[House Hearing, 109 Congress]
[From the U.S. Government Publishing Office]




 
                        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



                    U.S. GOVERNMENT PRINTING OFFICE
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                 HOUSE COMMITTEE ON FINANCIAL SERVICES

                    MICHAEL G. OXLEY, Ohio, Chairman

JAMES A. LEACH, Iowa                 BARNEY FRANK, Massachusetts
RICHARD H. BAKER, Louisiana          PAUL E. KANJORSKI, Pennsylvania
DEBORAH PRYCE, Ohio                  MAXINE WATERS, California
SPENCER BACHUS, Alabama              CAROLYN B. MALONEY, New York
MICHAEL N. CASTLE, Delaware          LUIS V. GUTIERREZ, Illinois
PETER T. KING, New York              NYDIA M. VELAZQUEZ, New York
EDWARD R. ROYCE, California          MELVIN L. WATT, North Carolina
FRANK D. LUCAS, Oklahoma             GARY L. ACKERMAN, New York
ROBERT W. NEY, Ohio                  DARLENE HOOLEY, Oregon
SUE W. KELLY, New York, Vice Chair   JULIA CARSON, Indiana
RON PAUL, Texas                      BRAD SHERMAN, California
PAUL E. GILLMOR, Ohio                GREGORY W. MEEKS, New York
JIM RYUN, Kansas                     BARBARA LEE, California
STEVEN C. LaTOURETTE, Ohio           DENNIS MOORE, Kansas
DONALD A. MANZULLO, Illinois         MICHAEL E. CAPUANO, Massachusetts
WALTER B. JONES, Jr., North          HAROLD E. FORD, Jr., Tennessee
    Carolina                         RUBEN HINOJOSA, Texas
JUDY BIGGERT, Illinois               JOSEPH CROWLEY, New York
CHRISTOPHER SHAYS, Connecticut       WM. LACY CLAY, Missouri
VITO FOSSELLA, New York              STEVE ISRAEL, New York
GARY G. MILLER, California           CAROLYN McCARTHY, New York
PATRICK J. TIBERI, Ohio              JOE BACA, California
MARK R. KENNEDY, Minnesota           JIM MATHESON, Utah
TOM FEENEY, Florida                  STEPHEN F. LYNCH, Massachusetts
JEB HENSARLING, Texas                BRAD MILLER, North Carolina
SCOTT GARRETT, New Jersey            DAVID SCOTT, Georgia
GINNY BROWN-WAITE, Florida           ARTUR DAVIS, Alabama
J. GRESHAM BARRETT, South Carolina   AL GREEN, Texas
KATHERINE HARRIS, Florida            EMANUEL CLEAVER, Missouri
RICK RENZI, Arizona                  MELISSA L. BEAN, Illinois
JIM GERLACH, Pennsylvania            DEBBIE WASSERMAN SCHULTZ, Florida
STEVAN PEARCE, New Mexico            GWEN MOORE, Wisconsin,
RANDY NEUGEBAUER, Texas               
TOM PRICE, Georgia                   BERNARD SANDERS, Vermont
MICHAEL G. FITZPATRICK, 
    Pennsylvania
GEOFF DAVIS, Kentucky
PATRICK T. McHENRY, North Carolina

                 Robert U. Foster, III, Staff Director
       Subcommittee on Financial Institutions and Consumer Credit

                   SPENCER BACHUS, Alabama, Chairman

WALTER B. JONES, Jr., North          BERNARD SANDERS, Vermont
    Carolina, Vice Chairman          CAROLYN B. MALONEY, New York
RICHARD H. BAKER, Louisiana          MELVIN L. WATT, North Carolina
MICHAEL N. CASTLE, Delaware          GARY L. ACKERMAN, New York
EDWARD R. ROYCE, California          BRAD SHERMAN, California
FRANK D. LUCAS, Oklahoma             GREGORY W. MEEKS, New York
SUE W. KELLY, New York               LUIS V. GUTIERREZ, Illinois
RON PAUL, Texas                      DENNIS MOORE, Kansas
PAUL E. GILLMOR, Ohio                PAUL E. KANJORSKI, Pennsylvania
JIM RYUN, Kansas                     MAXINE WATERS, California
STEVEN C. LaTOURETTE, Ohio           DARLENE HOOLEY, Oregon
JUDY BIGGERT, Illinois               JULIA CARSON, Indiana
VITO FOSSELLA, New York              HAROLD E. FORD, Jr., Tennessee
GARY G. MILLER, California           RUBEN HINOJOSA, Texas
PATRICK J. TIBERI, Ohio              JOSEPH CROWLEY, New York
TOM FEENEY, Florida                  STEVE ISRAEL, New York
JEB HENSARLING, Texas                CAROLYN McCARTHY, New York
SCOTT GARRETT, New Jersey            JOE BACA, California
GINNY BROWN-WAITE, Florida           AL GREEN, Texas
J. GRESHAM BARRETT, South Carolina   GWEN MOORE, Wisconsin
RICK RENZI, Arizona                  WM. LACY CLAY, Missouri
STEVAN PEARCE, New Mexico            JIM MATHESON, Utah
RANDY NEUGEBAUER, Texas              BARNEY FRANK, Massachusetts
TOM PRICE, Georgia
PATRICK T. McHENRY, North Carolina
MICHAEL G. OXLEY, Ohio


                            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


                        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.
    Consumers in the United States have more ready access to 
low-cost 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.]
    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.''
    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.
    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.
    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 
broad-based 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.
    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.
    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 well-defined 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, effectively 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 
one-third 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.
    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 first-time 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 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.
    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 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 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 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 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.
    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 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, insurance, 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. 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 industry-wide. 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.
    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 different 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 concerned 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 debt-free. 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?
    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 part-time 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.
    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?
    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 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.
    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 African-American 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 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 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.
    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.
    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
    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.
    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.
    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.
    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.
    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.
    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 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.]


                            A P P E N D I X



                              May 12, 2005


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