[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
25-389 WASHINGTON : 2005
_____________________________________________________________________________
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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
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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
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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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