OF REPRESENTATIVES

ONE HUNDRED NINTH CONGRESS

FIRST SESSION

MAY 12, 2005

Printed for the use of the Committee on Financial Services

Serial No. 109–29

(

(II)

HOUSE COMMITTEE ON FINANCIAL SERVICES 

MICHAEL G. OXLEY, Ohio, Chairman

JAMES A. LEACH, Iowa 

RICHARD H. BAKER, Louisiana 

DEBORAH PRYCE, Ohio 

SPENCER BACHUS, Alabama 

MICHAEL N. CASTLE, Delaware 

PETER T. KING, New York 

EDWARD R. ROYCE, California 

FRANK D. LUCAS, Oklahoma 

ROBERT W. NEY, Ohio 

SUE W. KELLY, New York, Vice Chair 

RON PAUL, Texas 

PAUL E. GILLMOR, Ohio 

JIM RYUN, Kansas 

STEVEN C. LATOURETTE, Ohio 

DONALD A. MANZULLO, Illinois 

WALTER B. JONES, JR., North Carolina 

JUDY BIGGERT, Illinois 

CHRISTOPHER SHAYS, Connecticut 

VITO FOSSELLA, New York 

GARY G. MILLER, California 

PATRICK J. TIBERI, Ohio 

MARK R. KENNEDY, Minnesota 

TOM FEENEY, Florida 

JEB HENSARLING, Texas 

SCOTT GARRETT, New Jersey 

GINNY BROWN-WAITE, Florida 

J. GRESHAM BARRETT, South Carolina 

KATHERINE HARRIS, Florida 

RICK RENZI, Arizona 

JIM GERLACH, Pennsylvania 

STEVAN PEARCE, New Mexico 

RANDY NEUGEBAUER, Texas 

TOM PRICE, Georgia 

MICHAEL G. FITZPATRICK, Pennsylvania 

GEOFF DAVIS, Kentucky 

PATRICK T. MCHENRY, North Carolina 

BARNEY FRANK, Massachusetts 

PAUL E. KANJORSKI, Pennsylvania 

MAXINE WATERS, California 

CAROLYN B. MALONEY, New York 

LUIS V. GUTIERREZ, Illinois 

NYDIA M. VELA ́ ZQUEZ, New York 

MELVIN L. WATT, North Carolina 

GARY L. ACKERMAN, New York 

DARLENE HOOLEY, Oregon 

JULIA CARSON, Indiana 

BRAD SHERMAN, California 

GREGORY W. MEEKS, New York 

BARBARA LEE, California 

DENNIS MOORE, Kansas 

MICHAEL E. CAPUANO, Massachusetts 

HAROLD E. FORD, JR., Tennessee 

RUBE ́ N HINOJOSA, Texas 

JOSEPH CROWLEY, New York 

WM. LACY CLAY, Missouri 

STEVE ISRAEL, New York 

CAROLYN MCCARTHY, New York 

JOE BACA, California 

JIM MATHESON, Utah 

STEPHEN F. LYNCH, Massachusetts 

BRAD MILLER, North Carolina 

DAVID SCOTT, Georgia 

ARTUR DAVIS, Alabama 

AL GREEN, Texas 

EMANUEL CLEAVER, Missouri 

MELISSA L. BEAN, Illinois 

DEBBIE WASSERMAN SCHULTZ, Florida 

GWEN MOORE, Wisconsin, 

BERNARD SANDERS, Vermont

Robert U. Foster, III, Staff Director 

(III)

SUBCOMMITTEE ON FINANCIAL INSTITUTIONS AND CONSUMER CREDIT

SPENCER BACHUS, Alabama, Chairman

WALTER B. JONES, JR., North Carolina, 

Vice Chairman 

RICHARD H. BAKER, Louisiana 

MICHAEL N. CASTLE, Delaware 

EDWARD R. ROYCE, California 

FRANK D. LUCAS, Oklahoma 

SUE W. KELLY, New York 

RON PAUL, Texas 

PAUL E. GILLMOR, Ohio 

JIM RYUN, Kansas 

STEVEN C. LATOURETTE, Ohio 

JUDY BIGGERT, Illinois 

VITO FOSSELLA, New York 

GARY G. MILLER, California 

PATRICK J. TIBERI, Ohio 

TOM FEENEY, Florida 

JEB HENSARLING, Texas 

SCOTT GARRETT, New Jersey 

GINNY BROWN-WAITE, Florida 

J. GRESHAM BARRETT, South Carolina 

RICK RENZI, Arizona 

STEVAN PEARCE, New Mexico 

RANDY NEUGEBAUER, Texas 

TOM PRICE, Georgia 

PATRICK T. MCHENRY, North Carolina 

MICHAEL G. OXLEY, Ohio 

BERNARD SANDERS, Vermont 

CAROLYN B. MALONEY, New York 

MELVIN L. WATT, North Carolina 

GARY L. ACKERMAN, New York 

BRAD SHERMAN, California 

GREGORY W. MEEKS, New York 

LUIS V. GUTIERREZ, Illinois 

DENNIS MOORE, Kansas 

PAUL E. KANJORSKI, Pennsylvania 

MAXINE WATERS, California 

DARLENE HOOLEY, Oregon 

JULIA CARSON, Indiana 

HAROLD E. FORD, JR., Tennessee 

RUBE ́ N HINOJOSA, Texas 

JOSEPH CROWLEY, New York 

STEVE ISRAEL, New York 

CAROLYN MCCARTHY, New York 

JOE BACA, California 

AL GREEN, Texas 

GWEN MOORE, Wisconsin 

WM. LACY CLAY, Missouri 

JIM MATHESON, Utah 

BARNEY FRANK, Massachusetts 

(V)

C O N T E N T S 

Page 

Hearing held on: 

May 12, 2005 ..................................................................................................... 1

Appendix: 

May 12, 2005 ..................................................................................................... 41

WITNESSES 

THURSDAY, MAY 12, 2005

Catone, Mark, Senior Vice President, First American Credco ............................. 7

Nelson, Lisa, Vice President, Business Operations, Fair Isaac Corporation ...... 6

Saunders, Margot, Attorney, National Consumer Law Center ............................ 11

Thomas, Gwen, Senior Vice President, Consumer Real Estate, Bank of America .......................................................................................................................... 9

Turner, Michael, President and Senior Scholar, Information Policy Institute ... 13

APPENDIX 

Prepared statements: 

Oxley, Hon. Michael G. .................................................................................... 42

Bachus, Hon. Spencer ...................................................................................... 47

Castle, Hon. Michael N. ................................................................................... 51

Gillmor, Hon. Paul E. ....................................................................................... 52

LaTourette, Hon. Steven C. ............................................................................. 53

Catone, Mark ........................................................................................................... 55

Nelson, Lisa .............................................................................................................. 61

Saunders, Margot .................................................................................................... 72

Thomas, Gwen ......................................................................................................... 87

Turner, Michael ....................................................................................................... 92

ADDITIONAL MATERIAL SUBMITTED FOR THE RECORD

Castle, Hon. Michael N.: 

Community Financial Services Association, position paper ......................... 102

′′First American to Develop New Credit Scores′′, American Banker, October 14, 2003 ................................................................................................... 104

′′Pay Rent, Build Credit, Success Story′′, Center for Financial Services 

Innovation ...................................................................................................... 106

Catone, Mark: 

Response to questions from Hon. Barney Frank ........................................... 108

Response to questions from Hon. Luis V. Gutierrez and Hon. Deborah 

Pryce .............................................................................................................. 126

Nelson, Lisa: .............................................................................................................

Response to questions from Hon. Barney Frank ........................................... 130

Response to questions from Hon. Luis V. Gutierrez ...................................... 138

Thomas, Gwen: ........................................................................................................

Response to questions from Hon. Luis V. Gutierrez and Hon. Barney 

Frank ............................................................................................................. 139

Turner, Michael: ......................................................................................................

Response to questions from Hon. Luis V. Gutierrez ...................................... 141

(1)

HELPING CONSUMERS OBTAIN 

THE CREDIT THEY DESERVE 

Thursday, May 12, 2005

U.S. HOUSE OF REPRESENTATIVES, 

SUBCOMMITTEE ON FINANCIAL INSTITUTIONS

AND CONSUMER CREDIT, 

COMMITTEE ON FINANCIAL SERVICES, 

Washington, D.C. 

The subcommittee met, pursuant to call, at 10:03 a.m., in Room 

2128, Rayburn House Office Building, Hon. Spencer Bachus [chairman of the subcommittee] presiding. 

Present: Representatives Bachus, Castle, Ryun, Hensarling, 

Brown-Waite, Pearce, Neugebauer, McHenry, Sanders, Maloney, 

Watt, Sherman, Gutierrez, Moore of Kansas, Waters, Carson, Ford, 

Baca, Green, Moore of Wisconsin, and Clay. 

Chairman BACHUS. [Presiding.] The Subcommittee on Financial 

Institutions and Consumer Credit will come to order. 

Today we are holding a hearing entitled, ‘‘Helping Consumers 

Obtain the Credit They Deserve.’’

As we learned during our recent debates on the Fair Credit Reporting Act, a consumer’s credit history can play an important role 

in his or her ability to obtain credit, as well as the price of the 

credit offered. 

However, we also learned that many consumers who pay their 

bills on time may not have sufficient information in their credit reports demonstrating their credit worthiness. This is due to the fact 

that not all companies provide payment history information to 

credit bureaus. 

Today’s hearing will provide us a forum in which we can explore 

the type of information that may be valuable in the credit underwriting process, but that are underreported to credit bureaus. We 

may also identify any structural barriers that may hinder the reporting of such information. 

Generally, we want to learn more about how we can improve consumers’ credit options, especially for those consumers who are low 

or moderate income. 

This committee has demonstrated time and time again a dedication to ensuring that all American consumers maintain a level of 

access to financial services and products that is unrivaled anywhere in the world. Today’s hearing further demonstrates this commitment. 

I want to particularly thank Chairman Castle for requesting this 

hearing, and I commend him for his leadership in this area. 

2

Consumers in the United States have more ready access to lowcost credit than consumers anywhere else in the world. This is due 

in large part to public policies that support the pooling and sharing 

of consumer credit data. 

The availability to lenders of complete and accurate data on past 

consumer borrowing behavior is considered essential to an efficient 

credit market. 

Despite the enormous growth in the U.S. credit market, many 

consumers still experience difficulty obtaining adequate consumer 

credit because they have little or no credit history. 

I understand it is estimated that as many as 55 million Americans do not have sufficient credit history for a lender to accurately 

determine their true risk of default. 

Many of these consumers may be making timely payments on 

various monthly or contractual obligations. However, these payments are often going unreported to the credit reporting agencies. 

For example, many landlords do not report information to credit 

bureaus, so a renter’s credit history will not necessarily reflect the 

fact that the consumer is paying regularly. The same can be said 

for some utility companies, cable companies, and telecommunications companies. 

If a consumer does not have significant amounts of information 

in his credit report, that consumer is said to have a ‘‘thin file,’’ 

making it difficult for creditors to assess his credit worthiness. 

Consumers in low-and moderate-income households may be more 

likely to have thin files because they do not have mortgages or 

other forms of traditional credit that show up in credit reports. 

Therefore, a low-income renter may find himself in a vicious cycle 

of not having adequate low-cost credit available because he or she 

has not had access to credit in the past. 

We need to explore whether the information that could be provided by landlords, utilities, phone companies, cable companies and 

others to credit bureaus can be valuable in the underwriting process. For example, would a creditor be more likely to grant a mortgage to a consumer if the creditor knew that the consumer faithfully and diligently paid his or her phone bill each month? 

I also look forward to learning more about why certain types of 

companies do not report information to credit bureaus. Is it too expensive? Are there other barriers? Are there other motivations? Is 

there too much liability involved? 

It is my hope today’s hearing will allow us to explore ways in 

which the use of alternative data not currently reported to credit 

bureaus may benefit millions of Americans that either do not currently have a credit score or little information in their credit file. 

Let me again thank Mr. Castle for his leadership on this issue. 

He is strongly committed and I admire his dedication to ensuring 

that the underserved have access to the low-cost credit they need 

and deserve. 

The Chair now recognizes the ranking member of the subcommittee, Mr. Sanders, for any opening statement that he wishes 

to make. 

[The prepared statement of Hon. Spencer Bachus can be found 

on page 47 in the appendix.] 

3

Mr. SANDERS. Thank you, Mr. Chairman, and thanks for holding 

this important hearing. 

The title of our hearing is ‘‘Helping Consumers Obtain the Credit 

They Deserve.’’ I think the hearing title is very appropriate and important, but I would add a caveat. 

And that is, while we should be helping consumers obtain the affordable credit they deserve, the truth of the matter is that in too 

many instances these days, more and more consumers, whether 

they are college students without jobs, seniors on fixed incomes, 

low-and middle-income families, are gaining access to credit, but 

from predatory lenders, payday lenders, rent-to-own companies, 

used-car salesmen, subprime lenders, retailers, and credit card 

companies that they cannot afford. 

They are being ripped off. 

I think this committee has the obligation to deal with this reality 

that millions and millions of consumers—and I do not know the 

more gentle word to use, but the reality is they are being ripped 

off by sky-high fees and outrageous interest rates. I think people 

all over this country understand that. 

Let’s just take a look at credit cards. Each and every year, credit 

card companies put 5 billion applications in the mail to consumers. 

Mr. Chairman, do you know that 5 billion—I tell that to people 

and they cannot believe it. That is an astronomical number. But 5 

billion credit card applications go out. 

I have often stated I think my family receives about half of them, 

but that is apparently not the case. Your family may get the other 

half. I do not know, but there are a lot of them. 

Consumers are now over $2 trillion in debt, while for 5 consecutive years in a row credit card companies made record-breaking 

profits, and their CEOs in some cases earned hundreds of millions 

of dollars in compensation. 

I think, Mr. Chairman, this is an issue we should be focusing on. 

Credit card companies alone collected over $21 billion in fees last 

year, compared to only $7.3 billion in 1994. So the whole issue of 

fees and the kinds of very high fees that they are charging is something this committee, in my view, should look at. 

Revenue from late and penalty fees has jumped from $1.7 billion 

in 1996 to an amazing $11.7 billion today. Over the past 8 years, 

late fees have risen from $10 to as high as $39, and experts are 

predicting that late fees could balloon to as high as $50 this year. 

Today, if consumers are even 1 hour late on credit card bills, they 

will get slapped with as much as a $39 late fee and a penalty interest rate as high as 29 percent. 

Predatory lending abuses cost consumers over $9 billion a year. 

Mr. Chairman, as you may know, I am not a great fan of Newt 

Gingrich, but here is what his former aide and bankruptcy expert 

Robert R. Weed had to say about this subject in a front-page story 

that appeared in the Los Angeles Times. 

He said, ‘‘Most of the credit card companies that end up in bankruptcy proceedings have already made a profit from the companies 

that issued them. That is because people are paying so many fees 

that they have already paid more than was originally borrowed.’’

4

Mr. Chairman, as 1.6 million Americans filed for bankruptcy last 

year, many paid more in credit card fees than they originally borrowed in the first place. I think this has got to stop. 

To address these concerns, I have introduced H.R. 1619, the 

Loan Shark Prevention Act, to protect consumers against predatory 

lending. 

Specifically, this legislation would, one, cap interest rates at 8 

percent above what the IRS charges income tax deadbeats. Currently, the cap would be about 14 percent, the same level that the 

Senate approved by a 74-to-19 vote in an amendment offered by 

then-Senator Al D’Amato in 1991. So we would like to do what Mr. 

D’Amato pushed for in 1991. Number two, it would cap bank and credit card fees at $15. 

Number three, ban the credit card interest rate bait and switch. 

As you know, Mr. Chairman, credit card companies are doubling or 

tripling interest rates on consumers even though they always paid 

their credit bills on time. I think all over America, people regard 

that as just extremely unfair. People paid their credit card bills on 

time. The companies should not be allowed to double or triple interest rates. 

Loan-sharking is an odious practice, whether it is performed by 

street corner thugs or the CEOs of large banks. Charging economically vulnerable Americans outrageous interest rates and fees is 

simply not acceptable. Amid all the recent political discussion over 

values, this certainly does not constitute moral behavior. 

So, Mr. Chairman, let us keep in mind when we are talking 

about helping consumers obtain the credit they deserve, that it 

must be affordable credit. 

I thank the Chair for holding this hearing, and I look forward to 

working with him. 

Chairman BACHUS. Thank you, Congressman Sanders. 

Obviously, some of those numbers are disturbing. It is certainly 

not good news for American consumers. 

Mr. Castle? 

Mr. CASTLE. Thank you very much, Chairman Bachus, for holding this hearing. I appreciate it. 

Also thanks to Ranking Member Sanders, Newt Gingrich’s new 

best friend, for being here today and his statements on this. He has 

always been interested in these subjects. 

I would also like to thank Chairman Oxley and Chairman Bachus for working with me on bringing this issue before the committee. Obviously, I believe it is an important one that warrants 

further discussion. 

Today, more people have access to credit than ever before. However, there are indications that some Americans—the young, minorities, and recent immigrants in particular—are not truly engaged in this competitive marketplace because they have little or 

no existing credit history for which lenders can assess risk and 

offer credit. 

As our witness Dr. Turner states in his recently released report, 

‘‘Giving Underserved Consumers Better Access to the Credit System,’’ there are an estimated 35 million to 50 million American borrowers who do not have credit scores, bank accounts, or whose files 

have too little information to be used in allocating credit. 

5

I feel there is information, such as rent and utility payments, 

that is not currently reported to the credit reporting agencies that 

could be helpful to consumers. 

For example, if an individual pays their rent on time each 

month, there is no transmission of this information to the credit reporting agencies. Conversely, individuals with mortgages do receive 

credit for paying their obligation on time, and this further adds to 

their credit score and history. 

Mr. Chairman, that raises a question. If people regularly meet 

their contractual obligations for a variety of services, why should 

that responsible behavior not be taken into account and used to the 

advantage of the consumer? 

Now it could be that the different payments I mentioned may not 

prove to be predictive of future behavior, and there may be State 

regulations related to certain utility providers that limits sharing 

of some of this information. I hope that our witnesses today will 

help us better understand the predictiveness and value of the data. 

I am pleased that a number of the panelists will discuss innovative products that the marketplace has developed to better serve 

the needs of all of our constituents, especially those with thin or 

no credit history, so they can have access to the best and most competitive offers of credit possible. 

I would just like to say, one of the goals here is to try to channel 

consumers into mainstream lending practices, if you will. I tremble 

sometimes to think of some of the borrowing practices that do go 

on, be it the use of the credit cards because they cannot get other 

credit, as Mr. Sanders has mentioned, or obviously some lenders 

who are out there trying to gouge when the regular lenders, if you 

will, could perhaps fill the same obligation to these individuals at 

rates which would be more appropriate. 

Let me just say this, because I think it is important, and that 

is that this hearing, as far as I am concerned, is not pursuant to 

legislation either introduced or to be introduced, so much as it is 

hopefully an evolving way of looking at consumers. 

Maybe at some point down the road some form of legislation will 

be needed. Maybe it will be needed at the State level. But the bottom line is that we are trying to shed a light on practices which 

a number of our witnesses here have started to watch and hopefully be able to serve a part of our population that is less served 

now. 

So I do very much, Mr. Chairman, appreciate the hearing, and 

I appreciate our witnesses being here. 

I yield back. 

[The prepared statement of Hon. Michael N. Castle can be found 

on page 51 in the appendix.] 

Chairman BACHUS. Thank you, Chairman Castle. 

At this time, I would like to introduce our witnesses. 

We have Ms. Lisa Nelson, who is vice president of business operations at Fair Isaac Corporation; Mr. Mark Catone, senior vice 

president, First American CREDCO; Ms. Gwen Thomas, senior vice 

president, Consumer Real Estate Branch, Bank of America; and 

Ms. Margot Saunders, attorney, National Consumer Law Center. 

You have testified before our committee previously, and we welcome you back. 

6

And Dr. Michael Turner, president and senior scholar at the Information Policy Institute. 

Thank you, Dr. Turner. 

At this time, we will have our opening statements. 

Ms. Nelson, if you would go first. Thank you. 

STATEMENT OF LISA NELSON, VICE PRESIDENT, BUSINESS 

OPERATIONS, FAIR ISAAC CORPORATION 

Ms. NELSON. Mr. Chairman and members of the committee, my 

name is Lisa Nelson. As you have just heard, I am vice president 

of business operations for Fair Isaac Credit Services, which is a 

wholly-owned subsidiary of Fair Isaac Corporation. 

Thank you for the opportunity to testify before you today about 

Fair Isaac’s leadership in the utilization of alternative credit data, 

specifically as it pertains to the launch of our new product, the expansion score. 

My comments highlight Fair Isaac’s written statement submitted 

to this committee earlier. 

Fair Isaac has been providing statistically based credit risk evaluation systems, commonly known as credit scores, since 1960. 

Today there are many different kinds of credit scores used by 

thousands of credit grantors. The most well-known are the broadbased credit scores that rely on data provided by the three national 

credit reporting agencies. 

We were asked to come before you today to describe how alternative credit data is being used within the lending community to 

provide access to consumers seeking credit to fulfill their dreams, 

which might include purchasing a home, obtaining a car loan, or 

simply getting a credit card. 

My remarks this morning focus on three areas. I will describe 

the important role of alternative credit data, the expansion score 

itself, and how they benefit the consumer. 

So, first, the role of alternative credit data. 

Credit risk scores are typically a three-digit number that rank 

order consumers according to their credit risk. These and other 

credit scores use traditional consumer credit data consisting of 

positive information, such as the consumer has made all payments 

on an existing account, and negative information, which might include the fact that the consumer has failed to repay a loan. 

The expansion score leverages alternative credit data rather than 

relying on the traditional data. It is similar to the classic scores in 

that it uses both positive and negative data and relies on technology upon which other FICO scores have been built. 

Fair Isaac is committed to finding and using the best nontraditional credit available from third-party data providers. To provide 

its service, we resell data we obtain from a number of consumer reporting agencies that collect that data from the furnishers. 

An example of the data that we use within the score includes deposit account records, check-writing behaviors, telephone payments, 

and purchase plan performance. 

You may ask, why have we chosen to resell this data rather than 

create and maintain our own database? This strategy ensures that 

the expansion score will use the best and most predictive alternative credit data available. 

7

Also, the expansion score has been designed to utilize new 

sources of credit data as they become available. This approach allows us to continue exploring business relationships with reputable 

consumer reporting agencies that aggregate this alternative credit 

data. 

Next, I would like to describe how the data is used within the 

FICO expansion score. 

Fair Isaac developed the expansion score using the same statistical approach used to develop the classic FICO score. In developing 

the expansion score, Fair Isaac analyzed anonymous alternative 

credit report data to statistically determine what factors are most 

predictive of future credit performance. 

Credit grantors who cannot obtain a traditional credit risk score 

for the consumer can now, for many people, obtain the expansion 

score. The same 300 to 850 score range is used by both the classic 

FICO and the expansion scores. Consumers with higher scores are 

predicted to be more likely to repay creditors as agreed. 

Early results show that lenders are able to score and underwrite 

a high proportion of the credit underserved market. Fair Isaac has 

analyzed data from several lenders in mortgage financing, automotive lending, and bank cards, and has observed scorability rates 

as high as 80 percent. This means that the expansion score was 

available for eight out of ten applicants for whom a traditional risk 

score was not available. 

So finally, what does this mean for consumers? 

As mentioned earlier, we are estimating there are roughly 50 

million credit underserved adults. This group is not only large, it 

is diverse. No one should assume that this group represents a 

subprime lending market. 

Expansion scores help create access to credit for those consumers 

that choose to seek it, while enabling lenders to make informed decisions. They also make credit more affordable by helping to automate the lending process. 

In conclusion, using alternative credit data in scoring improves 

access to credit for Americans who may have been turned away in 

the past and provides lenders with the necessary risk management 

tools to make good decisions. 

Thank you. 

[The prepared statement of Lisa Nelson can be found on page 61 

in the appendix.] 

Mr. CASTLE. [Presiding.] If I would truly be the Chair, the first 

thing we would do is change the size of the print on the placards 

in front of you because I cannot read them from here particularly 

well. 

But the next witness is Mr. Catone, who has already been introduced. He is recognized for 5 minutes. 

STATEMENT OF MARK CATONE, SENIOR VICE PRESIDENT, 

FIRST AMERICAN CREDCO 

Mr. CATONE. Thank you, chairman and distinguished members of 

the Financial Services Committee. My name is Mark F. Catone, 

senior vice president with the First American Corporation. 

Thank you for inviting us to testify today on the topic of helping 

consumers obtain the credit they deserve. 

8

The changing demographics of the population in the United 

States are reshaping the demand for housing, automobiles, and 

other goods and services. As a result, these changes are having a 

significant impact on the credit markets. 

According to many sources, including prior testimony to this committee, immigration has accounted for more than one-third of 

household growth since the 1990s. 

For the most part, the credit system in the United States has 

done a good job and continues to improve. No where else in the 

world today can you buy a car in under an hour or qualify for a 

home purchase online in the time it takes to fill out an application 

and click a button. 

One of the remaining barriers confronting immigrants, low-and 

moderate-income borrowers, and other consumers entering our 

credit system is the problematic issue of little or no credit information. 

There is no one answer or quick fix to this issue because of the 

existing built-up infrastructure of what we know as the credit reporting system, credit scoring, and what is referred to as nontraditional credit. 

There are, however, several areas we are active in that we believe should be examined and improved upon that will lead to more 

comprehensive solutions in the long run. 

There are four points. 

Make quality data available. The December 2004 report by FTC 

to Congress under section 318 and 319 of FACTA identifies data 

such as bill payment histories at utilities, telecommunication carriers, as well as rental payment histories, to be rich sources of data 

indicative of credit behavior. 

The limited reporting and the economics of collection of this data 

are problematic. Our company is very active in compiling and delivering what are referred to as nontraditional credit reports, which 

mortgage originators and investors accept and have a fairly welldefined standard. 

We collect this data on demand, working with the lender and the 

consumer. We apply what we believe to be best practices in due 

diligence and verification of the creditor information, resulting in 

the reduction of risk for the lender and ultimately to the investor. 

This is an on-demand service capability, and it is part of the solution today in the mortgage reporting industry. 

We also believe making additional utility, telecom, and related 

payment data available at credit bureaus or otherwise in an automated way will reduce the number of no-file and thin file reports. 

The second point—packaging of services in order to make the 

transaction economical. 

Again, the FTC report cited earlier also notes that the data identified is more expensive to collect and to add to the system and 

closes by noting that this makes ready solutions an economic challenge. In order to address this, the industry should look for ways 

to mitigate the expense of sourcing additional data. 

Our company offsets the higher expenses of compiling and 

verifying information for mortgage transactions, for example, by 

wrapping it into a fixed-cost comprehensive settlement package, efVerDate 0ct 09 2002 12:08 Jan 19, 2006 Jkt 000000 PO 00000 Frm 00014 Fmt 6633 Sfmt 6633 G:\DOCS\109.29 RODNEY
9

fectively mitigating the higher one-off cost of credit alone. This concept may make more sense for other loan types. 

Third point—we need to provide more education and guidance to 

the consumer. 

We saw early on that a full-service consumer help line is key to 

providing both education and issue resolution to consumers. When 

our customers access credit for the extension of a loan, we provide 

education to the consumer if issues arise or education is needed relative to the credit report provided. This is an expensive function to 

provide, but we believe it is necessary and other players should follow this lead. 

Finally—encourage the standardization of credit reporting for 

consumers who do not have credit reports, but can demonstrate financial competency. 

Most loans employing nontraditional data today are considered 

manual loans, which must be handled outside of technology, resulting in higher costs to the lender and the consumer. Standardization 

of nontraditional credit reporting, both in method and technology, 

will lead to overall lower costs as industry players build this into 

their systems and infrastructure. Ultimately, everyone benefits. 

That concludes my verbal testimony. I would like to thank the 

Chairman and the committee and welcome any questions. 

[The prepared statement of Mark Catone can be found on page 

55 in the appendix.] 

Mr. CASTLE. Thank you, Mr. Catone. 

Ms. Thomas is recognized for 5 minutes. 

STATEMENT OF GWEN THOMAS, SENIOR VICE PRESIDENT, 

CONSUMER REAL ESTATE, BANK OF AMERICA 

Ms. THOMAS. Good morning, chairman, Congressmen, and committee members. It is a pleasure to be here to talk on this topic. 

I am Gwen Thomas with Bank of America Consumer Real Estate, where my responsibility is to increase homeownership among 

low-income individuals of all colors and minority individuals across 

the United States. 

It is an honor to be here today to talk on this topic that is so 

critical for us to be able to make continued progress. 

My testimony will focus heavily on a lot of focus groups. We call 

it voice of the customers that we have done with individuals who 

have limited credit. I accepted the subcommittee’s invitation because I believe there are many opportunities and benefits that we 

can bring both to the customer and to the lenders and, thus, to the 

communities. 

Bank of America is the largest consumer bank in the United 

States, with more than 33 million customers, and that is about onethird of the households across the country. With that size, we have 

an obligation to make sure we meet the needs of the consumers we 

serve and, thus, utilizing nontraditional credit helps us toward 

achieving that goal. 

We have all seen the statistics on projected growth in the minority population, according to the U.S. Census Bureau. The Hispanic 

segment of growth will be a 188 percent increase by 2050; Asian, 

213 percent by 2050; and African-American, 71 percent by 2050. So 

those are significant increases. 

10

Unfortunately, a lot of these individuals will not have traditional 

credit or have thin files, which causes potential barriers to achieving homeownership. Of those segments, the majority of the firsttime homebuyers in the future will come from the various ethnic 

segments. 

Based on the focus groups we did, the interesting thing we heard 

from customers and potential customers was what was most important to them was getting a yes, getting it quickly, having a quick 

decision, be it yes or no, no surprises, privacy, and making sure 

that we understand that as part of the culture, cash is very much 

a part of the culture, especially with some of the part-time employed individuals who get paid in cash. 

While the traditional customer segments have some of the same 

desires about things that were important, the utilization of cash 

was the most unique piece for the segments that have the most significant growth. 

The bank has developed a lot of processes to meet the needs of 

the individuals with nontraditional credit. However, while we have 

those processes, they are highly manual, and they have the potential to sacrifice data integrity. Because of data validity issues, we 

only use the processes in a very limited way, and the processes are 

not currently automated for what we are using. 

Failing to use nontraditional credit can cause us to decline customers who have good credit and could qualify for a home. That is 

what our end goal is, is to get people into homes. Once we get them 

into homes, that is one of their best assets that helps them build 

wealth. 

One of the examples of a very successful program we have had 

is a program called Neighborhood Champions. That is a program 

we started 5 years ago focused on teachers. Now that program is 

extended it to firefighters, policemen, health care workers, and others that work in related fields. 

That program uses nontraditional credit, as well as undocumented income, meaning income where a person is paid by cash, 

to help them qualify for the loan. This has been a creative way to 

help homeowners. But, again, the nontraditional credit is a piece 

that, if automated with the data validity, can really help improve 

that process much more. 

For consumers with traditional credit histories, lenders have 

automated processes and scoring models. Those scoring models can 

provide objective, consistent, and quick decisions. 

And credit information generated through those models have a 

direct interface to the credit reporting bureaus. Once you have that 

information in the bureaus, it can provide a depth and length of 

customers’ credit experience. It lets you know who is searching for 

credit, and it also helps you understand how the person utilizes 

and repays their credit. 

While these models are very good and they are automated, the 

drawback to the scoring models is that they are dependent upon information reported to the credit bureaus. For individuals that are 

either new immigrants or that use credit infrequently or that may 

just be coming out of college, they do not have the traditional credit 

to get reported to the bureaus, even though they may have been 

11

living with their parents or an aunt or uncle and paying rent for 

12 months. That really could demonstrate good credit behavior. 

We need to find an easier way for reporting alternative payment 

histories. While current manual processes that we and others use 

in limited circumstances, and in some cases is accepted by the secondary market in a very limited way, it really does not work as efficiently as we would like for it to. 

One advantage of an automated process is the ability to treat all 

applicants equally. Bank of America is testing but not currently 

using any of the new automated systems that have nontraditional 

credit because we want to continue to work with potential partners 

as they improve the predictability of the information. 

Our goal is for this process to become more automated in a way 

that meets our criteria consistently and with integrity, which will 

broaden the opportunities for use. 

In conclusion, what I would like to say is providing alternative 

sources of data to current mortgage lending processes could greatly 

benefit multicultural and low-income customers. It would increase 

the number of people who can get into a home, reduce declinations, 

and help us to increase homeownership in the community. 

I am very pleased we have started this dialogue, and I look forward to continuous conversations. 

Thank you. 

[The prepared statement of Gwen Thomas can be found on page 

87 in the appendix.] 

Mr. CASTLE. Thank you, Ms. Thomas. 

Ms. Saunders is recognized. 

STATEMENT OF MARGOT SAUNDERS, ATTORNEY, NATIONAL 

CONSUMER LAW CENTER 

Ms. SAUNDERS. Thank you, Mr. Chairman. I am happy to be here 

today. 

I represent the low-income clients of the National Consumer Law 

Center, as well as the Consumer Federation of America, the National Association of Consumer Advocates, and the U.S. Public Interest Research Groups today. 

We believe that the reporting of alternative credit data holds the 

potential to help consumers considerably. 

However, because of the way the credit data and scores are currently being used in the marketplace, if these systems are built incorrectly or inappropriately used, the dangers to consumers could 

be devastating. 

We analyzed these new data systems through the prism of how 

they are currently being used. 

In addition to access to credit, credit scores and credit reports are 

being used to price credit. Some of the risk-based pricing that results from this use of credit scores today has supposedly justified 

very, very high-cost credit which is often unaffordable and leads to 

credit failure, default, and foreclosure. 

The credit scores currently are being used for eligibility and price 

for insurance in some States. They are also being used for employment, the initial decision relating to obtaining employment, as well 

as job retention. 

12

In some areas of the country, utility companies are looking at 

credit scores to determine eligibility for access to utility service. 

And there has been consideration of, and so far rejection of, the use 

of credit information to price utility service, which certainly must 

be kept on the radar screen. 

Because of that wide variety of uses of credit scores and credit 

data, we are very concerned that these new systems be developed 

based on fundamentally sound principles so that the information 

that goes into the new credit scores is truly relevant to the question of whether or not the consumer will have a likelihood to repay 

the credit for which the score being used. 

I am going to come back to that and talk about that mostly, but 

we also have concerns obviously that the information be accurate. 

We are very concerned that as these new credit data sources arise 

or grow, they only be allowed to be used for credit purposes until 

they have been thoroughly tested. 

Finally, there is considerable concern already on credit scores 

that they have a discriminatory impact and that they are built 

based on discriminatory history. We want to ensure, or we would 

hope to ensure, that the new credit scoring systems do not exacerbate this problem. 

It is essential that new scoring systems use payment histories 

which have characteristics substantially similar to the credit for 

which the systems are used. Specifically, one needs to look at the 

motivating factors behind both types of credit. 

The problem is that for many low-income people, for example, 

utility payments and some forms of credit such as payday loans 

and rent-to-own transactions have very different inherent features 

which send significantly different price and motivating signals to 

the consumer regarding whether to pay or not. 

We completely agree—I want to get this on the table—that a 

monthly rent obligation is an excellent source of information to use 

to base an evaluation of a consumer’s willingness and likelihood to 

repay similar credit, especially a home mortgage obligation. 

The rent payment is an exchange for essentially the same product: a home to live in. The payment is generally at the same intervals: monthly. The consequences of not paying are similar: loss of 

the home and a forced move. Similarly, the requirement of a regular months payment for a wireless telephone bill is certainly relevant to requirements for other monthly obligations. 

But a utility bill for heat, gas, or water consumers is not appropriate. That is because many of the programs devised to help protect low-income households from shut-off of essential utility service 

in the cold winter months do not punish for late payments. In fact, 

many Federal and State programs designed to assist low-income 

consumers with high utility bills are only triggered once the consumer is delinquent. 

Similarly, payday loan characteristics are very different than 

those for traditional loans. The consumer repaying a payday loan 

has a very different set of criteria to face. 

Number one, it is a huge lump-sum payment. Number two, failure to make that payment might result in criminal prosecution. 

Number three, making the payment may result in not having essential funds for food or rent or some other necessity. Four, payday 

13

loans, unlike other loans, have lenders who actually encourage consumers to not repay the full loan immediately, and they offer discounts and coupons for consumers who do not repay fully. They like 

the rollover; rollovers are how they make their money. 

I am out of time, but I am happy to answer any questions. Thank 

you. 

[The prepared statement of Margot Saunders can be found on 

page 72 in the appendix.] 

Mr. CASTLE. Thank you, Ms. Saunders. 

Dr. Turner? 

STATEMENT OF MICHAEL TURNER, PRESIDENT AND SENIOR 

SCHOLAR, INFORMATION POLICY INSTITUTE 

Mr. TURNER. Good morning, Mr. Chairman, honorable members 

of the subcommittee. I am grateful for this opportunity to testify 

before you today. 

I would like to commend Chairman Bachus, Chairman Oxley, 

and Chairman Castle for their leadership on this complex and crucial issue of consumer credit. 

Two years ago, I appeared before this subcommittee to discuss 

the benefits that Americans enjoy as a result of our national credit 

reporting system. That system is, by most accounts, the envy of the 

world. It is one of the engines behind the remarkable rates of 

homeownership in the United States. It is also of enormous help 

to those Americans who wish to start their own business. 

The success of our system of credit reporting is inarguable. But 

despite that success, many Americans, conservatively estimated at 

35 million, remain outside of that system. 

The reasons for this are not altogether clear. Despite the complexity of this issue, we have identified one of the reasons for their 

difficulties, namely the lack of credit information about these 35 

million Americans at the three national credit bureaus. 

Credit bureau information is, as we all know, one of the key 

means by which lenders make decisions on loans. And of course, 

paradoxically, without credit to begin with, it is difficult for such 

consumers to establish that they are credit worthy. It is like trying 

to get your first job when all the jobs posted require 3-to 5-years’ 

experience. 

We are here today because we believe alternative data offers a 

possible way to help consumers overcome the consumer credit hurdle. Categories of alternative data include energy and water utility 

payments, landline and wireless phone bills, auto liability insurance payments, rental payments, especially apartments, and certain types of retail payments. 

We recently completed the first part of a two-stage study examining the inclusion of alternative data in consumer credit reports. 

Several of our preliminary findings should interest members of this 

committee. 

Our first key finding is that utility and telecom data are likely 

to be the most immediately useful and practical alternative data 

for reaching people with little or no information in their credit files. 

By ‘‘useful,’’ I mean that virtually all Americans purchase services from utilities, including most of the population with which we 

14

are concerned here. In our analysis, we refer to this metric as ‘‘coverage.’’

By ‘‘practical,’’ I mean that these industry sectors are populated 

by a relatively small number of very large firms, meaning that 

there are very few data furnishers to reach. In our analysis, we 

refer to this metric as ‘‘concentration.’’

Finally, there are benefits for these companies where they do 

begin reporting. We have seen strong evidence suggesting that reporting customer data to credit bureaus, combined with customer 

awareness programs, substantially reduces delinquencies and defaults. 

Our second key finding is that nontraditional data is unlikely to 

negatively affect the credit scores of most Americans. Serious negative information is already reported by utilities, telecommunications firms, and other sources of nontraditional data, typically indirectly through collection agencies. What is not generally reported 

is positive information or timely payments. Reporting positive data 

improves credit scores and builds credit history. 

Given this, the public policy question then becomes, what can we 

do to promote the sharing of this information? 

Our study also examines factors that hinder the reporting of alternative data. In our forthcoming research, we identify two economic barriers and two regulatory barriers that may deter the reporting of this information. 

The four barriers are, first, in many States, regulatory uncertainty acts as a soft barrier on the provision of nontraditional information. This is especially true for utility providers that are often 

unsure of the permissibility of reporting. As a result, without clarification from State legislators or regulators, the fear of potential 

legal liability and public relations fallout acts to block the sharing 

of customer data with credit bureaus. 

Second, in our survey, at least two States have laws that prevent 

utilities from reporting certain types of consumer payments. 

Third, some prospective furnishers are reluctant to report this 

data fearing that it will enable competitors to steal their customers. 

Fourth and finally, some firms may have complex and incompatible legacy IT systems in place that would make the cost of reporting greater than any perceived benefits. 

These last two are obviously problems we should leave to the 

market, but public officials can address the first two barriers we 

identified: again, regulatory uncertainty and legal hindrances. 

In some ways, regulatory uncertainty could be dispelled with little more than a public commitment to the idea of alternative data 

sharing. Public service firms should be encouraged to at least look 

at whether or not reporting alternative data might be a good idea 

for them. 

We have framed what we believe are the key practical questions 

concerning the reporting of alternative data. In the months ahead, 

we intend to work with members of the credit reporting industry, 

financial institutions, utilities, and consumer education organizations to measure whether and how much the inclusion of alternative data in consumer credit reports could help more Americans 

15

realize their dreams, dreams like homeownership, buying a new 

car, or starting their own business. 

We look forward to providing our findings to members of this 

subcommittee in the near future. 

Again, I thank the members of this committee and the chairman 

in particular for this opportunity and welcome your questions and 

feedback. 

[The prepared statement of Michael Turner can be found on page 

92 in the appendix.] 

Mr. CASTLE. Thank you, Dr. Turner. 

Thank you, all. This is a very interesting panel, and you have a 

lot to say. 

We do not have enough time in our questions to be able to possibly cover all of the things that we should cover, but I will start 

by yielding to myself for 5 minutes. 

Let me ask just one basic question. I said this in my opening 

statement, and ever since I said it, which my staff helped prepare, 

I have sort of questioned it. 

That is, I said that 35 million to 50 million Americans are without credit scores. If my recollection is correct, we have, what, about 

280 million people in the United States of America, a lot of which 

are children. Thirty-five million to 50 million sounds high to me. 

Does anyone here—and if you do not know, do not try to answer—but does anyone here have any idea what the number really 

is? In any of your businesses, have you ever tried to identify that 

whole number of those who do not have credit scores at this point? 

Ms. NELSON. We have, and our ranges are similar to yours. I 

mentioned 50 million. The general thought process that got us to 

that number was that of the total population, it is estimated that 

there are about 215 million adults aged 18 or over living in the 

United States. 

Mr. CASTLE. I am sorry, how many? 

Ms. NELSON. About 215 million. 

Mr. CASTLE. Right. 

Ms. NELSON. So I am just walking you through our logic. This 

comes from a number of different sources that we have pretty 

much culminated together. 

And then from there, we are also estimating that there are about 

165 million of those consumers that have enough data within the 

bureaus to generate a score. 

So our estimation is that of the remaining 50 million or so, about 

30 million do have data at one of the three national repositories, 

but not enough to generate a score, and another 20 million probably have no data at all. 

Mr. CASTLE. So we are dealing with pretty big numbers here. 

Ms. NELSON. Yes. 

Mr. CASTLE. This is not just a problem of 1 million people or several hundred thousand or something like that, but a big number. 

This is a question I could ask any of you, so I will just try to 

limit it and I will ask Mr. Catone perhaps and Dr. Turner to comment on this. 

I indicated in my opening statement that this hearing was not 

preparatory to introduce legislation, and you mentioned it a little 

16

bit, Dr. Turner, not that we should do it, but you mentioned a little 

bit in what you stated. 

My question is, do you feel that at a State or Federal level that 

we should be considering some form of legislation, statutory legislation or regulation to deal with these issues? 

Obviously, from all five of you, it is an evolving issue. In fact, 

there are some differences that are very interesting here in terms 

of what you view as significant data in terms of alternative credit 

information. 

My question is, should we be regulating this? We have been 

doing a lot of regulating around here lately. I am a little reluctant 

to over-regulate. I would be interested in your viewpoints on that. 

Mr. CATONE. It is an issue of economics. It is much more expensive to do manual compilation of data or verifications of the data, 

do the proper fraud checks and things to prevent information that 

may not be quite right from entering the system. Lenders and investors are concerned about that aspect of it. So it is much more 

expensive to serve that community. 

What needs to occur at some point in time—and based on the 

changing demographics of the United States, it may be 2 years, 5 

years, 10 years—but something would need to be done to adjust the 

economic incentives to serve the market better. We are starting to 

see that, and the reason we are sitting here today is because it is 

becoming an issue. So there is a whole set of economics that come 

into play. That is the reality of the situation. 

Mr. CASTLE. Dr. Turner, do you have a quick answer to that? 

Mr. TURNER. I would not endorse regulatory activity at this juncture. The barriers that we identified in terms of policy primarily 

are indirect. 

We have spoken with utility companies that are reporting and 

met with their public service commission in their State and let 

them know that they were going to report and were told outright 

that they should not report. They went ahead and reported anyway 

because there were no statutory prohibitions on the book. They 

were doing this as a matter of courtesy. 

We have also spoken with regulators actually in your State, Mr. 

Chairman, and there was a case where a utility was reporting data 

and was told not to report the data by the public utility commission 

and discontinued the practice despite the fact that no laws were on 

the book. 

In California, we had conversations with regulators there and 

they, in fact, suggested that there were requests from utility companies in California to report the data and asked the regulator, ‘‘Do 

we have permission to do this?’’ The regulator said, ‘‘Sure, go 

ahead.’’ The utility company said, ‘‘Can we have this in writing?’’ 

The regulators were unwilling to put this in writing until they got 

direction from the legislature. 

So it is really a matter, I think, of some sort of guidance from 

the State legislatures at this juncture. Only two States have varied 

prohibitions on the books for the onward transfer of this data, and 

it is not with this issue in mind. 

Mr. CASTLE. Thank you. I appreciate that. Obviously, this is an 

evolving issue, so we will continue to look at this. 

17

I am just interested, if I could ask a little bit of a different question of Ms. Saunders, of you, and perhaps Dr. Turner—I thought 

I saw disagreement here, because, Ms. Saunders, you were pretty 

adamant that utilities were not necessarily very predictive, primarily in terms of a mortgage. But in terms of lending perhaps, I 

think all of you agreed that rent is in that circumstance. Part of 

it is that the programs that exist that do not even have any implications until you go into default, to a degree. 

Dr. Turner, you talked about the utilities and telecommunications as the most promising and practical source of nontraditional information. I would say there is a bit of a conflict there in 

terms of what you both have said, not to pit you against each 

other. There is probably some truth in what both of you have said. 

Maybe we should start with you, Dr. Turner. Can you defend 

why you said that? I think I understood Ms. Saunders’s position, 

and perhaps she can try to respond to that. 

I am not looking for trouble here. I am just looking for the best 

answers on what might be predictive or not. 

Mr. TURNER. Ultimately, I think we disagree actually not only on 

utilities and telecoms data, but also on rent data as well. 

In our analysis, we identified industry sectors that have a high 

level of concentration, meaning just a few data furnishers or prospective data furnishers, and a high coverage, meaning that many 

of the lower-to moderate-income Americans, the unbanked, the thin 

or unscorable filed Americans, would have these services. 

Rental payments are highly fragmented. It does not really reach 

a lot of the affected population. 

We do think, for example, if there is some sense of a need for 

public policy, many of those in affordable housing or public housing 

actually would benefit potentially from having their payment history reported. That is an area where State public housing authorities could act. 

But ultimately, in any of these data types, we are not prepared 

to make judgments as to whether or not one data set is currently 

more predictive than another. That is an empirical matter. That is 

what we are setting out to do in our quantitative analysis in the 

next component. We are just not prepared to suggest qualitatively 

that certain types of data are better or worse without the benefit 

of actual empirical analysis, regression analysis. 

We are aware of some groups that are actually putting this to 

the test in the trenches and meeting with consumers, asking them 

to volunteer to have their data reported, and measuring over time 

whether or not it makes an impact on their score and their access 

to credit and the terms of credit. 

Mr. CASTLE. What do you think, Ms. Saunders? Is it empirical 

data, or can we put a qualitative mark on each of these things as 

to what is better and what is not? 

Ms. SAUNDERS. I think Dr. Turner is correct that we need to do 

a lot more analysis. 

I want to explain that while we are concerned with the furnishers who are providing the data, we are also very concerned 

with the users. So part of our concern with using utility payments 

as a means of gaining information about the consumer is guided by 

the fact that we really do not want to see utility bills in the future 

18

based on risk, as some non-regulated utility providers have already 

proposed doing and have been rejected. 

Specifically in Texas, there was a bill that would have allowed—

or there was consideration of that exact question. Let me clarify 

that. Let me emphasize that what they were proposing to do was 

to charge higher rates for electric and gas for low-income consumers who had worse credit. 

That is exactly what we are most afraid of because electric and 

gas and other utilities are essentials, and you should not be able 

to do that. So part of our concern with the furnishing of utility information is guided by the fear on the back end. 

I do agree with what Dr. Turner said, that when some utility 

bills are seriously delinquent, they are already reported to the credit reporting agencies, so that it would not hurt in those situations. 

But I would challenge him on the point that all delinquent utility 

bills are regularly reported because I think that is just not the case 

across the country. 

Mr. CASTLE. Thank you, Ms. Saunders. 

My time is up, and Ms. Moore is recognized for 5 minutes at this 

time. 

Ms. MOORE OF WISCONSIN. Thank you so much, Mr. Chairman. 

I apologize to the panel for not hearing the testimony of these 

distinguished panelists. 

I have listened with interest over the discussion of the use of 

rent and utilities as a means of getting these folks with thin 

records an opportunity to receive credit, particularly mortgages. 

Ms. Thomas, I came in during your testimony. 

I guess my question is, why can’t we develop some sort of instrument where people who do not have any credit history are presumed to be bankable, innocent until proven guilty? 

There are many people who deliberately do not have credit because they heave learned what we have learned years later: You 

should not have too many credit cards in your pocketbook. The generation before me, my uncles and aunts paid all their bills, bought 

things on layaway, except for owning their own home. 

I am wondering, number one, why it is a problem that people 

have thin credit? 

Secondly, I also am concerned about using utilities as a factor in 

determining credit because energy costs—I am from Wisconsin, and 

energy costs have far outpaced people’s ability to pay, even people 

who are not regarded as low income. 

In addition to which, people have due dates that are completely 

arbitrary. It is not like every bill is due the first of the month. The 

billing date may be the 14th of the month. If you pay on the 15th, 

then you are in trouble. 

I guess I would like for Ms. Thomas, Ms. Saunders, to sort of respond to these concerns that I have, and anyone else who would 

like to jump in. 

Thank you. 

Ms. THOMAS. I think your first point about why is it considered 

a thin file and the whole thin file piece is a standard definition 

based on individuals having less than three credit lines. That is 

why we accept that information manually today. If a person does 

not have enough credit, we ask for rent, utilities, telecom, insurVerDate 0ct 09 2002 12:08 Jan 19, 2006 Jkt 000000 PO 00000 Frm 00024 Fmt 6633 Sfmt 6633 G:\DOCS\109.29 RODNEY
19

ance, anything that can show us payment history. Because typically you will find that there is good payment history there, it is 

just not automated. 

Then for the utility piece specifically, back to your and Ms. 

Saunders’s point, if we see indications where those payments have 

not been paid on time, when you are doing this manually, you can 

ask further questions to seek the understanding of what happened. 

In most cases, the customer can explain that it was due to some 

extreme circumstance, that we can then move forward with the 

loan. 

Ms. MOORE OF WISCONSIN. That is a very good point. 

I remember once I was subjected to a utility shut-off and I had paid all through the moratorium and still had a $2,000 bill come 

spring. When they asked further questions, they discovered that I 

had a 30-year-old furnace that had originally been a coal furnace 

converted to an oil furnace, and I had converted it to a gas furnace. 

It was very inefficient, and that was the reason that I just could 

not keep pace with the utility bills. 

Ms. Saunders? 

Ms. SAUNDERS. I would like to pose the juxtaposition between 

utility bills and standard credit. 

Most credit offered to middle-income consumers is underwritten. 

There is an evaluation made by the lender about the consumer’s 

ability, not just willingness but ability based on income, to repay 

that loan. 

Utility bills and payday loans are not underwritten. In fact, they 

are quite the reverse. Utility bills can very often be very large, 

much larger for lower-income people than they are for higher-income people because they live in houses which are not weatherized 

and because they have many people in their family. 

So we are using information that is really not relevant, and that 

is our concern. 

Ms. MOORE OF WISCONSIN. I also want to ask one final question, 

Ms. Saunders. You mentioned pricing credit used to justify high interest rates. I have seen this continuously where creditors just are 

in glee to see a little glitch on your credit report. So I have come 

to think that somehow the Fair Isaac scores are not fair. 

I have heard many reports, experienced it personally, where 

there is almost this little game where people just really are in glee 

about bad credit. 

Can just anybody respond to that before my time expires? 

Thank you, Mr. Chairman. 

Ms. SAUNDERS. If I might very quickly, I would like to point you 

to that part of my testimony where I discuss in some detail the discriminatory questions that have been raised about credit scores already. 

There have been lawsuits, and there have been a lot of studies, 

and a lot of people believe that current credit scores do have discriminatory impact. And we are concerned that as these new alternative sources of credit scoring develop, that we not exacerbate 

that problem. 

Ms. NELSON. I just need to point out one comment to what was 

just said. That is that, as we develop scores, we are very cognizant 

of what is allowed and not allowed as factors that drive the score. 

20

So that is an important piece of understanding that I would like 

to make sure this entire subcommittee understands. 

Secondly, when you talk about the fairness of the scores, the 

score has been proven time and time again to be a solid predictor 

of risk. I think part of what you are describing is some lenders’ decisions and policies around how to react to that score when dealing 

with the consumers themselves. 

So I just want to be careful not to leave the impression with this 

committee that the scores do not work. The scores absolutely are 

predictive of consumer behavior going forward. 

But policies that surround that score is an issue that I think 

every lender deals with in a very, very strategic and personalized 

way. So it is difficult to describe any practice as being industrywide. We know that there are some lenders that are more aggressive than others in how they deal with consumers in that account 

review mode. 

Mr. CASTLE. Thank you, Ms. Moore. We appreciate it. 

Chairman Bachus is recognized for 5 minutes. 

Mr. BACHUS. I thank the chairman. 

I guess before I ask a question, I would make a statement. I am 

not sure that this Congress or this committee should ever require 

companies or individuals to share information about payments. 

That is being pretty intrusive if you ordered utility companies to 

share that with credit bureaus. 

You know, 90 percent of the landlords in this country are individuals, so it is a very decentralized thing. That would take a monstrous bureaucracy and enforcement system if you required all of 

them to report that. I mean, that would be a pretty overreaching 

law. 

I am also concerned about privacy. That is a very important 

issue in this country, is people’s privacy. For the Government to 

start saying that you have to give out information on your customers or on your tenants would be, to me, almost a revolutionary 

thought because that gets in the public domain. So I would make 

that comment. 

I would ask that with 90 percent of the rental units in the hands 

of individual landlords, is it even practical to require such a reporting system? Let me ask that question first. Just any feedback from 

the panel on that? 

Ms. NELSON. I would provide a couple of thoughts. 

I have a history not with Fair Isaac but in prior employment 

with a consumer reporting agency that is obviously not one of the 

three national bureaus. The services we provided were to financial 

institutions to help manage risk on the debit side of their house. 

That is an example where back when that company was founded 

in the early 1970s, it was not a highly concentrated banking industry as it is today. There were thousands and thousands of banks 

across the country. 

The inception of that particular business model occurred because 

banks were getting hurt by consumers that were either being abusive or fraudulent with their checking accounts. So there was a reason for the industry to cooperate together, share information and 

help themselves manage risk. 

21

I raise this as an example because Mark already mentioned that 

the economic model behind this issue is a significant aspect in that 

there are significant costs both to the furnishers that provide the 

data, as well as the aggregators. 

And there has got to be some sort of incentive. In some industries the incentive is to be able to better manage the risk within 

my industry if I share with my competitors information, both positive and negative. 

So in the case of the rental industry, if there was enough incentive to that group of small business owners to be able to start sharing that data, that is the incentive that gives them the reason to 

start to share the data and, therefore, would be available for use 

to help consumers beyond finding that new housing, but also to 

eventually obtain a mortgage. 

So the economic model is a big issue. Tied to that is the whole 

regulatory aspect. 

If you look at the work that any of us are doing today, all alternative credit data is governed by the FCRA and FACTA. So we 

have the same consumer protection mechanisms in place as we do 

with the national bureaus. 

So whether you are a large national bureau or a very small boutique consumer reporting agency, your obligations as an aggregator 

and the obligations of your furnishers are identical in that you 

have to be certain the data is accurate. 

Mr. BACHUS. I guess my question was more, aren’t there some 

real practical hurdles to even—I almost hesitate to ask the question because I would not be in favor of requiring America’s landlords to report. 

Ms. NELSON. The costs would be insurmountable, I believe. 

Mr. BACHUS. That was really it. 

Let me go on to utility payments for a minute. 

Number one, I would say I am not sure what the value would 

be because people are going to pay their utilities, or the option is 

to get the service disconnected at times, I would think. But secondly, with utilities they estimate payments. My mother, for instance, with $1,200 Social Security, she will have a bill that comes in one month and it is $15 for water, then 

the next month it is $115. They vary quite a bit. The gas bill—I 

have seen them; they will go from $100 to $250. What we do is we 

supplement that and my mother pays them. But her utility bills 

can really go up and down. I actually charted that out, and they 

go up as much as 40 percent and 50 percent. 

So I would think some people do that by paying one month a certain amount each month. And I think most, like Alabama Power, 

I think their policy—probably somebody pays $50 on a $50 bill, and 

the next month they get a $150 bill and they pay $75 and catch 

up. I am not sure anybody thinks there is anything wrong with 

that. 

Mr. TURNER. If I could just respond to the utility question. 

Again, I think whether or not any individual data sets are predictive in terms of one’s credit risk, credit capacity, or credit worthiness, there are ultimately empirical questions. 

In terms of utilities, I agree with Margot Saunders; all of these 

data sets have different characteristics. They are likely to have difVerDate 0ct 09 2002 12:08 Jan 19, 2006 Jkt 000000 PO 00000 Frm 00027 Fmt 6633 Sfmt 6633 G:\DOCS\109.29 RODNEY
22

ferent predictive value for different lenders, for example. What may 

matter in a home mortgage loan immensely may not matter so 

much for general purpose revolving credit. 

However, in our analysis, we make a distinction between types 

of alternative data that are more credit-like, meaning that you receive a service before you make a payment, like a credit card. You 

can use a credit card before you have to make the payment, or that 

are more cash-like, like a debit card. We think that that is a meaningful distinction. 

And when you look at a thin file or someone who is unbanked 

and you have no ability to accurately predict the probability of default, if you can populate that file then with credit-like components, 

utility data, wireless phone data— again, they have different characteristics—it may be possible to make a better assessment of that 

individual’s credit worthiness. That is what this is really about. 

Ms. THOMAS. What I would like to add to that—and you made 

an interesting comment about privacy because that is a concern—

but one of the challenges sometimes for the customer when you are 

trying to get that mortgage loan approved—and that is the hat that 

I am wearing is if they do not have receipts, because who keeps 

12 months of utility and rent receipts, it is tough for the customer 

sometimes to get the information, and sometimes we try to help 

them do that. 

Mr. BACHUS. I would say this. I would agree with you. I think 

if someone low or middle income, particularly, that needs to establish credit, I think that if they sign something and say, I would like 

the utility company to supply my payments, or a landlord, I can 

certainly see that. That does away with most of my privacy concerns. 

Ms. THOMAS. Okay. 

Mr. BACHUS. I think that a tenant probably has the right to ask 

for that, and I am sure landlords would not mind supplying that. 

I would hope not. 

Ms. THOMAS. Some of them do not mind; some do. 

Mr. BACHUS. Yes. That is a very good point. I had not thought 

of that. 

I yield back. I do not have any time left. 

Mr. CASTLE. Thank you, sir. 

Congressman Baca is recognized for 5 minutes. 

Mr. BACA. Thank you very much, Mr. Chairman, and thank you 

for having this hearing. 

Let me ask this question of Mark Catone. 

In your testimony, you discussed the changing demographics that 

impact credit markets. You state that immigrants have accounted 

for more than one third of the household growth since 1990. Immigrants are included in a list of rising numbers of consumers, and 

I state, ‘‘A rising number of consumers who are planning to make 

major purchases either earlier in their lives or soon or after becoming U.S. citizens.’’

I am very much concerned that Real ID and the laws to establish 

national ID cards for employment purchases will affect immigrant 

consumers in the U.S. It is true that the use of nontraditional credit reporting, such as utility statements for immigrants, can provide 

them with greater credit availability. However, I am more conVerDate 0ct 09 2002 12:08 Jan 19, 2006 Jkt 000000 PO 00000 Frm 00028 Fmt 6633 Sfmt 6633 G:\DOCS\109.29 RODNEY
23

cerned that the Real ID will prevent some banks from doing business with immigrants. It may push them further into the category 

of unbanked. 

Can you comment on the Real ID bill as a new barrier for immigrants seeking to build a credit history? This is question number 

one. 

And two, what do you believe can be done to prevent this, if anything? 

Mr. CATONE. Let me position it in terms of our experience and 

our experience of compiling nontraditional data in response to 

mortgage originators’ and investors’ loans. 

We have seen alternative identification presented to use for those 

consumers in compiling that information—for example, consumers 

that may not have a Social Security number or who may have an 

individual identification number or an alternative mechanism. 

There is not anything that I am aware of—and I am probably not 

the best person to speak on the regulatory subject of the identity 

issue, but in our experience, we do not differentiate between 

whether an individual has a different type of identity or 

verification of that nature. 

We are responding to our originator or a mortgage investor’s request to compile a nontraditional credit report for the purpose of 

extending a loan. So it is more general based than broad based. We 

are not telling the difference between one or the other. 

We do verify the identity, the address of the applicant. We do 

verify the data that is sent to us and that we collect and compile. 

That is transmitted back to the mortgage lender or the investor. 

So I do not have the depth, I think, of granularity you are looking for in terms of the identity issue. 

Mr. BACA. So it could create a problem, though, because right 

now most of them can use matriculas for identity purposes and 

banking purposes, but if Real ID was put into place, the difficulty 

then in terms of the banking, as well, would also impact our societies because individuals use either banking or credit through 

banking, not only in obtaining credit and credit rating, but they 

also use the banking to pay a lot of their payments. 

In making payments from the banking or checking accounts, they 

end up becoming taxpayers on sales tax, so that sales tax then 

could conceivably be lost within each and every one of our communities based on what may be implemented and how it is interpreted, with Real ID, the law that just passed last week. I just 

wanted to find out if it would have any impact on our banking system based on Real ID. 

Let me ask you another question. This one goes to Michael Turner. 

Latinos are more likely to have no credit history—22 percent 

compared to 4 percent of whites and 3 percent of African-Americans. Some suggest that part of Latino culture is to remain debtfree. What cultural or economic reasons are there that create the 

discrepancy? This is question number one. 

And how can we increase and improve education to Latinos and 

other minorities, especially regarding the new use of nontraditional 

credit risk indicators to encourage a healthy credit history so they 

are able to enjoy the same credit availability as their neighbors? 

24

That is difficult when it comes out with the credit rating being 

higher for a Latino versus a non-Latino. 

Michael? 

Mr. TURNER. Thank you for the question. There are two questions, actually. 

I cannot pretend for a moment to fully understand or explain the 

discrepancies. I have seen analysis that suggests that, for instance, 

with the Latino community in particular, there is an issue of parttime residency. 

I lived in Washington Heights with the largest Dominican population outside of the Dominican Republic. Many people in my 

neighborhood would leave for 3 or 4 months at a time and go back 

to D.R. They would not pay utility bills for 3 or 4 months, and then 

when they could come back everything would be paid. 

So in a traditional credit model, that is a pretty serious negative, 

a serious delinquency, but it may not accurately reflect, for instance, their credit risk or credit worthiness. 

I am aware of some efforts to try and better understand certain 

populations and these discrepancies in credit scores and how they 

are explained behaviorally. We do not analyze that in our study. 

It is certainly an interesting topic, and it is a very rich subject, and 

it is worth a lot of analysis, but I cannot really speak directly to 

that. 

What I can speak to, and I think you make a very important 

point here, the group that we are talking about, the unbanked, recent immigrants, thin-file Americans, they are not likely to have a 

high degree of financial literacy. What is the significance of a consumer credit report? What is the meaning of my credit score? Why 

does it matter in day-to-day life? 

We are dialoging through our own work with programs that are 

actually out in the field working with low- to moderate-income 

Americans, different immigrant populations, and testing. They are 

small efforts at this point, and they are vastly underfunded. But 

they are testing whether or not they can hold a focus group or educational seminars, get consumers from these populations to volunteer to have this data shared, and to track over time whether it 

matters materially to their score, to access to credit, to the terms 

of that credit. 

I think that is a tremendously important effort. I think certainly, 

at least I am hopeful that one of the outcomes of this hearing is 

an increased awareness of the importance of those efforts. 

Mr. CASTLE. Thank you, Mr. Baca. 

Mr. BACA. I know that my time has expired, but I hope we do 

more educational awareness training because we do not want them 

to prey on these kinds of individuals, because their credit, being 

minorities, is a lot higher than anyone else. If there is that kind 

of educational training, at least they will be aware to look at their 

credit rating, change whatever needs to be done in that area, so 

this way they do not continue to prey as, hey, I am going to make 

X amount of dollars because their credit rating is so high, so 

,therefore, I am going to charge X amount of dollars. 

Thank you very much. 

Mr. CASTLE. Thank you, sir. 

25

Ms. THOMAS. Chairman Castle, may I add one brief comment to 

what he was saying? 

Mr. CASTLE. If you can be very brief. 

Ms. THOMAS. One organization, the National Association of Hispanic Real Estate Professionals, is doing a lot around educating the 

Latino community on that particular issue. 

Thank you. 

Mr. CASTLE. Thank you. You were brief. 

Mr. Pearce is recognized for 5 minutes. 

Mr. PEARCE. Thank you. 

I have a series of questions, and I am going to ask for the shorter 

answer rather than the expansive answer. Five minutes elapses 

really quickly, and if you are drifting off, I will probably pull you 

back, but do not take it personally. 

I do not want to talk about the unethical people who exist on 

both fringes: unethical lenders who would exploit or unethical consumers who would take advantage of it. I am trying to wrestle with 

the concept somewhere out in the middle of how we deal with people who have not always been on the upside of the economic spectrum. 

Ms. Nelson points out that their improved techniques are allowing actually credit to be given more widely. Instead of a categorical 

exclusion, we are actually getting down into some of the participants maybe that previously could not have gotten credit because 

we have better information. 

Ms. Saunders is somewhat uncomfortable, on page two, with people pricing credit based on your ability or your previous history of 

paying. And yet I find Ms. Thomas, I suspect you all, if you find 

someone who is not a very good credit risk, but you are going to 

try to work them into your program, and I see that happening. 

Our district is very poor, and Mr. Baca has pointed out a lot of 

people in the Hispanic economy are actually on the cash economy. 

Do you all find that your costs associated with some of those clients are higher than the costs associated with someone who just 

sends a payment in every month? 

Ms. THOMAS. What we see, and I do not have the exact cost numbers, but it does take longer in terms of cycle time, which can 

translate into costs. So it takes more effort working with the consumer. 

Mr. PEARCE. So if you have a higher cost, if you do not charge 

a greater price, and you have a higher cost, then you are actually 

charging someone else for that person’s cost. 

Ms. THOMAS. We are charging that individual, but we are not 

charging them a higher rate. 

Mr. PEARCE. I am just saying that if it is a higher cost and you 

charge the same thing you are charging someone else with a lower 

cost, then actually you are either accepting less margin, and if that 

margin becomes negative, you then charge someone else for fees 

that would go over here. 

Ms. THOMAS. No, that is not the case. It does impact our productivity, so you are correct there. 

Mr. PEARCE. That is all I needed to know. 

Ms. Saunders, you would feel very uncomfortable with any price 

increase no matter what the credit risk? 

26

Ms. SAUNDERS. No, sir. I think you misunderstand me. I was trying to put a lot of ideas into a few short words. 

We do not disagree with the idea behind or the justifications of 

risk-based pricing. We certainly see many instances where low-income consumers have benefited from them. 

What we disagree with is the very typical practice among some 

creditors of using risk-based pricing——

Mr. PEARCE. Sure, yes, those are the ones I said we are not going 

to talk about. Yes, there are unethical people. But you are giving 

clarification, and that is what I am asking for, that you really do 

not object to the price. It is the unethical treatment of price increases. 

Ms. SAUNDERS. Well, there is a recent study that came out in the 

paper just a few weeks ago where it showed that those consumers 

of credit cards that were paying the late fees and the default interest rates were actually subsidizing the middle-income consumers 

who were not paying anything. So in terms of subsidies, I think it 

is going that way. 

Mr. PEARCE. I appreciate that. 

On your program, Ms. Thomas, in the underserved market, what 

kind of success rate are you having on the repayment of your 

loans? 

Ms. THOMAS. We are having a very good success rate. We monitor that pretty closely. That is how we were able to get the practice of utilizing nontraditional credit approved in the first place. 

Mr. PEARCE. And typically people in this credit category that you 

are reaching down trying to now extend services to, they usually 

are not going to be the people looking for the $100,000 to $200,000 

loans. So what size loans do you find them targeting? What is the 

smallest loan you give? 

Ms. THOMAS. I am sorry, what was the last one? 

Mr. PEARCE. What is the smallest loan you all give? 

Ms. THOMAS. Loans can vary anywhere from $70,000 up—I think about different markets, where $100,000 could be a low-income 

home, a low-income mortgage. And for individuals that are on the 

extreme end of the credit risk, we require counseling, education, 

because we have——

Mr. PEARCE. No, I am just asking for what size loan. 

Ms. THOMAS. Anywhere, $70,000 up to, in California it could be $200,000-plus. 

Mr. PEARCE. And that is my point, that one of the greater tasks 

for us, I think, is some of the smaller banking institutions. You all 

do a good job of outreach and reaching in, but really in our district 

we find that the low loans of $30,000 really not many people want 

to offer down in there. It kind of addresses Ms. Saunders’s concern 

that there are not many participants willing to go down into that 

range. 

So we really have the testimony here that would allow us to give 

a lot more people access to credit if we can figure out how to measure the parameters and we can find lenders who are willing to get 

out and take that step and charge a reasonable rate of interest and 

give access and take the risk. 

I appreciate the fact that Bank of America is doing that. Somewhere we have to find the measurement tools that will then allow 

27

us to really thread the needle a little bit more finely than these 

categorical exclusions. 

So myself, I appreciate all of the efforts on both sides of trying 

to solve it because it is a thing that affects my district a lot. We 

are low income. We are majority minority, and people just work 

hard and stay on cash economies. 

So I salute you for what you are doing. We will see if we can facilitate it. And thank you all for your good testimony. 

Mr. CASTLE. Thank you, Mr. Pearce. 

Ms. Carson is recognized for 5 minutes. 

Ms. CARSON. Thank you very much, Mr. Chairman. 

And thank all of you, certainly, for being here. 

My question is one of not to be combative, but simply to understand the process better. 

For example, I have a neighbor. Well, let me start over. There 

are consumers who are good payers. There are consumers who are 

slow payers. And there are consumers that do not pay at all. I understand that, and I am not favoring the no-pay-at-all when they 

can pay, please. 

In situations like in my district where the gas bills have skyrocketed—in my own case, this is not hypothetical, I have lived in 

the same house for 35 years. My winter gas bill has gone from $100 

a month to $700 a month now. It is just outrageous. We have 

neighbors in the same situation, who are low-income, who have had 

to borrow payday loans, put utilities on credit cards, to keep their 

utilities on. Sometimes it works and sometimes it does not, but the 

more they borrow, the more the cost of the utilities becomes. 

In your scoring process, do you by any chance take into consideration people who have been good payers and then suddenly something happens and they go down the drain financially and do not 

pay the utilities on time and a lot of them are disconnected? 

Do you use a unique scoring system that would take all of that 

into consideration if you know about it? And how can you know 

about it if somebody does not tell you about the circumstances? 

Ms. THOMAS. In terms of a scoring system, that example would 

not be dealt with in an automated way, but in a manual way we 

can ask the question. Because if you see a person’s history has 

been good and all of a sudden something happens, we usually will 

ask for an explanation, and if the explanation is one that makes 

sense, then we can use that information to continue underwriting 

the loan. But it is not automated; it is manually done. 

Ms. CARSON. So it is always manually done when the red flag 

comes up. Who ultimately determines if your credit scores are statistically sound? Is there some independent external oversight of 

your credit scoring methods? 

Ms. NELSON. Are you asking as a lender or as an industry? 

Ms. CARSON. Industry. 

Ms. NELSON. Fair Isaac continually works to validate the predictiveness of their score. Every lender that uses the score will 

then manage the score and their loss rates so that they are looking 

at their own portfolio to be certain and confident that the cutoff 

ranges that they are using are appropriate for the business that 

they are trying to attract. 

28

So it is a very personalized process for each lender in terms of 

monitoring performance of the scores that they have used. 

Ms. CARSON. I have another question. I see that payday loan 

lenders can be used to determine FICO expansion scores. I know 

anybody that goes regularly to a payday lender is in financial trouble anyway. If you go borrow $100, and when you pay it back it 

is going to cost you $120 or $130, you automatically have a problem 

anyway. 

So how then do payday loans become a part of the equation when 

you know straight up? I have constituents, because I tried to close 

payday loans down, and they were outraged at me. ‘‘How dare you. 

That is what I depend on.’’ Well, hell, I didn’t know. I just thought 

you were getting ripped off unfairly or unnecessarily. So payday 

loans are very popular with some people. 

Now my district, don’t confuse what it is. It is not African American. It is not welfare oriented. We just happen to have some constituents who fall through the cracks. I have to qualify that because people look at me and presume that I am from an AfricanAmerican district, and that is not true, even though I have been 

elected to Congress five times. 

So it is not to rely heavily on somebody that is of color, somebody 

that is on welfare, any of that. I get annoyed because people automatically make those assumptions when they look at me. 

But how then do military families rely ordinarily on payday 

loans because the Government, I am not going to use the word because I do not know if there any kids in the audience, but they are 

not runaway brides. They are trying to protect the sanctity of this 

country, the freedom of the country. Military people rely on payday 

loans all the time. I think it is something like 23 percent of them 

that are on active duty in the military. 

So then how do you differentiate those kinds of situations, payday loan lenders, in your scoring process? 

Ms. NELSON. Specifically to the expansion score, we have looked 

at the value or the predictiveness of payday lending behavior, loan 

behaviors for consumers. So we have analyzed it, but today it is not 

part of the expansion score. 

Ms. CARSON. You do not use it? 

Ms. NELSON. No. 

Ms. CARSON. You do not use them. I take your word for it. 

Ms. NELSON. You have my word for it. We do not use payday 

lending information. 

Ms. CARSON. I am going to yield back the balance of my time. 

Mr. CASTLE. Thank you, Ms. Carson. Thank you very much. 

Mr. Hensarling is recognized for 5 minutes. 

Mr. HENSARLING. Thank you, Mr. Chairman. Thank you for your 

leadership on this issue. I certainly think it is a worthy topic, 

whether or not nontraditional data can be used in these credit 

scores to provide credit to perhaps historically underserved populations. It is certainly a topic worthy of our discussion. 

Dr. Turner, in your testimony, you have touched upon it, but I 

would like for you to elaborate. I think, if I understand you properly, you have concluded that the reporting of nontraditional data 

is very unlikely to negatively impact credit scores for most Americans. I think you essentially see this as an upside because you have 

29

stated that, by and large, most negative credit information is already reported into the system, and frankly it is the thin file, to 

use industry parlance, that is the major challenge. 

Can you just go into a little bit more detail about what facts and 

research your conclusion is based upon? 

Mr. TURNER. I would be happy to. 

In our forthcoming study—and, again, it is a qualitative analysis 

that sets up the subsequent quantitative analysis—we interviewed 

a number of prospective data furnishers, lenders, modelers, credit 

bureaus, et cetera, and really got a firm sense of the landscape of 

what is and is not reported. 

I am in agreement with my colleague here, Margot Saunders, 

that all utility companies do not report all negative data. I never 

ever implied that or inferred that. There are some utility companies that are reporting both positive and negative data directly to 

credit bureaus currently. It is a minority, but there are some that 

are doing it. 

What I focused on was the indirect reporting from this universe 

of alternative data providers, the telephone companies, your 

landline, your wireless, utility companies. When accounts go into 

serious delinquency or default, they go to collection. The collection 

agencies report payment and nonpayment, the entire set of information, to the credit bureaus. So those sets of negative data from 

this range of alternative data furnishers are already reported. 

So if in a hypothetical situation, all utility companies, all wireless provides, et cetera, were to begin reporting positive and negative, the net impact would be unlikely to be very negative for those 

that we have identified as thin file or unscorable or the unbanked. 

What they would benefit from would be the overwhelming 

amount of positive payment history that would be appended to 

their files and may, and again this is an empirical question, may 

enable them to enter into the mainstream credit system. 

Mr. HENSARLING. In your testimony, didn’t you also mention that 

the lack of access to credit may help explain why there are lower 

levels of entrepreneurial activity among the poorer segments of the 

population? Is that correct? Did you reach that conclusion? 

Going back to the question of the payday lending, I found the 

comment of my colleague to be interesting because indeed I have 

found a number of my own constituents who find payday lending 

to be a far superior alternative to paying fees, late fees on credit 

cards, and bounced check fees, and reconnection fees, and the rest. 

Ms. Saunders, I believe in your testimony, if I am quoting you 

correctly, ‘‘the essential characteristics of payday loan transactions 

are so different than more traditional forms of credit that the payment or nonpayment of these liabilities is simply not relevant to 

whether a consumer will pay a credit card bill or traditional car 

loan.’’ I am reading from your testimony. 

If you would accept the proposition that the thin file is a challenge for any underserved populations, why would you deny me—

or maybe you would not, but if I am in the business of extending 

credit and I have one individual who has no credit history whatsoever and I have another individual who I see over the course of 2 

years has taken out seven payday loans and has repaid each and 

every one on time, it seems to me—and you might disagree, but we 

30

could have a logical disagreement—I might consider that to be predictive behavior of one’s credit worthiness. 

Are you advocating a policy that would deny me that right as one 

who is in the business of extending credit? 

Ms. SAUNDERS. I am simply advocating a policy of ensuring that 

the information that the creditor receives relating to your ability to 

make the repayment is relevant. 

I would posit the theory that whether a particular consumer repays payday loans or not is probably not relevant. I leave it to my 

colleagues around the table to prove me wrong. If it is in fact entirely predictive that a payday loan consumer will repay or will not 

repay based on traditional credit, based on how they have used 

payday loans, then I may be wrong. 

My analysis and our kind of uniform analysis among the consumer groups is that it would not be predictive, but I may be 

wrong. I have been wrong before; I hate to admit it. 

Mr. HENSARLING. But regardless of the relevance or irrelevance, 

would you advocate the policy denying me that right? 

Ms. SAUNDERS. I would advocate the policy simply of ensuring 

relevance. That is the policy I want. 

Mr. HENSARLING. I seem to be out of time. Thank you. 

Mr. CASTLE. Thank you, Mr. Hensarling. 

Mr. Ford is recognized for 5 minutes. 

Mr. FORD. Just to follow up on a lot of questioning from my 

friend, any sense, real quick, of the profile of those who take out 

payday loans? 

Because I think the point my colleague made is interesting. I 

think most people who do, there is a perception that they have to 

be black and poor. And I think your point was that that is not the 

case, but the reality is, I do not think that the profile that my colleague has painted is necessarily an accurate one. Most people who 

go get payday loans are people who cannot get help from traditional sources. 

Although maybe the payday loan industry hopes it evolves to 

that point that you have envisioned, Congressman, I do not think 

that is the case at the moment. Maybe Ms. Nelson and others can 

dispute us. I saw her nodding when you raised your question. As 

wonderful a description as it is, I think it is more fictitious than 

it is realistic. 

I would ask the question, Ms. Nelson, you talked about how your 

scores are a solid predictor. I have a bias against what you all do. 

I want to start out before we get going. You say that as much as 

it is a solid predictor, you all do not have much control over what 

lenders do. 

Do you think you have any responsibility as to what lenders do, 

since you all developed that score? 

Ms. NELSON. We have a responsibility to help them understand 

what the score is predicting. 

Mr. FORD. Right. But we know that there are abuses, and you 

do not think that you have any responsibility to address it? 

I think the question that my colleague asked about, you take into 

account. Mr. Thomas was kind enough to say that it is done on an 

individual basis if it is a good point that a consumer may have 

about why they were late making a payment. 

31

But you all do not take any kind of systematic approach to this 

in terms of accounting for differences in prices and the fact that 

someone may hit a hard time. 

I am of the opinion that you all could do a better job than you 

do. It is easy to put the score out there and say, ‘‘We have nothing 

to do with it now.’’ You know what it is used for. You know how 

it is used. 

We voted on bankruptcy reform here in the Congress a while 

ago, and I voted for it because I did not think the credit card companies or others should be responsible fully for this. I think all of 

you all are responsible in some ways, and we have to start at the 

root and work our way across. 

But you do not think you have any responsibility to adjust when 

you know lenders are using it in ways that it should not be used 

or using it in ways that hurt consumers? 

Ms. NELSON. We have an obligation, first and foremost, to make 

sure that lender has permissible purpose to use the score. 

In terms of our ability to systematically adjust the score based 

on qualitative information about the consumer, it is virtually impossible. That is why the score is used as part of a decision process 

by any lender. I do not think that we should make the assumption 

that the score is the one and only aspect of the decision. 

Mr. FORD. How often do you think it is the one and only aspect? 

Ms. NELSON. It is the first aspect for the automated process. 

Now most of the customers that we work with, and Ms. Thomas 

is a terrific example, have manual underwriting processes so that 

if a consumer kicks out of that automated process for whatever reason, if the score is too low, or if there are other risk elements that 

makes that lender uncomfortable, that then moves into a manual 

underwriting process, both from a lender perspective, as well as if 

you talked to the GSEs. 

So our role in the process is really to help automate as much of 

the decisioning as we can, to streamline the process, bring out cost. 

Then once you have consumers that go outside of that automated 

process, we are absolutely supportive of manual intervention. 

Mr. FORD. But you do not apply any pressure for them to do any 

of that. You just provide the score. However they choose to respond 

to it, if you have good actors like Ms. Thomas or bad actors, or medium-level actors, you all do not really put any pressure on anybody. You just release the score. 

Ms. NELSON. I would say that is correct simply because I do not 

know what pressure we have on our customers to be able to influence their individual business practices. 

Mr. FORD. No, I did not ask if you could develop a kind of pressure point. I was just curious. You all do not do anything other 

than just provide the scores. 

Ms. NELSON. Correct. 

Mr. FORD. You are aware that sometimes the scores are used in 

ways that there are some good actors who are using it, as you cite 

Ms. Thomas’s practices, and there are people who use it in a bad 

way. 

So you are aware that there is a variance in how the scores can 

be used and how some people will use the score not as the only factor but as part of a set of considerations. 

32

Ms. NELSON. I cannot say that I am aware of any specific examples like that, no. 

Mr. FORD. You just said Ms. Thomas uses it for certain purposes. 

Ms. NELSON. All I am saying is I would not characterize the fact 

that there is a score as a bad way. So we applaud efforts for lenders that want to go above and beyond the utilization of a score in 

their decisioning process. 

Mr. FORD. Right. So presumably that means it is good if you are 

applauding it. Right? 

Ms. NELSON. And presumably, we believe that most lenders do 

that very thing. 

Mr. FORD. But there are some that do not, and you all have to 

be aware of that too, right? You know some are not doing it, so presumably you would not applaud them. My only point is, I think you 

are more aware of things than you say you are. 

I hope this committee, as we look at nontraditional factors, we 

talk about payday loans. I say to my colleagues, we are one of the 

biggest payday loan users in the world; the United States is. Our 

payday loan folks are called Japan and China. And thank God they 

keep loaning us money to finance the things everybody here puts 

cards out for us to do. 

This is not a partisan thing at all, but of all the people in the 

country to be getting on people about debt, we at the Federal level, 

the United States Congress, trying to tell people how to manage 

their money better when we run $400 billion deficits year-in and 

year-out and a $7.5 trillion national debt is a remarkable thing. 

But God is in the blessing business, and maybe we will figure out 

a way to get out of this mess. 

I hope that we take very seriously what has been said today. I 

do hope that we can find better ways to gauge people’s credit, basing it on how much people pay or if people are able to pay their 

light bills or their phone bills and stuff. 

I mean, we would not do this to rich people in this country. And 

to say to poor people that we are going to develop the system that 

you all are putting together, I think you can do better, and not you, 

but just the whole industry can do a lot better than what you all 

have presented us today. 

I am one person on this committee who will fight tooth and nail, 

Mr. Chairman, to ensure, I do not care what they look like. If they 

are working people, and they are trying to support their families, 

and factors outside of their control are causing costs to go up, they 

should not be saddled with a weak effort like we have heard here 

today. We should come up with a better way to determine these 

things. Whether you live in Delaware or Texas or Tennessee, and 

whether you are Democrat or Republican, there has to be a better 

way to do this. 

Ms. Nelson, I did not mean to jump on you, but I think if you 

all applaud certain practices, you ought to figure out a way to encourage those practices. It is the only fair way to do it. We do it 

here in the Congress, and you all should be expected to do it in the 

private sector as well. 

Mr. CASTLE. Thank you, Mr. Ford. 

Mr. McHenry is recognized for 5 minutes. 

Mr. MCHENRY. Thank you, Mr. Chairman 

33

This is mainly directed at Ms. Nelson, but I would love to have 

the whole panel chime in if you feel so led. 

It is interesting to me that we are debating sort of a regulatory 

scheme for the marketplace of credit. It seems to me that especially 

your company, Ms. Nelson, you are in a position where you are trying to have, I would say, a market advantage, that maybe your system of scoring is more accurate for institutions to use, that you are 

a better predictor of someone’s credit worthiness. 

Is that your business, would you say? 

Ms. NELSON. Obviously, the Fair Isaac business has been built 

around the development of credit scores. 

What I came here specifically to talk about was the creation of 

a sister service called expansion score, which takes in the best alternative credit data available in the marketplace today for the 

purposes of helping to score those consumers that previously could 

not get a traditional score. 

So when we talk about regulatory framework, we sit perfectly inside the regulatory framework that exists today to ensure accuracy 

and completeness of data and, therefore, solid scores that can be 

developed from that data to predict the likelihood of credit risk for 

any individual consumer. 

Mr. MCHENRY. But there are many institutions that are doing 

exactly what you are doing. There is a choice that businesses can 

make to use your exact business rather than another’s. 

Ms. NELSON. Correct. We are one option of many. And you have 

heard today Ms. Thomas talking about the processes they go 

through to evaluate whether or not they can extend a mortgage to 

a consumer. Mr. Catone has explained the same thing. 

So what the unique element of the service that we bring is that 

we are trying to help the industry automate all of this, so Mr. 

Catone is able to generate one-by-one consumer reports or nontraditional credit reports for any consumer that is applying for a 

mortgage. 

What we are trying to do is supplement that with an automated 

process that is going out and, at a macro level, finding data providers that have that positive information that we can pull together 

and generate a score. I think the clear difference here is that we 

are very supportive of all the other efforts. You could almost look 

at this expansion score as a first step. 

So if we are able to find information about checking accounts or 

payment plans where there is a lot of positive information, we are 

able to generate a score that is high enough for that lender to feel 

comfortable. It is a first step. It can either be used as a big piece 

of the decision or an indicator for the decision to move on and invest in the creation of a full-blown nontraditional credit report. 

Mr. MCHENRY. But it is the marketplace there which you are responding to. Is that correct? 

Ms. NELSON. Absolutely, absolutely. 

Mr. MCHENRY. Is there a regulatory framework that is holding 

you back in providing more accurate scores and a more accurate 

prediction of credit worthiness that perhaps Bank of America, let’s 

say, needs, that they would like to have this additional information—

Ms. NELSON. Right. 

34

Mr. MCHENRY. —So they could extend credit? 

Ms. NELSON. If you look at a classic or a traditional credit score, 

typically I believe the average is maybe 13 credit lines feed into 

that score. Within the expansion score, we have a much lower number of alternative credit data sources or data points. 

And so, as we gain more and more alternative credit data to be 

made available to all of us in the industry, it is going to enhance 

our ability to get that score to be refined further and further for 

the consumers. 

So when you ask, is there a barrier, right now our barrier is trying to find those alternative credit sources to continue building and 

building the value of the score and the report that we are able to 

provide, which would then allow much more automation and efficiency in the process than having to go through the manual systems today on each and every one. 

It does not displace the need for the manual reviews, but it allows a lot more of those consumers to pass through the system 

without having to go through the cost of the manual reviews. 

Mr. MCHENRY. Dr. Turner, it looks as though I was going to you 

next. 

Can you describe the marketplace forces that are driving the direction that we are trying to go in here, with actually providing 

more information to extend credit? 

I think there is a great failure in Congress to understand that 

there is a marketplace, and the marketplace will drive innovation. 

The marketplace will drive a great advance in extending credit in 

many different things. 

We had a hearing just not too long ago about data security, and 

I think there is a marketplace for companies such as Bank of 

America. Bank of America has this wonderful commercial that describes the accuracy of their check processing and their innovation 

there and the accuracy by which the process the checks. 

I just think we need to look at what the marketplace is driving 

toward, and is there a barrier that government is imposing through 

regulatory schemes or laws or whatnot that are actually holding 

back this process of innovation. 

Mr. TURNER. There are several questions there. 

Our study touches on some barriers that impede these flows. We 

talk about two economic barriers and two regulatory barriers. We 

surveyed about 25 State regulatory commissions, and we are only 

aware of regulatory barriers that forbid the onward transfer of telephone, wireless, wireline, electric, water, utility data in two States. 

So it is about 8 percent. 

We have no reason to expect the balance in the remaining 25 

States that that number would be markedly higher. Those prohibitions were not expressly for preventing credit reporting. They had 

different purposes. 

So I do not see a substantial regulatory barrier in the States or 

federally. What is more important that in preventing this is the 

regulatory uncertainty. Utility companies want to report the data. 

One of the market forces driving them is cash flow. They have 

high delinquency and default rates. Reporting payment history is 

a disciplining mechanism. It improves cash flow. So they have a 

powerful market incentive that is driving the demand for this data. 

35

But they cannot report the data, the utility companies, because 

their regulators will not give them written permission to do so, 

even though there is nothing statutory that prohibits them from 

sharing the data. 

So yes, there are barriers, but they are more indirect and soft 

barriers than direct. 

Other market forces, and I think that my panelists got to this 

as well, there is a lot of this information that is gathered already. 

If you look at the mortgage insurance industry, mortgage insurers 

gather vast amounts of alternative data for use in underwriting decisions about mortgage loans. They collect data we have not even 

discussed here. They collect the presence of children, truancy 

issues. They manually verify all of this data. 

If there were a company or several companies that were able to 

systematically gather this data and then provide it to those who 

want it for their decisioning processes, that is an unmet need. It 

would be a tremendous efficiency for the mortgage insurers, for instance. 

So there are market forces compelling the collection of this data 

on a variety of different levels and a variety of different directions. 

Mr. MCHENRY. Thank you. 

Mr. CASTLE. Thank you, all. 

Thank you, Mr. McHenry. 

Ms. Maloney is recognized for 5 minutes. 

Mrs. MALONEY. Thank you. 

And I thank all the panelists for being here today and for your 

testimony. 

One fact that many consumers are not aware of is having more 

than one credit card or two or three credit cards lowers your credit 

rating. This is particularly a challenge with young people or many 

people. 

They walk into stores. I represent New York. It is a large retail 

base. The Fair Credit Reporting Act was tremendously important 

to the city that I represent and to our economy for institutions to 

be able to have a Federal standard so they could make decisions 

and allow credit. 

But a side of it, and I would like to ask Bank of America, Ms. 

Thomas, consumers are not aware of this. Many promotions are always there. You can go into a store in my city or probably anywhere in this country and they will say, take out a credit card and 

we will give you 20 percent off; we will give you $100 if you spend 

$300 and take our credit card; we will give you $50—I mean, all 

of these promotions to entice consumers to have credit cards. In 

many cases, they may use the credit card just once, yet it remains 

on their credit file and lowers their credit rating. 

As a source of credit cards, what is your comment on it? Should 

we notify consumers that having more credit cards lowers their 

credit rating? By the time they try to buy a car or an apartment 

or whatever, their credit rating is ruined because they have 10 or 

20 or 30 credit cards. 

Ms. THOMAS. One of the ways that we try to address that is 

through consumer education. We do a lot of financial literacy at the 

school and college level. 

36

In talking to a college student who says they have 12 credit cards 

for emergencies, and you ask, what is the emergency? And it is to 

buy a dress to go to a party. That shows us lack of the education. 

So that is one way, not only college students, but other adults 

who also have the same issue. It is just continuous education is the 

best way, but it is still not enough. There is still more that needs 

to be done in that space. 

Mrs. MALONEY. Do you think we should require better disclosure 

of this adverse consequence on credit cards so that people could be 

notified when they are applying? 

You do not even have to apply for a credit card in New York. 

They are practically hawking them on you. You get them in the 

mail. They mail them to you. In literally every store, you can go 

into a gum shop store, and they have their own credit card. 

So do you think if we required better disclosure: ‘‘Congratulations, you have this credit card, but please be aware that if you 

have more than three credit cards, your credit rating will be lowered.’’

Ms. THOMAS. I do not know that it should be a requirement. I 

think it needs to be an awareness that is continuously done so people know that that is a problem, because you are right. Most people 

do not know. 

Mrs. MALONEY. I would like to ask the credit agencies—and we 

all have challenges in our work. Ms. Nelson and Mr. Catone, could 

you clarify for me what is the procedure in the credit agencies? And 

why is it a decision to lower credit if someone has 10 cards? If a 

consumer has 10 cards and they have totally paid off the debt so 

they have no debt, why do you lower the credit card rating? 

This was an issue in the Fair Credit Reporting Act. We became 

aware that you could have had a credit card for 10 years, maybe 

used it once, paid off the debt, but still your rating would be lowered if you had more, I believe, than three cards. 

Could you clarify what the standard is? 

To me, I think when you are looking at credit, you want to know 

what the person’s payment schedule is and what the debt is. So if 

a person had 100 cards and they paid off all their debt, why are 

you lowering the credit rating on them? 

I was told the standard was three cards, and then you lower the 

credit standing, but maybe you could clarify our understanding of 

it. 

Mr. CATONE. Maybe Ms. Nelson can clarify one part of that. 

There are two pieces here. One is the alternative data or the 

nontraditional data. Many underwriting standards allow compilation of payment pattern history, one being credit cards or utility 

data, rent data, whatever. These underwriting standards in the 

mortgage industry at least have been very, very different than the 

traditional. You see that Fair Isaac has come out with a different 

score for that application. 

I think what you are referring to is the existing type of scoring 

mechanisms that have been in the marketplace and are in wide use 

today, if I am not mistaken. And that is a more general issue. So 

there are two here. 

37

Mrs. MALONEY. Okay. I would like to understand how the credit 

agencies create their credit scoring as it applies to the number of 

credit cards that you have. Could you answer that? 

I was told by a credit agency when one of my constituents called, 

that if anyone had over three credit cards, their credit scoring was 

lowered. Is that true? 

Ms. NELSON. I cannot say specifically if it is true or false, but I 

can tell you that more important than the number of cards possessed by a consumer is what degree of debt have they consumed 

on those cards. So if I have three cards and they are all maxed out, 

it is a very different scenario than having three that are not in use. 

Right? 

Mrs. MALONEY. The example that I am using is every credit card 

is paid off completely at the end of the month. There are 10 credit 

cards that the consumer has not even used in 10 years. They used 

them in college. Ten years later, they are not using them. They are 

still on their credit report, and just the mere fact that they have 

the credit cards lowers their score, even though it has been paid 

off completely. Consistently for 10 years, there has been no debt on 

those credit cards. I was told that it lowers the credit scoring. 

Can you clarify that? If you cannot do that today, would you get 

back to us in writing? 

Because I have heard it three or four times from constituents 

who are stunned when they finally go to get a credit score that 

they have a low score, although they have no debt, make a lot of 

money, always pay their debt, always pay the credit card off at the 

end of the month, only use one of them. Yet just the mere fact that 

from their college days or whatever or because there was a promotion that gave them 20 percent off or whatever, they have a terrible credit score. 

I think that that is a problem, and people should be aware of it, 

and they are stunned to find out about it, and I was stunned to 

find out about it. 

Ms. NELSON. And that is exactly what I will do. I will go back 

and get specific information around that question of number of 

cards. I cannot tell you specifically today how it would, if at all, affect a score, but I will gladly research that and get back to you. 

Mr. CASTLE. Thank you. 

Thank you, Ms. Maloney. 

Mrs. MALONEY. Okay. 

Mr. CASTLE. Mr. Clay is recognized for 5 minutes. 

Mr. CLAY. Thank you, Mr. Chairman. 

And I thank the panel for participating today. 

Getting access to credit at reasonable rates is one of the more 

difficult tasks faced by minorities, women, moderate-and low-income workers, and immigrants. Credit agencies cite that there is 

insufficient credit history using traditional data in a majority of the 

cases. 

Do we have conclusive evidence that employing the use of nontraditional credit information is effective in dealing with minorities’ 

problems of limited access to credit? And how effective is the use 

of these? And what do we compare the results to? 

Anybody can tackle it. 

38

Ms. THOMAS. What we see at Bank of America is that there are 

individuals that we would have otherwise declined because they 

did not have enough credit that we can say yes to because we are 

trying to figure out, within reason, because you do not want to put 

somebody in a home they cannot keep, because it is not about getting a loan, it is about keeping it. 

But if we did not utilize some of the nontraditional data, we 

would have to say no. And if a person has demonstrated good payment behavior, then that is a way of getting them into that home. 

Mr. CLAY. Well, how reliable is the use of nontraditional data in 

determining payment behavior patterns or any other credit-related 

behavior? What suggestions do you have to address this problem? 

Ms. THOMAS. In terms of reliability? 

Mr. CLAY. Yes. 

Ms. THOMAS. Because the process is so variable from customer 

to customer and type of alternative credit you would use, we have 

seen some data that shows good behavior, especially around rental 

data, but other types of data, there is still more analysis to be 

done, and we only do it on such a limited basis because there is 

such variability in it. 

Mr. CLAY. Well, how about young people just starting their jobs, 

careers? How do you gauge whether they are worthy of a home 

loan or worthy of a credit card? Do you take in extenuating circumstances, other factors to determine that? 

Ms. THOMAS. For a young person just starting out—because I 

had several people on my staff under 30, which was good learning 

for me—they may have been paying rent to a parent, and they 

could demonstrate it, or they were paying rent on an apartment. 

So that is an example of one. They may have one credit card. Some 

have a bunch, and we worked on those. 

So that is data we can use, but they typically will be a thin file 

because they do not have enough, but it is the same thing. They 

can demonstrate payment history. 

Mr. CLAY. Ms. Thomas, let me ask you, some young people that 

come right out of college are heavily indebted with student loans. 

Do you ever give consideration to them as far as purchasing a 

home and then rolling that student loan into the mortgage? 

Ms. THOMAS. We give consideration to that, but if we see where 

there is a severe struggle with doing that, along with other debt, 

oftentimes what we will do is refer that young person to some credit counseling. They do not have to take it, but we want to get them 

in better shape now so that they can continue to progress not only 

with that mortgage, but other things as well. 

So sometimes we can say yes. Sometimes we have to refer them 

and hope they will come back after we have educated them. 

Mr. CLAY. I see, after they have accumulated some time and 

credit history. 

Ms. THOMAS. And understand what they can do to improve their 

situation. 

Mr. CLAY. Thank you for your response. 

Mr. Catone, how do you view the use of such nontraditional credit score such as the FICO expansion score and the instant-merge 

credit reports? How do each of them reach their targeted consumer 

39

groups? Are the programs having a major impact on helping consumers get better access to credit? 

Mr. CATONE. What I want to point out is that the financial services industry is very automated today. There is a heavy investment 

in technology, process, and things to make it very economical and 

fast to underwrite a consumer for any financial instrument. 

In cases where there is obviously not enough data and things of 

this nature, it falls into a special category. As the other panelists 

have noted, it goes into a manual process. It takes longer. It is 

more difficult. The consumer does not understand these things. 

So there are a variety of underwriting criteria depending on the 

program, Bank of America’s program or what have you, that override and can adjust for different types of situations, credit counseling being one of those; other types of payment history data being 

those types as well. 

So I think you have to look at the underwriting standards that 

are in the industry today, specifically counseling. There are many 

studies out that have proven that pre-home purchase counseling 

contributes to the integrity of being able to repay that loan and 

budget and things of this nature. 

Mr. CLAY. Thank you for that response. 

Thank you, Mr. Chairman. 

Mr. CASTLE. Thank you, Mr. Clay. We appreciate your being here 

and appreciate your questioning. 

We are going to bring this to a close. We appreciate all the panelists being here and for answering our questions. 

It is possible that some of the members may have additional 

questions for the panel which they will submit in writing to you in 

the course of the next 30 days. I do not know how likely that is; 

nobody has seemed to opine that way today, but that could possibly 

happen. 

So with that, I declare this hearing adjourned. 

And thank you again for being here. 

[Whereupon, at 12:06 p.m., the subcommittee was adjourned.] 

(41)

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May 12, 2005

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