[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 _____________________________________________________________________________ For Sale by the Superintendent of Documents, U.S. Government Printing Office Internet: bookstore.gpo.gov Phone: toll free (866) 512-1800; (202) 512�091800 Fax: (202) 512�092250 Mail: Stop SSOP, Washington, DC 20402�090001 HOUSE COMMITTEE ON FINANCIAL SERVICES MICHAEL G. OXLEY, Ohio, Chairman JAMES A. LEACH, Iowa BARNEY FRANK, Massachusetts RICHARD H. BAKER, Louisiana PAUL E. KANJORSKI, Pennsylvania DEBORAH PRYCE, Ohio MAXINE WATERS, California SPENCER BACHUS, Alabama CAROLYN B. MALONEY, New York MICHAEL N. CASTLE, Delaware LUIS V. GUTIERREZ, Illinois PETER T. KING, New York NYDIA M. VELAZQUEZ, New York EDWARD R. ROYCE, California MELVIN L. WATT, North Carolina FRANK D. LUCAS, Oklahoma GARY L. ACKERMAN, New York ROBERT W. NEY, Ohio DARLENE HOOLEY, Oregon SUE W. KELLY, New York, Vice Chair JULIA CARSON, Indiana RON PAUL, Texas BRAD SHERMAN, California PAUL E. GILLMOR, Ohio GREGORY W. MEEKS, New York JIM RYUN, Kansas BARBARA LEE, California STEVEN C. LaTOURETTE, Ohio DENNIS MOORE, Kansas DONALD A. MANZULLO, Illinois MICHAEL E. CAPUANO, Massachusetts WALTER B. JONES, Jr., North HAROLD E. FORD, Jr., Tennessee Carolina RUBEN HINOJOSA, Texas JUDY BIGGERT, Illinois JOSEPH CROWLEY, New York CHRISTOPHER SHAYS, Connecticut WM. LACY CLAY, Missouri VITO FOSSELLA, New York STEVE ISRAEL, New York GARY G. MILLER, California CAROLYN McCARTHY, New York PATRICK J. TIBERI, Ohio JOE BACA, California MARK R. KENNEDY, Minnesota JIM MATHESON, Utah TOM FEENEY, Florida STEPHEN F. LYNCH, Massachusetts JEB HENSARLING, Texas BRAD MILLER, North Carolina SCOTT GARRETT, New Jersey DAVID SCOTT, Georgia GINNY BROWN-WAITE, Florida ARTUR DAVIS, Alabama J. GRESHAM BARRETT, South Carolina AL GREEN, Texas KATHERINE HARRIS, Florida EMANUEL CLEAVER, Missouri RICK RENZI, Arizona MELISSA L. BEAN, Illinois JIM GERLACH, Pennsylvania DEBBIE WASSERMAN SCHULTZ, Florida STEVAN PEARCE, New Mexico GWEN MOORE, Wisconsin, RANDY NEUGEBAUER, Texas TOM PRICE, Georgia BERNARD SANDERS, Vermont MICHAEL G. FITZPATRICK, Pennsylvania GEOFF DAVIS, Kentucky PATRICK T. McHENRY, North Carolina Robert U. Foster, III, Staff Director Subcommittee on Financial Institutions and Consumer Credit SPENCER BACHUS, Alabama, Chairman WALTER B. JONES, Jr., North BERNARD SANDERS, Vermont Carolina, Vice Chairman CAROLYN B. MALONEY, New York RICHARD H. BAKER, Louisiana MELVIN L. WATT, North Carolina MICHAEL N. CASTLE, Delaware GARY L. ACKERMAN, New York EDWARD R. ROYCE, California BRAD SHERMAN, California FRANK D. LUCAS, Oklahoma GREGORY W. MEEKS, New York SUE W. KELLY, New York LUIS V. GUTIERREZ, Illinois RON PAUL, Texas DENNIS MOORE, Kansas PAUL E. GILLMOR, Ohio PAUL E. KANJORSKI, Pennsylvania JIM RYUN, Kansas MAXINE WATERS, California STEVEN C. LaTOURETTE, Ohio DARLENE HOOLEY, Oregon JUDY BIGGERT, Illinois JULIA CARSON, Indiana VITO FOSSELLA, New York HAROLD E. FORD, Jr., Tennessee GARY G. MILLER, California RUBEN HINOJOSA, Texas PATRICK J. TIBERI, Ohio JOSEPH CROWLEY, New York TOM FEENEY, Florida STEVE ISRAEL, New York JEB HENSARLING, Texas CAROLYN McCARTHY, New York SCOTT GARRETT, New Jersey JOE BACA, California GINNY BROWN-WAITE, Florida AL GREEN, Texas J. GRESHAM BARRETT, South Carolina GWEN MOORE, Wisconsin RICK RENZI, Arizona WM. LACY CLAY, Missouri STEVAN PEARCE, New Mexico JIM MATHESON, Utah RANDY NEUGEBAUER, Texas BARNEY FRANK, Massachusetts TOM PRICE, Georgia PATRICK T. McHENRY, North Carolina MICHAEL G. OXLEY, Ohio C O N T E N T S ---------- Page Hearing held on: May 12, 2005................................................. 1 Appendix: May 12, 2005................................................. 41 WITNESSES Thursday, May 12, 2005 Catone, Mark, Senior Vice President, First American Credco....... 7 Nelson, Lisa, Vice President, Business Operations, Fair Isaac Corporation.................................................... 6 Saunders, Margot, Attorney, National Consumer Law Center......... 11 Thomas, Gwen, Senior Vice President, Consumer Real Estate, Bank of America..................................................... 9 Turner, Michael, President and Senior Scholar, Information Policy Institute...................................................... 13 APPENDIX Prepared statements: Oxley, Hon. Michael G........................................ 42 Bachus, Hon. Spencer......................................... 47 Castle, Hon. Michael N....................................... 51 Gillmor, Hon. Paul E......................................... 52 LaTourette, Hon. Steven C.................................... 53 Catone, Mark..................................................... 55 Nelson, Lisa..................................................... 61 Saunders, Margot................................................. 72 Thomas, Gwen..................................................... 87 Turner, Michael.................................................. 92 Additional Material Submitted for the Record Castle, Hon. Michael N.: Community Financial Services Association, position paper..... 102 "First American to Develop New Credit Scores", American Banker, October 14, 2003................................... 104 "Pay Rent, Build Credit, Success Story", Center for Financial Services Innovation........................................ 106 Catone, Mark: Response to questions from Hon. Barney Frank................. 108 Response to questions from Hon. Luis V. Gutierrez and Hon. Deborah Pryce.............................................. 126 Nelson, Lisa:.................................................... Response to questions from Hon. Barney Frank................. 130 Response to questions from Hon. Luis V. Gutierrez............ 138 Thomas, Gwen:.................................................... Response to questions from Hon. Luis V. Gutierrez and Hon. Barney Frank............................................... 139 Turner, Michael:................................................. Response to questions from Hon. Luis V. Gutierrez............ 141 HELPING CONSUMERS OBTAIN THE CREDIT THEY DESERVE ---------- Thursday, May 12, 2005 U.S. House of Representatives, Subcommittee on Financial Institutions and Consumer Credit, Committee on Financial Services, Washington, D.C. The subcommittee met, pursuant to call, at 10:03 a.m., in Room 2128, Rayburn House Office Building, Hon. Spencer Bachus [chairman of the subcommittee] presiding. Present: Representatives Bachus, Castle, Ryun, Hensarling, Brown-Waite, Pearce, Neugebauer, McHenry, Sanders, Maloney, Watt, Sherman, Gutierrez, Moore of Kansas, Waters, Carson, Ford, Baca, Green, Moore of Wisconsin, and Clay. Chairman Bachus. [Presiding.] The Subcommittee on Financial Institutions and Consumer Credit will come to order. Today we are holding a hearing entitled, ``Helping Consumers Obtain the Credit They Deserve.'' As we learned during our recent debates on the Fair Credit Reporting Act, a consumer's credit history can play an important role in his or her ability to obtain credit, as well as the price of the credit offered. However, we also learned that many consumers who pay their bills on time may not have sufficient information in their credit reports demonstrating their credit worthiness. This is due to the fact that not all companies provide payment history information to credit bureaus. Today's hearing will provide us a forum in which we can explore the type of information that may be valuable in the credit underwriting process, but that are underreported to credit bureaus. We may also identify any structural barriers that may hinder the reporting of such information. Generally, we want to learn more about how we can improve consumers' credit options, especially for those consumers who are low or moderate income. This committee has demonstrated time and time again a dedication to ensuring that all American consumers maintain a level of access to financial services and products that is unrivaled anywhere in the world. Today's hearing further demonstrates this commitment. I want to particularly thank Chairman Castle for requesting this hearing, and I commend him for his leadership in this area. Consumers in the United States have more ready access to low-cost credit than consumers anywhere else in the world. This is due in large part to public policies that support the pooling and sharing of consumer credit data. The availability to lenders of complete and accurate data on past consumer borrowing behavior is considered essential to an efficient credit market. Despite the enormous growth in the U.S. credit market, many consumers still experience difficulty obtaining adequate consumer credit because they have little or no credit history. I understand it is estimated that as many as 55 million Americans do not have sufficient credit history for a lender to accurately determine their true risk of default. Many of these consumers may be making timely payments on various monthly or contractual obligations. However, these payments are often going unreported to the credit reporting agencies. For example, many landlords do not report information to credit bureaus, so a renter's credit history will not necessarily reflect the fact that the consumer is paying regularly. The same can be said for some utility companies, cable companies, and telecommunications companies. If a consumer does not have significant amounts of information in his credit report, that consumer is said to have a ``thin file,'' making it difficult for creditors to assess his credit worthiness. Consumers in low-and moderate-income households may be more likely to have thin files because they do not have mortgages or other forms of traditional credit that show up in credit reports. Therefore, a low-income renter may find himself in a vicious cycle of not having adequate low-cost credit available because he or she has not had access to credit in the past. We need to explore whether the information that could be provided by landlords, utilities, phone companies, cable companies and others to credit bureaus can be valuable in the underwriting process. For example, would a creditor be more likely to grant a mortgage to a consumer if the creditor knew that the consumer faithfully and diligently paid his or her phone bill each month? I also look forward to learning more about why certain types of companies do not report information to credit bureaus. Is it too expensive? Are there other barriers? Are there other motivations? Is there too much liability involved? It is my hope today's hearing will allow us to explore ways in which the use of alternative data not currently reported to credit bureaus may benefit millions of Americans that either do not currently have a credit score or little information in their credit file. Let me again thank Mr. Castle for his leadership on this issue. He is strongly committed and I admire his dedication to ensuring that the underserved have access to the low-cost credit they need and deserve. The Chair now recognizes the ranking member of the subcommittee, Mr. Sanders, for any opening statement that he wishes to make. [The prepared statement of Hon. Spencer Bachus can be found on page 47 in the appendix.] Mr. Sanders. Thank you, Mr. Chairman, and thanks for holding this important hearing. The title of our hearing is ``Helping Consumers Obtain the Credit They Deserve.'' I think the hearing title is very appropriate and important, but I would add a caveat. And that is, while we should be helping consumers obtain the affordable credit they deserve, the truth of the matter is that in too many instances these days, more and more consumers, whether they are college students without jobs, seniors on fixed incomes, low-and middle-income families, are gaining access to credit, but from predatory lenders, payday lenders, rent-to-own companies, used-car salesmen, subprime lenders, retailers, and credit card companies that they cannot afford. They are being ripped off. I think this committee has the obligation to deal with this reality that millions and millions of consumers--and I do not know the more gentle word to use, but the reality is they are being ripped off by sky-high fees and outrageous interest rates. I think people all over this country understand that. Let's just take a look at credit cards. Each and every year, credit card companies put 5 billion applications in the mail to consumers. Mr. Chairman, do you know that 5 billion--I tell that to people and they cannot believe it. That is an astronomical number. But 5 billion credit card applications go out. I have often stated I think my family receives about half of them, but that is apparently not the case. Your family may get the other half. I do not know, but there are a lot of them. Consumers are now over $2 trillion in debt, while for 5 consecutive years in a row credit card companies made record- breaking profits, and their CEOs in some cases earned hundreds of millions of dollars in compensation. I think, Mr. Chairman, this is an issue we should be focusing on. Credit card companies alone collected over $21 billion in fees last year, compared to only $7.3 billion in 1994. So the whole issue of fees and the kinds of very high fees that they are charging is something this committee, in my view, should look at. Revenue from late and penalty fees has jumped from $1.7 billion in 1996 to an amazing $11.7 billion today. Over the past 8 years, late fees have risen from $10 to as high as $39, and experts are predicting that late fees could balloon to as high as $50 this year. Today, if consumers are even 1 hour late on credit card bills, they will get slapped with as much as a $39 late fee and a penalty interest rate as high as 29 percent. Predatory lending abuses cost consumers over $9 billion a year. Mr. Chairman, as you may know, I am not a great fan of Newt Gingrich, but here is what his former aide and bankruptcy expert Robert R. Weed had to say about this subject in a front- page story that appeared in the Los Angeles Times. He said, ``Most of the credit card companies that end up in bankruptcy proceedings have already made a profit from the companies that issued them. That is because people are paying so many fees that they have already paid more than was originally borrowed.'' Mr. Chairman, as 1.6 million Americans filed for bankruptcy last year, many paid more in credit card fees than they originally borrowed in the first place. I think this has got to stop. To address these concerns, I have introduced H.R. 1619, the Loan Shark Prevention Act, to protect consumers against predatory lending. Specifically, this legislation would, one, cap interest rates at 8 percent above what the IRS charges income tax deadbeats. Currently, the cap would be about 14 percent, the same level that the Senate approved by a 74-to-19 vote in an amendment offered by then-Senator Al D'Amato in 1991. So we would like to do what Mr. D'Amato pushed for in 1991. Number two, it would cap bank and credit card fees at $15. Number three, ban the credit card interest rate bait and switch. As you know, Mr. Chairman, credit card companies are doubling or tripling interest rates on consumers even though they always paid their credit bills on time. I think all over America, people regard that as just extremely unfair. People paid their credit card bills on time. The companies should not be allowed to double or triple interest rates. Loan-sharking is an odious practice, whether it is performed by street corner thugs or the CEOs of large banks. Charging economically vulnerable Americans outrageous interest rates and fees is simply not acceptable. Amid all the recent political discussion over values, this certainly does not constitute moral behavior. So, Mr. Chairman, let us keep in mind when we are talking about helping consumers obtain the credit they deserve, that it must be affordable credit. I thank the Chair for holding this hearing, and I look forward to working with him. Chairman Bachus. Thank you, Congressman Sanders. Obviously, some of those numbers are disturbing. It is certainly not good news for American consumers. Mr. Castle? Mr. Castle. Thank you very much, Chairman Bachus, for holding this hearing. I appreciate it. Also thanks to Ranking Member Sanders, Newt Gingrich's new best friend, for being here today and his statements on this. He has always been interested in these subjects. I would also like to thank Chairman Oxley and Chairman Bachus for working with me on bringing this issue before the committee. Obviously, I believe it is an important one that warrants further discussion. Today, more people have access to credit than ever before. However, there are indications that some Americans--the young, minorities, and recent immigrants in particular--are not truly engaged in this competitive marketplace because they have little or no existing credit history for which lenders can assess risk and offer credit. As our witness Dr. Turner states in his recently released report, ``Giving Underserved Consumers Better Access to the Credit System,'' there are an estimated 35 million to 50 million American borrowers who do not have credit scores, bank accounts, or whose files have too little information to be used in allocating credit. I feel there is information, such as rent and utility payments, that is not currently reported to the credit reporting agencies that could be helpful to consumers. For example, if an individual pays their rent on time each month, there is no transmission of this information to the credit reporting agencies. Conversely, individuals with mortgages do receive credit for paying their obligation on time, and this further adds to their credit score and history. Mr. Chairman, that raises a question. If people regularly meet their contractual obligations for a variety of services, why should that responsible behavior not be taken into account and used to the advantage of the consumer? Now it could be that the different payments I mentioned may not prove to be predictive of future behavior, and there may be State regulations related to certain utility providers that limits sharing of some of this information. I hope that our witnesses today will help us better understand the predictiveness and value of the data. I am pleased that a number of the panelists will discuss innovative products that the marketplace has developed to better serve the needs of all of our constituents, especially those with thin or no credit history, so they can have access to the best and most competitive offers of credit possible. I would just like to say, one of the goals here is to try to channel consumers into mainstream lending practices, if you will. I tremble sometimes to think of some of the borrowing practices that do go on, be it the use of the credit cards because they cannot get other credit, as Mr. Sanders has mentioned, or obviously some lenders who are out there trying to gouge when the regular lenders, if you will, could perhaps fill the same obligation to these individuals at rates which would be more appropriate. Let me just say this, because I think it is important, and that is that this hearing, as far as I am concerned, is not pursuant to legislation either introduced or to be introduced, so much as it is hopefully an evolving way of looking at consumers. Maybe at some point down the road some form of legislation will be needed. Maybe it will be needed at the State level. But the bottom line is that we are trying to shed a light on practices which a number of our witnesses here have started to watch and hopefully be able to serve a part of our population that is less served now. So I do very much, Mr. Chairman, appreciate the hearing, and I appreciate our witnesses being here. I yield back. [The prepared statement of Hon. Michael N. Castle can be found on page 51 in the appendix.] Chairman Bachus. Thank you, Chairman Castle. At this time, I would like to introduce our witnesses. We have Ms. Lisa Nelson, who is vice president of business operations at Fair Isaac Corporation; Mr. Mark Catone, senior vice president, First American CREDCO; Ms. Gwen Thomas, senior vice president, Consumer Real Estate Branch, Bank of America; and Ms. Margot Saunders, attorney, National Consumer Law Center. You have testified before our committee previously, and we welcome you back. And Dr. Michael Turner, president and senior scholar at the Information Policy Institute. Thank you, Dr. Turner. At this time, we will have our opening statements. Ms. Nelson, if you would go first. Thank you. STATEMENT OF LISA NELSON, VICE PRESIDENT, BUSINESS OPERATIONS, FAIR ISAAC CORPORATION Ms. Nelson. Mr. Chairman and members of the committee, my name is Lisa Nelson. As you have just heard, I am vice president of business operations for Fair Isaac Credit Services, which is a wholly-owned subsidiary of Fair Isaac Corporation. Thank you for the opportunity to testify before you today about Fair Isaac's leadership in the utilization of alternative credit data, specifically as it pertains to the launch of our new product, the expansion score. My comments highlight Fair Isaac's written statement submitted to this committee earlier. Fair Isaac has been providing statistically based credit risk evaluation systems, commonly known as credit scores, since 1960. Today there are many different kinds of credit scores used by thousands of credit grantors. The most well-known are the broad-based credit scores that rely on data provided by the three national credit reporting agencies. We were asked to come before you today to describe how alternative credit data is being used within the lending community to provide access to consumers seeking credit to fulfill their dreams, which might include purchasing a home, obtaining a car loan, or simply getting a credit card. My remarks this morning focus on three areas. I will describe the important role of alternative credit data, the expansion score itself, and how they benefit the consumer. So, first, the role of alternative credit data. Credit risk scores are typically a three-digit number that rank order consumers according to their credit risk. These and other credit scores use traditional consumer credit data consisting of positive information, such as the consumer has made all payments on an existing account, and negative information, which might include the fact that the consumer has failed to repay a loan. The expansion score leverages alternative credit data rather than relying on the traditional data. It is similar to the classic scores in that it uses both positive and negative data and relies on technology upon which other FICO scores have been built. Fair Isaac is committed to finding and using the best nontraditional credit available from third-party data providers. To provide its service, we resell data we obtain from a number of consumer reporting agencies that collect that data from the furnishers. An example of the data that we use within the score includes deposit account records, check-writing behaviors, telephone payments, and purchase plan performance. You may ask, why have we chosen to resell this data rather than create and maintain our own database? This strategy ensures that the expansion score will use the best and most predictive alternative credit data available. Also, the expansion score has been designed to utilize new sources of credit data as they become available. This approach allows us to continue exploring business relationships with reputable consumer reporting agencies that aggregate this alternative credit data. Next, I would like to describe how the data is used within the FICO expansion score. Fair Isaac developed the expansion score using the same statistical approach used to develop the classic FICO score. In developing the expansion score, Fair Isaac analyzed anonymous alternative credit report data to statistically determine what factors are most predictive of future credit performance. Credit grantors who cannot obtain a traditional credit risk score for the consumer can now, for many people, obtain the expansion score. The same 300 to 850 score range is used by both the classic FICO and the expansion scores. Consumers with higher scores are predicted to be more likely to repay creditors as agreed. Early results show that lenders are able to score and underwrite a high proportion of the credit underserved market. Fair Isaac has analyzed data from several lenders in mortgage financing, automotive lending, and bank cards, and has observed scorability rates as high as 80 percent. This means that the expansion score was available for eight out of ten applicants for whom a traditional risk score was not available. So finally, what does this mean for consumers? As mentioned earlier, we are estimating there are roughly 50 million credit underserved adults. This group is not only large, it is diverse. No one should assume that this group represents a subprime lending market. Expansion scores help create access to credit for those consumers that choose to seek it, while enabling lenders to make informed decisions. They also make credit more affordable by helping to automate the lending process. In conclusion, using alternative credit data in scoring improves access to credit for Americans who may have been turned away in the past and provides lenders with the necessary risk management tools to make good decisions. Thank you. [The prepared statement of Lisa Nelson can be found on page 61 in the appendix.] Mr. Castle. [Presiding.] If I would truly be the Chair, the first thing we would do is change the size of the print on the placards in front of you because I cannot read them from here particularly well. But the next witness is Mr. Catone, who has already been introduced. He is recognized for 5 minutes. STATEMENT OF MARK CATONE, SENIOR VICE PRESIDENT, FIRST AMERICAN CREDCO Mr. Catone. Thank you, chairman and distinguished members of the Financial Services Committee. My name is Mark F. Catone, senior vice president with the First American Corporation. Thank you for inviting us to testify today on the topic of helping consumers obtain the credit they deserve. The changing demographics of the population in the United States are reshaping the demand for housing, automobiles, and other goods and services. As a result, these changes are having a significant impact on the credit markets. According to many sources, including prior testimony to this committee, immigration has accounted for more than one- third of household growth since the 1990s. For the most part, the credit system in the United States has done a good job and continues to improve. No where else in the world today can you buy a car in under an hour or qualify for a home purchase online in the time it takes to fill out an application and click a button. One of the remaining barriers confronting immigrants, low- and moderate-income borrowers, and other consumers entering our credit system is the problematic issue of little or no credit information. There is no one answer or quick fix to this issue because of the existing built-up infrastructure of what we know as the credit reporting system, credit scoring, and what is referred to as nontraditional credit. There are, however, several areas we are active in that we believe should be examined and improved upon that will lead to more comprehensive solutions in the long run. There are four points. Make quality data available. The December 2004 report by FTC to Congress under section 318 and 319 of FACTA identifies data such as bill payment histories at utilities, telecommunication carriers, as well as rental payment histories, to be rich sources of data indicative of credit behavior. The limited reporting and the economics of collection of this data are problematic. Our company is very active in compiling and delivering what are referred to as nontraditional credit reports, which mortgage originators and investors accept and have a fairly well-defined standard. We collect this data on demand, working with the lender and the consumer. We apply what we believe to be best practices in due diligence and verification of the creditor information, resulting in the reduction of risk for the lender and ultimately to the investor. This is an on-demand service capability, and it is part of the solution today in the mortgage reporting industry. We also believe making additional utility, telecom, and related payment data available at credit bureaus or otherwise in an automated way will reduce the number of no-file and thin file reports. The second point--packaging of services in order to make the transaction economical. Again, the FTC report cited earlier also notes that the data identified is more expensive to collect and to add to the system and closes by noting that this makes ready solutions an economic challenge. In order to address this, the industry should look for ways to mitigate the expense of sourcing additional data. Our company offsets the higher expenses of compiling and verifying information for mortgage transactions, for example, by wrapping it into a fixed-cost comprehensive settlement package, effectively mitigating the higher one-off cost of credit alone. This concept may make more sense for other loan types. Third point--we need to provide more education and guidance to the consumer. We saw early on that a full-service consumer help line is key to providing both education and issue resolution to consumers. When our customers access credit for the extension of a loan, we provide education to the consumer if issues arise or education is needed relative to the credit report provided. This is an expensive function to provide, but we believe it is necessary and other players should follow this lead. Finally--encourage the standardization of credit reporting for consumers who do not have credit reports, but can demonstrate financial competency. Most loans employing nontraditional data today are considered manual loans, which must be handled outside of technology, resulting in higher costs to the lender and the consumer. Standardization of nontraditional credit reporting, both in method and technology, will lead to overall lower costs as industry players build this into their systems and infrastructure. Ultimately, everyone benefits. That concludes my verbal testimony. I would like to thank the Chairman and the committee and welcome any questions. [The prepared statement of Mark Catone can be found on page 55 in the appendix.] Mr. Castle. Thank you, Mr. Catone. Ms. Thomas is recognized for 5 minutes. STATEMENT OF GWEN THOMAS, SENIOR VICE PRESIDENT, CONSUMER REAL ESTATE, BANK OF AMERICA Ms. Thomas. Good morning, chairman, Congressmen, and committee members. It is a pleasure to be here to talk on this topic. I am Gwen Thomas with Bank of America Consumer Real Estate, where my responsibility is to increase homeownership among low- income individuals of all colors and minority individuals across the United States. It is an honor to be here today to talk on this topic that is so critical for us to be able to make continued progress. My testimony will focus heavily on a lot of focus groups. We call it voice of the customers that we have done with individuals who have limited credit. I accepted the subcommittee's invitation because I believe there are many opportunities and benefits that we can bring both to the customer and to the lenders and, thus, to the communities. Bank of America is the largest consumer bank in the United States, with more than 33 million customers, and that is about one-third of the households across the country. With that size, we have an obligation to make sure we meet the needs of the consumers we serve and, thus, utilizing nontraditional credit helps us toward achieving that goal. We have all seen the statistics on projected growth in the minority population, according to the U.S. Census Bureau. The Hispanic segment of growth will be a 188 percent increase by 2050; Asian, 213 percent by 2050; and African-American, 71 percent by 2050. So those are significant increases. Unfortunately, a lot of these individuals will not have traditional credit or have thin files, which causes potential barriers to achieving homeownership. Of those segments, the majority of the first-time homebuyers in the future will come from the various ethnic segments. Based on the focus groups we did, the interesting thing we heard from customers and potential customers was what was most important to them was getting a yes, getting it quickly, having a quick decision, be it yes or no, no surprises, privacy, and making sure that we understand that as part of the culture, cash is very much a part of the culture, especially with some of the part-time employed individuals who get paid in cash. While the traditional customer segments have some of the same desires about things that were important, the utilization of cash was the most unique piece for the segments that have the most significant growth. The bank has developed a lot of processes to meet the needs of the individuals with nontraditional credit. However, while we have those processes, they are highly manual, and they have the potential to sacrifice data integrity. Because of data validity issues, we only use the processes in a very limited way, and the processes are not currently automated for what we are using. Failing to use nontraditional credit can cause us to decline customers who have good credit and could qualify for a home. That is what our end goal is, is to get people into homes. Once we get them into homes, that is one of their best assets that helps them build wealth. One of the examples of a very successful program we have had is a program called Neighborhood Champions. That is a program we started 5 years ago focused on teachers. Now that program is extended it to firefighters, policemen, health care workers, and others that work in related fields. That program uses nontraditional credit, as well as undocumented income, meaning income where a person is paid by cash, to help them qualify for the loan. This has been a creative way to help homeowners. But, again, the nontraditional credit is a piece that, if automated with the data validity, can really help improve that process much more. For consumers with traditional credit histories, lenders have automated processes and scoring models. Those scoring models can provide objective, consistent, and quick decisions. And credit information generated through those models have a direct interface to the credit reporting bureaus. Once you have that information in the bureaus, it can provide a depth and length of customers' credit experience. It lets you know who is searching for credit, and it also helps you understand how the person utilizes and repays their credit. While these models are very good and they are automated, the drawback to the scoring models is that they are dependent upon information reported to the credit bureaus. For individuals that are either new immigrants or that use credit infrequently or that may just be coming out of college, they do not have the traditional credit to get reported to the bureaus, even though they may have been living with their parents or an aunt or uncle and paying rent for 12 months. That really could demonstrate good credit behavior. We need to find an easier way for reporting alternative payment histories. While current manual processes that we and others use in limited circumstances, and in some cases is accepted by the secondary market in a very limited way, it really does not work as efficiently as we would like for it to. One advantage of an automated process is the ability to treat all applicants equally. Bank of America is testing but not currently using any of the new automated systems that have nontraditional credit because we want to continue to work with potential partners as they improve the predictability of the information. Our goal is for this process to become more automated in a way that meets our criteria consistently and with integrity, which will broaden the opportunities for use. In conclusion, what I would like to say is providing alternative sources of data to current mortgage lending processes could greatly benefit multicultural and low-income customers. It would increase the number of people who can get into a home, reduce declinations, and help us to increase homeownership in the community. I am very pleased we have started this dialogue, and I look forward to continuous conversations. Thank you. [The prepared statement of Gwen Thomas can be found on page 87 in the appendix.] Mr. Castle. Thank you, Ms. Thomas. Ms. Saunders is recognized. STATEMENT OF MARGOT SAUNDERS, ATTORNEY, NATIONAL CONSUMER LAW CENTER Ms. Saunders. Thank you, Mr. Chairman. I am happy to be here today. I represent the low-income clients of the National Consumer Law Center, as well as the Consumer Federation of America, the National Association of Consumer Advocates, and the U.S. Public Interest Research Groups today. We believe that the reporting of alternative credit data holds the potential to help consumers considerably. However, because of the way the credit data and scores are currently being used in the marketplace, if these systems are built incorrectly or inappropriately used, the dangers to consumers could be devastating. We analyzed these new data systems through the prism of how they are currently being used. In addition to access to credit, credit scores and credit reports are being used to price credit. Some of the risk-based pricing that results from this use of credit scores today has supposedly justified very, very high-cost credit which is often unaffordable and leads to credit failure, default, and foreclosure. The credit scores currently are being used for eligibility and price for insurance in some States. They are also being used for employment, the initial decision relating to obtaining employment, as well as job retention. In some areas of the country, utility companies are looking at credit scores to determine eligibility for access to utility service. And there has been consideration of, and so far rejection of, the use of credit information to price utility service, which certainly must be kept on the radar screen. Because of that wide variety of uses of credit scores and credit data, we are very concerned that these new systems be developed based on fundamentally sound principles so that the information that goes into the new credit scores is truly relevant to the question of whether or not the consumer will have a likelihood to repay the credit for which the score being used. I am going to come back to that and talk about that mostly, but we also have concerns obviously that the information be accurate. We are very concerned that as these new credit data sources arise or grow, they only be allowed to be used for credit purposes until they have been thoroughly tested. Finally, there is considerable concern already on credit scores that they have a discriminatory impact and that they are built based on discriminatory history. We want to ensure, or we would hope to ensure, that the new credit scoring systems do not exacerbate this problem. It is essential that new scoring systems use payment histories which have characteristics substantially similar to the credit for which the systems are used. Specifically, one needs to look at the motivating factors behind both types of credit. The problem is that for many low-income people, for example, utility payments and some forms of credit such as payday loans and rent-to-own transactions have very different inherent features which send significantly different price and motivating signals to the consumer regarding whether to pay or not. We completely agree--I want to get this on the table--that a monthly rent obligation is an excellent source of information to use to base an evaluation of a consumer's willingness and likelihood to repay similar credit, especially a home mortgage obligation. The rent payment is an exchange for essentially the same product: a home to live in. The payment is generally at the same intervals: monthly. The consequences of not paying are similar: loss of the home and a forced move. Similarly, the requirement of a regular months payment for a wireless telephone bill is certainly relevant to requirements for other monthly obligations. But a utility bill for heat, gas, or water consumers is not appropriate. That is because many of the programs devised to help protect low-income households from shut-off of essential utility service in the cold winter months do not punish for late payments. In fact, many Federal and State programs designed to assist low-income consumers with high utility bills are only triggered once the consumer is delinquent. Similarly, payday loan characteristics are very different than those for traditional loans. The consumer repaying a payday loan has a very different set of criteria to face. Number one, it is a huge lump-sum payment. Number two, failure to make that payment might result in criminal prosecution. Number three, making the payment may result in not having essential funds for food or rent or some other necessity. Four, payday loans, unlike other loans, have lenders who actually encourage consumers to not repay the full loan immediately, and they offer discounts and coupons for consumers who do not repay fully. They like the rollover; rollovers are how they make their money. I am out of time, but I am happy to answer any questions. Thank you. [The prepared statement of Margot Saunders can be found on page 72 in the appendix.] Mr. Castle. Thank you, Ms. Saunders. Dr. Turner? STATEMENT OF MICHAEL TURNER, PRESIDENT AND SENIOR SCHOLAR, INFORMATION POLICY INSTITUTE Mr. Turner. Good morning, Mr. Chairman, honorable members of the subcommittee. I am grateful for this opportunity to testify before you today. I would like to commend Chairman Bachus, Chairman Oxley, and Chairman Castle for their leadership on this complex and crucial issue of consumer credit. Two years ago, I appeared before this subcommittee to discuss the benefits that Americans enjoy as a result of our national credit reporting system. That system is, by most accounts, the envy of the world. It is one of the engines behind the remarkable rates of homeownership in the United States. It is also of enormous help to those Americans who wish to start their own business. The success of our system of credit reporting is inarguable. But despite that success, many Americans, conservatively estimated at 35 million, remain outside of that system. The reasons for this are not altogether clear. Despite the complexity of this issue, we have identified one of the reasons for their difficulties, namely the lack of credit information about these 35 million Americans at the three national credit bureaus. Credit bureau information is, as we all know, one of the key means by which lenders make decisions on loans. And of course, paradoxically, without credit to begin with, it is difficult for such consumers to establish that they are credit worthy. It is like trying to get your first job when all the jobs posted require 3-to 5-years' experience. We are here today because we believe alternative data offers a possible way to help consumers overcome the consumer credit hurdle. Categories of alternative data include energy and water utility payments, landline and wireless phone bills, auto liability insurance payments, rental payments, especially apartments, and certain types of retail payments. We recently completed the first part of a two-stage study examining the inclusion of alternative data in consumer credit reports. Several of our preliminary findings should interest members of this committee. Our first key finding is that utility and telecom data are likely to be the most immediately useful and practical alternative data for reaching people with little or no information in their credit files. By ``useful,'' I mean that virtually all Americans purchase services from utilities, including most of the population with which we are concerned here. In our analysis, we refer to this metric as ``coverage.'' By ``practical,'' I mean that these industry sectors are populated by a relatively small number of very large firms, meaning that there are very few data furnishers to reach. In our analysis, we refer to this metric as ``concentration.'' Finally, there are benefits for these companies where they do begin reporting. We have seen strong evidence suggesting that reporting customer data to credit bureaus, combined with customer awareness programs, substantially reduces delinquencies and defaults. Our second key finding is that nontraditional data is unlikely to negatively affect the credit scores of most Americans. Serious negative information is already reported by utilities, telecommunications firms, and other sources of nontraditional data, typically indirectly through collection agencies. What is not generally reported is positive information or timely payments. Reporting positive data improves credit scores and builds credit history. Given this, the public policy question then becomes, what can we do to promote the sharing of this information? Our study also examines factors that hinder the reporting of alternative data. In our forthcoming research, we identify two economic barriers and two regulatory barriers that may deter the reporting of this information. The four barriers are, first, in many States, regulatory uncertainty acts as a soft barrier on the provision of nontraditional information. This is especially true for utility providers that are often unsure of the permissibility of reporting. As a result, without clarification from State legislators or regulators, the fear of potential legal liability and public relations fallout acts to block the sharing of customer data with credit bureaus. Second, in our survey, at least two States have laws that prevent utilities from reporting certain types of consumer payments. Third, some prospective furnishers are reluctant to report this data fearing that it will enable competitors to steal their customers. Fourth and finally, some firms may have complex and incompatible legacy IT systems in place that would make the cost of reporting greater than any perceived benefits. These last two are obviously problems we should leave to the market, but public officials can address the first two barriers we identified: again, regulatory uncertainty and legal hindrances. In some ways, regulatory uncertainty could be dispelled with little more than a public commitment to the idea of alternative data sharing. Public service firms should be encouraged to at least look at whether or not reporting alternative data might be a good idea for them. We have framed what we believe are the key practical questions concerning the reporting of alternative data. In the months ahead, we intend to work with members of the credit reporting industry, financial institutions, utilities, and consumer education organizations to measure whether and how much the inclusion of alternative data in consumer credit reports could help more Americans realize their dreams, dreams like homeownership, buying a new car, or starting their own business. We look forward to providing our findings to members of this subcommittee in the near future. Again, I thank the members of this committee and the chairman in particular for this opportunity and welcome your questions and feedback. [The prepared statement of Michael Turner can be found on page 92 in the appendix.] Mr. Castle. Thank you, Dr. Turner. Thank you, all. This is a very interesting panel, and you have a lot to say. We do not have enough time in our questions to be able to possibly cover all of the things that we should cover, but I will start by yielding to myself for 5 minutes. Let me ask just one basic question. I said this in my opening statement, and ever since I said it, which my staff helped prepare, I have sort of questioned it. That is, I said that 35 million to 50 million Americans are without credit scores. If my recollection is correct, we have, what, about 280 million people in the United States of America, a lot of which are children. Thirty-five million to 50 million sounds high to me. Does anyone here--and if you do not know, do not try to answer--but does anyone here have any idea what the number really is? In any of your businesses, have you ever tried to identify that whole number of those who do not have credit scores at this point? Ms. Nelson. We have, and our ranges are similar to yours. I mentioned 50 million. The general thought process that got us to that number was that of the total population, it is estimated that there are about 215 million adults aged 18 or over living in the United States. Mr. Castle. I am sorry, how many? Ms. Nelson. About 215 million. Mr. Castle. Right. Ms. Nelson. So I am just walking you through our logic. This comes from a number of different sources that we have pretty much culminated together. And then from there, we are also estimating that there are about 165 million of those consumers that have enough data within the bureaus to generate a score. So our estimation is that of the remaining 50 million or so, about 30 million do have data at one of the three national repositories, but not enough to generate a score, and another 20 million probably have no data at all. Mr. Castle. So we are dealing with pretty big numbers here. Ms. Nelson. Yes. Mr. Castle. This is not just a problem of 1 million people or several hundred thousand or something like that, but a big number. This is a question I could ask any of you, so I will just try to limit it and I will ask Mr. Catone perhaps and Dr. Turner to comment on this. I indicated in my opening statement that this hearing was not preparatory to introduce legislation, and you mentioned it a little bit, Dr. Turner, not that we should do it, but you mentioned a little bit in what you stated. My question is, do you feel that at a State or Federal level that we should be considering some form of legislation, statutory legislation or regulation to deal with these issues? Obviously, from all five of you, it is an evolving issue. In fact, there are some differences that are very interesting here in terms of what you view as significant data in terms of alternative credit information. My question is, should we be regulating this? We have been doing a lot of regulating around here lately. I am a little reluctant to over-regulate. I would be interested in your viewpoints on that. Mr. Catone. It is an issue of economics. It is much more expensive to do manual compilation of data or verifications of the data, do the proper fraud checks and things to prevent information that may not be quite right from entering the system. Lenders and investors are concerned about that aspect of it. So it is much more expensive to serve that community. What needs to occur at some point in time--and based on the changing demographics of the United States, it may be 2 years, 5 years, 10 years--but something would need to be done to adjust the economic incentives to serve the market better. We are starting to see that, and the reason we are sitting here today is because it is becoming an issue. So there is a whole set of economics that come into play. That is the reality of the situation. Mr. Castle. Dr. Turner, do you have a quick answer to that? Mr. Turner. I would not endorse regulatory activity at this juncture. The barriers that we identified in terms of policy primarily are indirect. We have spoken with utility companies that are reporting and met with their public service commission in their State and let them know that they were going to report and were told outright that they should not report. They went ahead and reported anyway because there were no statutory prohibitions on the book. They were doing this as a matter of courtesy. We have also spoken with regulators actually in your State, Mr. Chairman, and there was a case where a utility was reporting data and was told not to report the data by the public utility commission and discontinued the practice despite the fact that no laws were on the book. In California, we had conversations with regulators there and they, in fact, suggested that there were requests from utility companies in California to report the data and asked the regulator, ``Do we have permission to do this?'' The regulator said, ``Sure, go ahead.'' The utility company said, ``Can we have this in writing?'' The regulators were unwilling to put this in writing until they got direction from the legislature. So it is really a matter, I think, of some sort of guidance from the State legislatures at this juncture. Only two States have varied prohibitions on the books for the onward transfer of this data, and it is not with this issue in mind. Mr. Castle. Thank you. I appreciate that. Obviously, this is an evolving issue, so we will continue to look at this. I am just interested, if I could ask a little bit of a different question of Ms. Saunders, of you, and perhaps Dr. Turner--I thought I saw disagreement here, because, Ms. Saunders, you were pretty adamant that utilities were not necessarily very predictive, primarily in terms of a mortgage. But in terms of lending perhaps, I think all of you agreed that rent is in that circumstance. Part of it is that the programs that exist that do not even have any implications until you go into default, to a degree. Dr. Turner, you talked about the utilities and telecommunications as the most promising and practical source of nontraditional information. I would say there is a bit of a conflict there in terms of what you both have said, not to pit you against each other. There is probably some truth in what both of you have said. Maybe we should start with you, Dr. Turner. Can you defend why you said that? I think I understood Ms. Saunders's position, and perhaps she can try to respond to that. I am not looking for trouble here. I am just looking for the best answers on what might be predictive or not. Mr. Turner. Ultimately, I think we disagree actually not only on utilities and telecoms data, but also on rent data as well. In our analysis, we identified industry sectors that have a high level of concentration, meaning just a few data furnishers or prospective data furnishers, and a high coverage, meaning that many of the lower-to moderate-income Americans, the unbanked, the thin or unscorable filed Americans, would have these services. Rental payments are highly fragmented. It does not really reach a lot of the affected population. We do think, for example, if there is some sense of a need for public policy, many of those in affordable housing or public housing actually would benefit potentially from having their payment history reported. That is an area where State public housing authorities could act. But ultimately, in any of these data types, we are not prepared to make judgments as to whether or not one data set is currently more predictive than another. That is an empirical matter. That is what we are setting out to do in our quantitative analysis in the next component. We are just not prepared to suggest qualitatively that certain types of data are better or worse without the benefit of actual empirical analysis, regression analysis. We are aware of some groups that are actually putting this to the test in the trenches and meeting with consumers, asking them to volunteer to have their data reported, and measuring over time whether or not it makes an impact on their score and their access to credit and the terms of credit. Mr. Castle. What do you think, Ms. Saunders? Is it empirical data, or can we put a qualitative mark on each of these things as to what is better and what is not? Ms. Saunders. I think Dr. Turner is correct that we need to do a lot more analysis. I want to explain that while we are concerned with the furnishers who are providing the data, we are also very concerned with the users. So part of our concern with using utility payments as a means of gaining information about the consumer is guided by the fact that we really do not want to see utility bills in the future based on risk, as some non- regulated utility providers have already proposed doing and have been rejected. Specifically in Texas, there was a bill that would have allowed--or there was consideration of that exact question. Let me clarify that. Let me emphasize that what they were proposing to do was to charge higher rates for electric and gas for low- income consumers who had worse credit. That is exactly what we are most afraid of because electric and gas and other utilities are essentials, and you should not be able to do that. So part of our concern with the furnishing of utility information is guided by the fear on the back end. I do agree with what Dr. Turner said, that when some utility bills are seriously delinquent, they are already reported to the credit reporting agencies, so that it would not hurt in those situations. But I would challenge him on the point that all delinquent utility bills are regularly reported because I think that is just not the case across the country. Mr. Castle. Thank you, Ms. Saunders. My time is up, and Ms. Moore is recognized for 5 minutes at this time. Ms. Moore of Wisconsin. Thank you so much, Mr. Chairman. I apologize to the panel for not hearing the testimony of these distinguished panelists. I have listened with interest over the discussion of the use of rent and utilities as a means of getting these folks with thin records an opportunity to receive credit, particularly mortgages. Ms. Thomas, I came in during your testimony. I guess my question is, why can't we develop some sort of instrument where people who do not have any credit history are presumed to be bankable, innocent until proven guilty? There are many people who deliberately do not have credit because they heave learned what we have learned years later: You should not have too many credit cards in your pocketbook. The generation before me, my uncles and aunts paid all their bills, bought things on layaway, except for owning their own home. I am wondering, number one, why it is a problem that people have thin credit? Secondly, I also am concerned about using utilities as a factor in determining credit because energy costs--I am from Wisconsin, and energy costs have far outpaced people's ability to pay, even people who are not regarded as low income. In addition to which, people have due dates that are completely arbitrary. It is not like every bill is due the first of the month. The billing date may be the 14th of the month. If you pay on the 15th, then you are in trouble. I guess I would like for Ms. Thomas, Ms. Saunders, to sort of respond to these concerns that I have, and anyone else who would like to jump in. Thank you. Ms. Thomas. I think your first point about why is it considered a thin file and the whole thin file piece is a standard definition based on individuals having less than three credit lines. That is why we accept that information manually today. If a person does not have enough credit, we ask for rent, utilities, telecom, insurance, anything that can show us payment history. Because typically you will find that there is good payment history there, it is just not automated. Then for the utility piece specifically, back to your and Ms. Saunders's point, if we see indications where those payments have not been paid on time, when you are doing this manually, you can ask further questions to seek the understanding of what happened. In most cases, the customer can explain that it was due to some extreme circumstance, that we can then move forward with the loan. Ms. Moore of Wisconsin. That is a very good point. I remember once I was subjected to a utility shut-off and I had paid all through the moratorium and still had a $2,000 bill come spring. When they asked further questions, they discovered that I had a 30-year-old furnace that had originally been a coal furnace converted to an oil furnace, and I had converted it to a gas furnace. It was very inefficient, and that was the reason that I just could not keep pace with the utility bills. Ms. Saunders? Ms. Saunders. I would like to pose the juxtaposition between utility bills and standard credit. Most credit offered to middle-income consumers is underwritten. There is an evaluation made by the lender about the consumer's ability, not just willingness but ability based on income, to repay that loan. Utility bills and payday loans are not underwritten. In fact, they are quite the reverse. Utility bills can very often be very large, much larger for lower-income people than they are for higher-income people because they live in houses which are not weatherized and because they have many people in their family. So we are using information that is really not relevant, and that is our concern. Ms. Moore of Wisconsin. I also want to ask one final question, Ms. Saunders. You mentioned pricing credit used to justify high interest rates. I have seen this continuously where creditors just are in glee to see a little glitch on your credit report. So I have come to think that somehow the Fair Isaac scores are not fair. I have heard many reports, experienced it personally, where there is almost this little game where people just really are in glee about bad credit. Can just anybody respond to that before my time expires? Thank you, Mr. Chairman. Ms. Saunders. If I might very quickly, I would like to point you to that part of my testimony where I discuss in some detail the discriminatory questions that have been raised about credit scores already. There have been lawsuits, and there have been a lot of studies, and a lot of people believe that current credit scores do have discriminatory impact. And we are concerned that as these new alternative sources of credit scoring develop, that we not exacerbate that problem. Ms. Nelson. I just need to point out one comment to what was just said. That is that, as we develop scores, we are very cognizant of what is allowed and not allowed as factors that drive the score. So that is an important piece of understanding that I would like to make sure this entire subcommittee understands. Secondly, when you talk about the fairness of the scores, the score has been proven time and time again to be a solid predictor of risk. I think part of what you are describing is some lenders' decisions and policies around how to react to that score when dealing with the consumers themselves. So I just want to be careful not to leave the impression with this committee that the scores do not work. The scores absolutely are predictive of consumer behavior going forward. But policies that surround that score is an issue that I think every lender deals with in a very, very strategic and personalized way. So it is difficult to describe any practice as being industry-wide. We know that there are some lenders that are more aggressive than others in how they deal with consumers in that account review mode. Mr. Castle. Thank you, Ms. Moore. We appreciate it. Chairman Bachus is recognized for 5 minutes. Mr. Bachus. I thank the chairman. I guess before I ask a question, I would make a statement. I am not sure that this Congress or this committee should ever require companies or individuals to share information about payments. That is being pretty intrusive if you ordered utility companies to share that with credit bureaus. You know, 90 percent of the landlords in this country are individuals, so it is a very decentralized thing. That would take a monstrous bureaucracy and enforcement system if you required all of them to report that. I mean, that would be a pretty overreaching law. I am also concerned about privacy. That is a very important issue in this country, is people's privacy. For the Government to start saying that you have to give out information on your customers or on your tenants would be, to me, almost a revolutionary thought because that gets in the public domain. So I would make that comment. I would ask that with 90 percent of the rental units in the hands of individual landlords, is it even practical to require such a reporting system? Let me ask that question first. Just any feedback from the panel on that? Ms. Nelson. I would provide a couple of thoughts. I have a history not with Fair Isaac but in prior employment with a consumer reporting agency that is obviously not one of the three national bureaus. The services we provided were to financial institutions to help manage risk on the debit side of their house. That is an example where back when that company was founded in the early 1970s, it was not a highly concentrated banking industry as it is today. There were thousands and thousands of banks across the country. The inception of that particular business model occurred because banks were getting hurt by consumers that were either being abusive or fraudulent with their checking accounts. So there was a reason for the industry to cooperate together, share information and help themselves manage risk. I raise this as an example because Mark already mentioned that the economic model behind this issue is a significant aspect in that there are significant costs both to the furnishers that provide the data, as well as the aggregators. And there has got to be some sort of incentive. In some industries the incentive is to be able to better manage the risk within my industry if I share with my competitors information, both positive and negative. So in the case of the rental industry, if there was enough incentive to that group of small business owners to be able to start sharing that data, that is the incentive that gives them the reason to start to share the data and, therefore, would be available for use to help consumers beyond finding that new housing, but also to eventually obtain a mortgage. So the economic model is a big issue. Tied to that is the whole regulatory aspect. If you look at the work that any of us are doing today, all alternative credit data is governed by the FCRA and FACTA. So we have the same consumer protection mechanisms in place as we do with the national bureaus. So whether you are a large national bureau or a very small boutique consumer reporting agency, your obligations as an aggregator and the obligations of your furnishers are identical in that you have to be certain the data is accurate. Mr. Bachus. I guess my question was more, aren't there some real practical hurdles to even--I almost hesitate to ask the question because I would not be in favor of requiring America's landlords to report. Ms. Nelson. The costs would be insurmountable, I believe. Mr. Bachus. That was really it. Let me go on to utility payments for a minute. Number one, I would say I am not sure what the value would be because people are going to pay their utilities, or the option is to get the service disconnected at times, I would think. But secondly, with utilities they estimate payments. My mother, for instance, with $1,200 Social Security, she will have a bill that comes in one month and it is $15 for water, then the next month it is $115. They vary quite a bit. The gas bill--I have seen them; they will go from $100 to $250. What we do is we supplement that and my mother pays them. But her utility bills can really go up and down. I actually charted that out, and they go up as much as 40 percent and 50 percent. So I would think some people do that by paying one month a certain amount each month. And I think most, like Alabama Power, I think their policy--probably somebody pays $50 on a $50 bill, and the next month they get a $150 bill and they pay $75 and catch up. I am not sure anybody thinks there is anything wrong with that. Mr. Turner. If I could just respond to the utility question. Again, I think whether or not any individual data sets are predictive in terms of one's credit risk, credit capacity, or credit worthiness, there are ultimately empirical questions. In terms of utilities, I agree with Margot Saunders; all of these data sets have different characteristics. They are likely to have different predictive value for different lenders, for example. What may matter in a home mortgage loan immensely may not matter so much for general purpose revolving credit. However, in our analysis, we make a distinction between types of alternative data that are more credit-like, meaning that you receive a service before you make a payment, like a credit card. You can use a credit card before you have to make the payment, or that are more cash-like, like a debit card. We think that that is a meaningful distinction. And when you look at a thin file or someone who is unbanked and you have no ability to accurately predict the probability of default, if you can populate that file then with credit-like components, utility data, wireless phone data-- again, they have different characteristics--it may be possible to make a better assessment of that individual's credit worthiness. That is what this is really about. Ms. Thomas. What I would like to add to that--and you made an interesting comment about privacy because that is a concern--but one of the challenges sometimes for the customer when you are trying to get that mortgage loan approved--and that is the hat that I am wearing is if they do not have receipts, because who keeps 12 months of utility and rent receipts, it is tough for the customer sometimes to get the information, and sometimes we try to help them do that. Mr. Bachus. I would say this. I would agree with you. I think if someone low or middle income, particularly, that needs to establish credit, I think that if they sign something and say, I would like the utility company to supply my payments, or a landlord, I can certainly see that. That does away with most of my privacy concerns. Ms. Thomas. Okay. Mr. Bachus. I think that a tenant probably has the right to ask for that, and I am sure landlords would not mind supplying that. I would hope not. Ms. Thomas. Some of them do not mind; some do. Mr. Bachus. Yes. That is a very good point. I had not thought of that. I yield back. I do not have any time left. Mr. Castle. Thank you, sir. Congressman Baca is recognized for 5 minutes. Mr. Baca. Thank you very much, Mr. Chairman, and thank you for having this hearing. Let me ask this question of Mark Catone. In your testimony, you discussed the changing demographics that impact credit markets. You state that immigrants have accounted for more than one third of the household growth since 1990. Immigrants are included in a list of rising numbers of consumers, and I state, ``A rising number of consumers who are planning to make major purchases either earlier in their lives or soon or after becoming U.S. citizens.'' I am very much concerned that Real ID and the laws to establish national ID cards for employment purchases will affect immigrant consumers in the U.S. It is true that the use of nontraditional credit reporting, such as utility statements for immigrants, can provide them with greater credit availability. However, I am more concerned that the Real ID will prevent some banks from doing business with immigrants. It may push them further into the category of unbanked. Can you comment on the Real ID bill as a new barrier for immigrants seeking to build a credit history? This is question number one. And two, what do you believe can be done to prevent this, if anything? Mr. Catone. Let me position it in terms of our experience and our experience of compiling nontraditional data in response to mortgage originators' and investors' loans. We have seen alternative identification presented to use for those consumers in compiling that information--for example, consumers that may not have a Social Security number or who may have an individual identification number or an alternative mechanism. There is not anything that I am aware of--and I am probably not the best person to speak on the regulatory subject of the identity issue, but in our experience, we do not differentiate between whether an individual has a different type of identity or verification of that nature. We are responding to our originator or a mortgage investor's request to compile a nontraditional credit report for the purpose of extending a loan. So it is more general based than broad based. We are not telling the difference between one or the other. We do verify the identity, the address of the applicant. We do verify the data that is sent to us and that we collect and compile. That is transmitted back to the mortgage lender or the investor. So I do not have the depth, I think, of granularity you are looking for in terms of the identity issue. Mr. Baca. So it could create a problem, though, because right now most of them can use matriculas for identity purposes and banking purposes, but if Real ID was put into place, the difficulty then in terms of the banking, as well, would also impact our societies because individuals use either banking or credit through banking, not only in obtaining credit and credit rating, but they also use the banking to pay a lot of their payments. In making payments from the banking or checking accounts, they end up becoming taxpayers on sales tax, so that sales tax then could conceivably be lost within each and every one of our communities based on what may be implemented and how it is interpreted, with Real ID, the law that just passed last week. I just wanted to find out if it would have any impact on our banking system based on Real ID. Let me ask you another question. This one goes to Michael Turner. Latinos are more likely to have no credit history--22 percent compared to 4 percent of whites and 3 percent of African-Americans. Some suggest that part of Latino culture is to remain debt-free. What cultural or economic reasons are there that create the discrepancy? This is question number one. And how can we increase and improve education to Latinos and other minorities, especially regarding the new use of nontraditional credit risk indicators to encourage a healthy credit history so they are able to enjoy the same credit availability as their neighbors? That is difficult when it comes out with the credit rating being higher for a Latino versus a non-Latino. Michael? Mr. Turner. Thank you for the question. There are two questions, actually. I cannot pretend for a moment to fully understand or explain the discrepancies. I have seen analysis that suggests that, for instance, with the Latino community in particular, there is an issue of part-time residency. I lived in Washington Heights with the largest Dominican population outside of the Dominican Republic. Many people in my neighborhood would leave for 3 or 4 months at a time and go back to D.R. They would not pay utility bills for 3 or 4 months, and then when they could come back everything would be paid. So in a traditional credit model, that is a pretty serious negative, a serious delinquency, but it may not accurately reflect, for instance, their credit risk or credit worthiness. I am aware of some efforts to try and better understand certain populations and these discrepancies in credit scores and how they are explained behaviorally. We do not analyze that in our study. It is certainly an interesting topic, and it is a very rich subject, and it is worth a lot of analysis, but I cannot really speak directly to that. What I can speak to, and I think you make a very important point here, the group that we are talking about, the unbanked, recent immigrants, thin-file Americans, they are not likely to have a high degree of financial literacy. What is the significance of a consumer credit report? What is the meaning of my credit score? Why does it matter in day-to-day life? We are dialoging through our own work with programs that are actually out in the field working with low- to moderate- income Americans, different immigrant populations, and testing. They are small efforts at this point, and they are vastly underfunded. But they are testing whether or not they can hold a focus group or educational seminars, get consumers from these populations to volunteer to have this data shared, and to track over time whether it matters materially to their score, to access to credit, to the terms of that credit. I think that is a tremendously important effort. I think certainly, at least I am hopeful that one of the outcomes of this hearing is an increased awareness of the importance of those efforts. Mr. Castle. Thank you, Mr. Baca. Mr. Baca. I know that my time has expired, but I hope we do more educational awareness training because we do not want them to prey on these kinds of individuals, because their credit, being minorities, is a lot higher than anyone else. If there is that kind of educational training, at least they will be aware to look at their credit rating, change whatever needs to be done in that area, so this way they do not continue to prey as, hey, I am going to make X amount of dollars because their credit rating is so high, so ,therefore, I am going to charge X amount of dollars. Thank you very much. Mr. Castle. Thank you, sir. Ms. Thomas. Chairman Castle, may I add one brief comment to what he was saying? Mr. Castle. If you can be very brief. Ms. Thomas. One organization, the National Association of Hispanic Real Estate Professionals, is doing a lot around educating the Latino community on that particular issue. Thank you. Mr. Castle. Thank you. You were brief. Mr. Pearce is recognized for 5 minutes. Mr. Pearce. Thank you. I have a series of questions, and I am going to ask for the shorter answer rather than the expansive answer. Five minutes elapses really quickly, and if you are drifting off, I will probably pull you back, but do not take it personally. I do not want to talk about the unethical people who exist on both fringes: unethical lenders who would exploit or unethical consumers who would take advantage of it. I am trying to wrestle with the concept somewhere out in the middle of how we deal with people who have not always been on the upside of the economic spectrum. Ms. Nelson points out that their improved techniques are allowing actually credit to be given more widely. Instead of a categorical exclusion, we are actually getting down into some of the participants maybe that previously could not have gotten credit because we have better information. Ms. Saunders is somewhat uncomfortable, on page two, with people pricing credit based on your ability or your previous history of paying. And yet I find Ms. Thomas, I suspect you all, if you find someone who is not a very good credit risk, but you are going to try to work them into your program, and I see that happening. Our district is very poor, and Mr. Baca has pointed out a lot of people in the Hispanic economy are actually on the cash economy. Do you all find that your costs associated with some of those clients are higher than the costs associated with someone who just sends a payment in every month? Ms. Thomas. What we see, and I do not have the exact cost numbers, but it does take longer in terms of cycle time, which can translate into costs. So it takes more effort working with the consumer. Mr. Pearce. So if you have a higher cost, if you do not charge a greater price, and you have a higher cost, then you are actually charging someone else for that person's cost. Ms. Thomas. We are charging that individual, but we are not charging them a higher rate. Mr. Pearce. I am just saying that if it is a higher cost and you charge the same thing you are charging someone else with a lower cost, then actually you are either accepting less margin, and if that margin becomes negative, you then charge someone else for fees that would go over here. Ms. Thomas. No, that is not the case. It does impact our productivity, so you are correct there. Mr. Pearce. That is all I needed to know. Ms. Saunders, you would feel very uncomfortable with any price increase no matter what the credit risk? Ms. Saunders. No, sir. I think you misunderstand me. I was trying to put a lot of ideas into a few short words. We do not disagree with the idea behind or the justifications of risk-based pricing. We certainly see many instances where low-income consumers have benefited from them. What we disagree with is the very typical practice among some creditors of using risk-based pricing---- Mr. Pearce. Sure, yes, those are the ones I said we are not going to talk about. Yes, there are unethical people. But you are giving clarification, and that is what I am asking for, that you really do not object to the price. It is the unethical treatment of price increases. Ms. Saunders. Well, there is a recent study that came out in the paper just a few weeks ago where it showed that those consumers of credit cards that were paying the late fees and the default interest rates were actually subsidizing the middle-income consumers who were not paying anything. So in terms of subsidies, I think it is going that way. Mr. Pearce. I appreciate that. On your program, Ms. Thomas, in the underserved market, what kind of success rate are you having on the repayment of your loans? Ms. Thomas. We are having a very good success rate. We monitor that pretty closely. That is how we were able to get the practice of utilizing nontraditional credit approved in the first place. Mr. Pearce. And typically people in this credit category that you are reaching down trying to now extend services to, they usually are not going to be the people looking for the $100,000 to $200,000 loans. So what size loans do you find them targeting? What is the smallest loan you give? Ms. Thomas. I am sorry, what was the last one? Mr. Pearce. What is the smallest loan you all give? Ms. Thomas. Loans can vary anywhere from $70,000 up--I think about different markets, where $100,000 could be a low- income home, a low-income mortgage. And for individuals that are on the extreme end of the credit risk, we require counseling, education, because we have---- Mr. Pearce. No, I am just asking for what size loan. Ms. Thomas. Anywhere, $70,000 up to, in California it could be $200,000-plus. Mr. Pearce. And that is my point, that one of the greater tasks for us, I think, is some of the smaller banking institutions. You all do a good job of outreach and reaching in, but really in our district we find that the low loans of $30,000 really not many people want to offer down in there. It kind of addresses Ms. Saunders's concern that there are not many participants willing to go down into that range. So we really have the testimony here that would allow us to give a lot more people access to credit if we can figure out how to measure the parameters and we can find lenders who are willing to get out and take that step and charge a reasonable rate of interest and give access and take the risk. I appreciate the fact that Bank of America is doing that. Somewhere we have to find the measurement tools that will then allow us to really thread the needle a little bit more finely than these categorical exclusions. So myself, I appreciate all of the efforts on both sides of trying to solve it because it is a thing that affects my district a lot. We are low income. We are majority minority, and people just work hard and stay on cash economies. So I salute you for what you are doing. We will see if we can facilitate it. And thank you all for your good testimony. Mr. Castle. Thank you, Mr. Pearce. Ms. Carson is recognized for 5 minutes. Ms. Carson. Thank you very much, Mr. Chairman. And thank all of you, certainly, for being here. My question is one of not to be combative, but simply to understand the process better. For example, I have a neighbor. Well, let me start over. There are consumers who are good payers. There are consumers who are slow payers. And there are consumers that do not pay at all. I understand that, and I am not favoring the no-pay-at-all when they can pay, please. In situations like in my district where the gas bills have skyrocketed--in my own case, this is not hypothetical, I have lived in the same house for 35 years. My winter gas bill has gone from $100 a month to $700 a month now. It is just outrageous. We have neighbors in the same situation, who are low-income, who have had to borrow payday loans, put utilities on credit cards, to keep their utilities on. Sometimes it works and sometimes it does not, but the more they borrow, the more the cost of the utilities becomes. In your scoring process, do you by any chance take into consideration people who have been good payers and then suddenly something happens and they go down the drain financially and do not pay the utilities on time and a lot of them are disconnected? Do you use a unique scoring system that would take all of that into consideration if you know about it? And how can you know about it if somebody does not tell you about the circumstances? Ms. Thomas. In terms of a scoring system, that example would not be dealt with in an automated way, but in a manual way we can ask the question. Because if you see a person's history has been good and all of a sudden something happens, we usually will ask for an explanation, and if the explanation is one that makes sense, then we can use that information to continue underwriting the loan. But it is not automated; it is manually done. Ms. Carson. So it is always manually done when the red flag comes up. Who ultimately determines if your credit scores are statistically sound? Is there some independent external oversight of your credit scoring methods? Ms. Nelson. Are you asking as a lender or as an industry? Ms. Carson. Industry. Ms. Nelson. Fair Isaac continually works to validate the predictiveness of their score. Every lender that uses the score will then manage the score and their loss rates so that they are looking at their own portfolio to be certain and confident that the cutoff ranges that they are using are appropriate for the business that they are trying to attract. So it is a very personalized process for each lender in terms of monitoring performance of the scores that they have used. Ms. Carson. I have another question. I see that payday loan lenders can be used to determine FICO expansion scores. I know anybody that goes regularly to a payday lender is in financial trouble anyway. If you go borrow $100, and when you pay it back it is going to cost you $120 or $130, you automatically have a problem anyway. So how then do payday loans become a part of the equation when you know straight up? I have constituents, because I tried to close payday loans down, and they were outraged at me. ``How dare you. That is what I depend on.'' Well, hell, I didn't know. I just thought you were getting ripped off unfairly or unnecessarily. So payday loans are very popular with some people. Now my district, don't confuse what it is. It is not African American. It is not welfare oriented. We just happen to have some constituents who fall through the cracks. I have to qualify that because people look at me and presume that I am from an African-American district, and that is not true, even though I have been elected to Congress five times. So it is not to rely heavily on somebody that is of color, somebody that is on welfare, any of that. I get annoyed because people automatically make those assumptions when they look at me. But how then do military families rely ordinarily on payday loans because the Government, I am not going to use the word because I do not know if there any kids in the audience, but they are not runaway brides. They are trying to protect the sanctity of this country, the freedom of the country. Military people rely on payday loans all the time. I think it is something like 23 percent of them that are on active duty in the military. So then how do you differentiate those kinds of situations, payday loan lenders, in your scoring process? Ms. Nelson. Specifically to the expansion score, we have looked at the value or the predictiveness of payday lending behavior, loan behaviors for consumers. So we have analyzed it, but today it is not part of the expansion score. Ms. Carson. You do not use it? Ms. Nelson. No. Ms. Carson. You do not use them. I take your word for it. Ms. Nelson. You have my word for it. We do not use payday lending information. Ms. Carson. I am going to yield back the balance of my time. Mr. Castle. Thank you, Ms. Carson. Thank you very much. Mr. Hensarling is recognized for 5 minutes. Mr. Hensarling. Thank you, Mr. Chairman. Thank you for your leadership on this issue. I certainly think it is a worthy topic, whether or not nontraditional data can be used in these credit scores to provide credit to perhaps historically underserved populations. It is certainly a topic worthy of our discussion. Dr. Turner, in your testimony, you have touched upon it, but I would like for you to elaborate. I think, if I understand you properly, you have concluded that the reporting of nontraditional data is very unlikely to negatively impact credit scores for most Americans. I think you essentially see this as an upside because you have stated that, by and large, most negative credit information is already reported into the system, and frankly it is the thin file, to use industry parlance, that is the major challenge. Can you just go into a little bit more detail about what facts and research your conclusion is based upon? Mr. Turner. I would be happy to. In our forthcoming study--and, again, it is a qualitative analysis that sets up the subsequent quantitative analysis--we interviewed a number of prospective data furnishers, lenders, modelers, credit bureaus, et cetera, and really got a firm sense of the landscape of what is and is not reported. I am in agreement with my colleague here, Margot Saunders, that all utility companies do not report all negative data. I never ever implied that or inferred that. There are some utility companies that are reporting both positive and negative data directly to credit bureaus currently. It is a minority, but there are some that are doing it. What I focused on was the indirect reporting from this universe of alternative data providers, the telephone companies, your landline, your wireless, utility companies. When accounts go into serious delinquency or default, they go to collection. The collection agencies report payment and nonpayment, the entire set of information, to the credit bureaus. So those sets of negative data from this range of alternative data furnishers are already reported. So if in a hypothetical situation, all utility companies, all wireless provides, et cetera, were to begin reporting positive and negative, the net impact would be unlikely to be very negative for those that we have identified as thin file or unscorable or the unbanked. What they would benefit from would be the overwhelming amount of positive payment history that would be appended to their files and may, and again this is an empirical question, may enable them to enter into the mainstream credit system. Mr. Hensarling. In your testimony, didn't you also mention that the lack of access to credit may help explain why there are lower levels of entrepreneurial activity among the poorer segments of the population? Is that correct? Did you reach that conclusion? Going back to the question of the payday lending, I found the comment of my colleague to be interesting because indeed I have found a number of my own constituents who find payday lending to be a far superior alternative to paying fees, late fees on credit cards, and bounced check fees, and reconnection fees, and the rest. Ms. Saunders, I believe in your testimony, if I am quoting you correctly, ``the essential characteristics of payday loan transactions are so different than more traditional forms of credit that the payment or nonpayment of these liabilities is simply not relevant to whether a consumer will pay a credit card bill or traditional car loan.'' I am reading from your testimony. If you would accept the proposition that the thin file is a challenge for any underserved populations, why would you deny me--or maybe you would not, but if I am in the business of extending credit and I have one individual who has no credit history whatsoever and I have another individual who I see over the course of 2 years has taken out seven payday loans and has repaid each and every one on time, it seems to me--and you might disagree, but we could have a logical disagreement--I might consider that to be predictive behavior of one's credit worthiness. Are you advocating a policy that would deny me that right as one who is in the business of extending credit? Ms. Saunders. I am simply advocating a policy of ensuring that the information that the creditor receives relating to your ability to make the repayment is relevant. I would posit the theory that whether a particular consumer repays payday loans or not is probably not relevant. I leave it to my colleagues around the table to prove me wrong. If it is in fact entirely predictive that a payday loan consumer will repay or will not repay based on traditional credit, based on how they have used payday loans, then I may be wrong. My analysis and our kind of uniform analysis among the consumer groups is that it would not be predictive, but I may be wrong. I have been wrong before; I hate to admit it. Mr. Hensarling. But regardless of the relevance or irrelevance, would you advocate the policy denying me that right? Ms. Saunders. I would advocate the policy simply of ensuring relevance. That is the policy I want. Mr. Hensarling. I seem to be out of time. Thank you. Mr. Castle. Thank you, Mr. Hensarling. Mr. Ford is recognized for 5 minutes. Mr. Ford. Just to follow up on a lot of questioning from my friend, any sense, real quick, of the profile of those who take out payday loans? Because I think the point my colleague made is interesting. I think most people who do, there is a perception that they have to be black and poor. And I think your point was that that is not the case, but the reality is, I do not think that the profile that my colleague has painted is necessarily an accurate one. Most people who go get payday loans are people who cannot get help from traditional sources. Although maybe the payday loan industry hopes it evolves to that point that you have envisioned, Congressman, I do not think that is the case at the moment. Maybe Ms. Nelson and others can dispute us. I saw her nodding when you raised your question. As wonderful a description as it is, I think it is more fictitious than it is realistic. I would ask the question, Ms. Nelson, you talked about how your scores are a solid predictor. I have a bias against what you all do. I want to start out before we get going. You say that as much as it is a solid predictor, you all do not have much control over what lenders do. Do you think you have any responsibility as to what lenders do, since you all developed that score? Ms. Nelson. We have a responsibility to help them understand what the score is predicting. Mr. Ford. Right. But we know that there are abuses, and you do not think that you have any responsibility to address it? I think the question that my colleague asked about, you take into account. Mr. Thomas was kind enough to say that it is done on an individual basis if it is a good point that a consumer may have about why they were late making a payment. But you all do not take any kind of systematic approach to this in terms of accounting for differences in prices and the fact that someone may hit a hard time. I am of the opinion that you all could do a better job than you do. It is easy to put the score out there and say, ``We have nothing to do with it now.'' You know what it is used for. You know how it is used. We voted on bankruptcy reform here in the Congress a while ago, and I voted for it because I did not think the credit card companies or others should be responsible fully for this. I think all of you all are responsible in some ways, and we have to start at the root and work our way across. But you do not think you have any responsibility to adjust when you know lenders are using it in ways that it should not be used or using it in ways that hurt consumers? Ms. Nelson. We have an obligation, first and foremost, to make sure that lender has permissible purpose to use the score. In terms of our ability to systematically adjust the score based on qualitative information about the consumer, it is virtually impossible. That is why the score is used as part of a decision process by any lender. I do not think that we should make the assumption that the score is the one and only aspect of the decision. Mr. Ford. How often do you think it is the one and only aspect? Ms. Nelson. It is the first aspect for the automated process. Now most of the customers that we work with, and Ms. Thomas is a terrific example, have manual underwriting processes so that if a consumer kicks out of that automated process for whatever reason, if the score is too low, or if there are other risk elements that makes that lender uncomfortable, that then moves into a manual underwriting process, both from a lender perspective, as well as if you talked to the GSEs. So our role in the process is really to help automate as much of the decisioning as we can, to streamline the process, bring out cost. Then once you have consumers that go outside of that automated process, we are absolutely supportive of manual intervention. Mr. Ford. But you do not apply any pressure for them to do any of that. You just provide the score. However they choose to respond to it, if you have good actors like Ms. Thomas or bad actors, or medium-level actors, you all do not really put any pressure on anybody. You just release the score. Ms. Nelson. I would say that is correct simply because I do not know what pressure we have on our customers to be able to influence their individual business practices. Mr. Ford. No, I did not ask if you could develop a kind of pressure point. I was just curious. You all do not do anything other than just provide the scores. Ms. Nelson. Correct. Mr. Ford. You are aware that sometimes the scores are used in ways that there are some good actors who are using it, as you cite Ms. Thomas's practices, and there are people who use it in a bad way. So you are aware that there is a variance in how the scores can be used and how some people will use the score not as the only factor but as part of a set of considerations. Ms. Nelson. I cannot say that I am aware of any specific examples like that, no. Mr. Ford. You just said Ms. Thomas uses it for certain purposes. Ms. Nelson. All I am saying is I would not characterize the fact that there is a score as a bad way. So we applaud efforts for lenders that want to go above and beyond the utilization of a score in their decisioning process. Mr. Ford. Right. So presumably that means it is good if you are applauding it. Right? Ms. Nelson. And presumably, we believe that most lenders do that very thing. Mr. Ford. But there are some that do not, and you all have to be aware of that too, right? You know some are not doing it, so presumably you would not applaud them. My only point is, I think you are more aware of things than you say you are. I hope this committee, as we look at nontraditional factors, we talk about payday loans. I say to my colleagues, we are one of the biggest payday loan users in the world; the United States is. Our payday loan folks are called Japan and China. And thank God they keep loaning us money to finance the things everybody here puts cards out for us to do. This is not a partisan thing at all, but of all the people in the country to be getting on people about debt, we at the Federal level, the United States Congress, trying to tell people how to manage their money better when we run $400 billion deficits year-in and year-out and a $7.5 trillion national debt is a remarkable thing. But God is in the blessing business, and maybe we will figure out a way to get out of this mess. I hope that we take very seriously what has been said today. I do hope that we can find better ways to gauge people's credit, basing it on how much people pay or if people are able to pay their light bills or their phone bills and stuff. I mean, we would not do this to rich people in this country. And to say to poor people that we are going to develop the system that you all are putting together, I think you can do better, and not you, but just the whole industry can do a lot better than what you all have presented us today. I am one person on this committee who will fight tooth and nail, Mr. Chairman, to ensure, I do not care what they look like. If they are working people, and they are trying to support their families, and factors outside of their control are causing costs to go up, they should not be saddled with a weak effort like we have heard here today. We should come up with a better way to determine these things. Whether you live in Delaware or Texas or Tennessee, and whether you are Democrat or Republican, there has to be a better way to do this. Ms. Nelson, I did not mean to jump on you, but I think if you all applaud certain practices, you ought to figure out a way to encourage those practices. It is the only fair way to do it. We do it here in the Congress, and you all should be expected to do it in the private sector as well. Mr. Castle. Thank you, Mr. Ford. Mr. McHenry is recognized for 5 minutes. Mr. McHenry. Thank you, Mr. Chairman This is mainly directed at Ms. Nelson, but I would love to have the whole panel chime in if you feel so led. It is interesting to me that we are debating sort of a regulatory scheme for the marketplace of credit. It seems to me that especially your company, Ms. Nelson, you are in a position where you are trying to have, I would say, a market advantage, that maybe your system of scoring is more accurate for institutions to use, that you are a better predictor of someone's credit worthiness. Is that your business, would you say? Ms. Nelson. Obviously, the Fair Isaac business has been built around the development of credit scores. What I came here specifically to talk about was the creation of a sister service called expansion score, which takes in the best alternative credit data available in the marketplace today for the purposes of helping to score those consumers that previously could not get a traditional score. So when we talk about regulatory framework, we sit perfectly inside the regulatory framework that exists today to ensure accuracy and completeness of data and, therefore, solid scores that can be developed from that data to predict the likelihood of credit risk for any individual consumer. Mr. McHenry. But there are many institutions that are doing exactly what you are doing. There is a choice that businesses can make to use your exact business rather than another's. Ms. Nelson. Correct. We are one option of many. And you have heard today Ms. Thomas talking about the processes they go through to evaluate whether or not they can extend a mortgage to a consumer. Mr. Catone has explained the same thing. So what the unique element of the service that we bring is that we are trying to help the industry automate all of this, so Mr. Catone is able to generate one-by-one consumer reports or nontraditional credit reports for any consumer that is applying for a mortgage. What we are trying to do is supplement that with an automated process that is going out and, at a macro level, finding data providers that have that positive information that we can pull together and generate a score. I think the clear difference here is that we are very supportive of all the other efforts. You could almost look at this expansion score as a first step. So if we are able to find information about checking accounts or payment plans where there is a lot of positive information, we are able to generate a score that is high enough for that lender to feel comfortable. It is a first step. It can either be used as a big piece of the decision or an indicator for the decision to move on and invest in the creation of a full-blown nontraditional credit report. Mr. McHenry. But it is the marketplace there which you are responding to. Is that correct? Ms. Nelson. Absolutely, absolutely. Mr. McHenry. Is there a regulatory framework that is holding you back in providing more accurate scores and a more accurate prediction of credit worthiness that perhaps Bank of America, let's say, needs, that they would like to have this additional information-- Ms. Nelson. Right. Mr. McHenry. --So they could extend credit? Ms. Nelson. If you look at a classic or a traditional credit score, typically I believe the average is maybe 13 credit lines feed into that score. Within the expansion score, we have a much lower number of alternative credit data sources or data points. And so, as we gain more and more alternative credit data to be made available to all of us in the industry, it is going to enhance our ability to get that score to be refined further and further for the consumers. So when you ask, is there a barrier, right now our barrier is trying to find those alternative credit sources to continue building and building the value of the score and the report that we are able to provide, which would then allow much more automation and efficiency in the process than having to go through the manual systems today on each and every one. It does not displace the need for the manual reviews, but it allows a lot more of those consumers to pass through the system without having to go through the cost of the manual reviews. Mr. McHenry. Dr. Turner, it looks as though I was going to you next. Can you describe the marketplace forces that are driving the direction that we are trying to go in here, with actually providing more information to extend credit? I think there is a great failure in Congress to understand that there is a marketplace, and the marketplace will drive innovation. The marketplace will drive a great advance in extending credit in many different things. We had a hearing just not too long ago about data security, and I think there is a marketplace for companies such as Bank of America. Bank of America has this wonderful commercial that describes the accuracy of their check processing and their innovation there and the accuracy by which the process the checks. I just think we need to look at what the marketplace is driving toward, and is there a barrier that government is imposing through regulatory schemes or laws or whatnot that are actually holding back this process of innovation. Mr. Turner. There are several questions there. Our study touches on some barriers that impede these flows. We talk about two economic barriers and two regulatory barriers. We surveyed about 25 State regulatory commissions, and we are only aware of regulatory barriers that forbid the onward transfer of telephone, wireless, wireline, electric, water, utility data in two States. So it is about 8 percent. We have no reason to expect the balance in the remaining 25 States that that number would be markedly higher. Those prohibitions were not expressly for preventing credit reporting. They had different purposes. So I do not see a substantial regulatory barrier in the States or federally. What is more important that in preventing this is the regulatory uncertainty. Utility companies want to report the data. One of the market forces driving them is cash flow. They have high delinquency and default rates. Reporting payment history is a disciplining mechanism. It improves cash flow. So they have a powerful market incentive that is driving the demand for this data. But they cannot report the data, the utility companies, because their regulators will not give them written permission to do so, even though there is nothing statutory that prohibits them from sharing the data. So yes, there are barriers, but they are more indirect and soft barriers than direct. Other market forces, and I think that my panelists got to this as well, there is a lot of this information that is gathered already. If you look at the mortgage insurance industry, mortgage insurers gather vast amounts of alternative data for use in underwriting decisions about mortgage loans. They collect data we have not even discussed here. They collect the presence of children, truancy issues. They manually verify all of this data. If there were a company or several companies that were able to systematically gather this data and then provide it to those who want it for their decisioning processes, that is an unmet need. It would be a tremendous efficiency for the mortgage insurers, for instance. So there are market forces compelling the collection of this data on a variety of different levels and a variety of different directions. Mr. McHenry. Thank you. Mr. Castle. Thank you, all. Thank you, Mr. McHenry. Ms. Maloney is recognized for 5 minutes. Mrs. Maloney. Thank you. And I thank all the panelists for being here today and for your testimony. One fact that many consumers are not aware of is having more than one credit card or two or three credit cards lowers your credit rating. This is particularly a challenge with young people or many people. They walk into stores. I represent New York. It is a large retail base. The Fair Credit Reporting Act was tremendously important to the city that I represent and to our economy for institutions to be able to have a Federal standard so they could make decisions and allow credit. But a side of it, and I would like to ask Bank of America, Ms. Thomas, consumers are not aware of this. Many promotions are always there. You can go into a store in my city or probably anywhere in this country and they will say, take out a credit card and we will give you 20 percent off; we will give you $100 if you spend $300 and take our credit card; we will give you $50--I mean, all of these promotions to entice consumers to have credit cards. In many cases, they may use the credit card just once, yet it remains on their credit file and lowers their credit rating. As a source of credit cards, what is your comment on it? Should we notify consumers that having more credit cards lowers their credit rating? By the time they try to buy a car or an apartment or whatever, their credit rating is ruined because they have 10 or 20 or 30 credit cards. Ms. Thomas. One of the ways that we try to address that is through consumer education. We do a lot of financial literacy at the school and college level. In talking to a college student who says they have 12 credit cards for emergencies, and you ask, what is the emergency? And it is to buy a dress to go to a party. That shows us lack of the education. So that is one way, not only college students, but other adults who also have the same issue. It is just continuous education is the best way, but it is still not enough. There is still more that needs to be done in that space. Mrs. Maloney. Do you think we should require better disclosure of this adverse consequence on credit cards so that people could be notified when they are applying? You do not even have to apply for a credit card in New York. They are practically hawking them on you. You get them in the mail. They mail them to you. In literally every store, you can go into a gum shop store, and they have their own credit card. So do you think if we required better disclosure: ``Congratulations, you have this credit card, but please be aware that if you have more than three credit cards, your credit rating will be lowered.'' Ms. Thomas. I do not know that it should be a requirement. I think it needs to be an awareness that is continuously done so people know that that is a problem, because you are right. Most people do not know. Mrs. Maloney. I would like to ask the credit agencies--and we all have challenges in our work. Ms. Nelson and Mr. Catone, could you clarify for me what is the procedure in the credit agencies? And why is it a decision to lower credit if someone has 10 cards? If a consumer has 10 cards and they have totally paid off the debt so they have no debt, why do you lower the credit card rating? This was an issue in the Fair Credit Reporting Act. We became aware that you could have had a credit card for 10 years, maybe used it once, paid off the debt, but still your rating would be lowered if you had more, I believe, than three cards. Could you clarify what the standard is? To me, I think when you are looking at credit, you want to know what the person's payment schedule is and what the debt is. So if a person had 100 cards and they paid off all their debt, why are you lowering the credit rating on them? I was told the standard was three cards, and then you lower the credit standing, but maybe you could clarify our understanding of it. Mr. Catone. Maybe Ms. Nelson can clarify one part of that. There are two pieces here. One is the alternative data or the nontraditional data. Many underwriting standards allow compilation of payment pattern history, one being credit cards or utility data, rent data, whatever. These underwriting standards in the mortgage industry at least have been very, very different than the traditional. You see that Fair Isaac has come out with a different score for that application. I think what you are referring to is the existing type of scoring mechanisms that have been in the marketplace and are in wide use today, if I am not mistaken. And that is a more general issue. So there are two here. Mrs. Maloney. Okay. I would like to understand how the credit agencies create their credit scoring as it applies to the number of credit cards that you have. Could you answer that? I was told by a credit agency when one of my constituents called, that if anyone had over three credit cards, their credit scoring was lowered. Is that true? Ms. Nelson. I cannot say specifically if it is true or false, but I can tell you that more important than the number of cards possessed by a consumer is what degree of debt have they consumed on those cards. So if I have three cards and they are all maxed out, it is a very different scenario than having three that are not in use. Right? Mrs. Maloney. The example that I am using is every credit card is paid off completely at the end of the month. There are 10 credit cards that the consumer has not even used in 10 years. They used them in college. Ten years later, they are not using them. They are still on their credit report, and just the mere fact that they have the credit cards lowers their score, even though it has been paid off completely. Consistently for 10 years, there has been no debt on those credit cards. I was told that it lowers the credit scoring. Can you clarify that? If you cannot do that today, would you get back to us in writing? Because I have heard it three or four times from constituents who are stunned when they finally go to get a credit score that they have a low score, although they have no debt, make a lot of money, always pay their debt, always pay the credit card off at the end of the month, only use one of them. Yet just the mere fact that from their college days or whatever or because there was a promotion that gave them 20 percent off or whatever, they have a terrible credit score. I think that that is a problem, and people should be aware of it, and they are stunned to find out about it, and I was stunned to find out about it. Ms. Nelson. And that is exactly what I will do. I will go back and get specific information around that question of number of cards. I cannot tell you specifically today how it would, if at all, affect a score, but I will gladly research that and get back to you. Mr. Castle. Thank you. Thank you, Ms. Maloney. Mrs. Maloney. Okay. Mr. Castle. Mr. Clay is recognized for 5 minutes. Mr. Clay. Thank you, Mr. Chairman. And I thank the panel for participating today. Getting access to credit at reasonable rates is one of the more difficult tasks faced by minorities, women, moderate-and low-income workers, and immigrants. Credit agencies cite that there is insufficient credit history using traditional data in a majority of the cases. Do we have conclusive evidence that employing the use of nontraditional credit information is effective in dealing with minorities' problems of limited access to credit? And how effective is the use of these? And what do we compare the results to? Anybody can tackle it. Ms. Thomas. What we see at Bank of America is that there are individuals that we would have otherwise declined because they did not have enough credit that we can say yes to because we are trying to figure out, within reason, because you do not want to put somebody in a home they cannot keep, because it is not about getting a loan, it is about keeping it. But if we did not utilize some of the nontraditional data, we would have to say no. And if a person has demonstrated good payment behavior, then that is a way of getting them into that home. Mr. Clay. Well, how reliable is the use of nontraditional data in determining payment behavior patterns or any other credit-related behavior? What suggestions do you have to address this problem? Ms. Thomas. In terms of reliability? Mr. Clay. Yes. Ms. Thomas. Because the process is so variable from customer to customer and type of alternative credit you would use, we have seen some data that shows good behavior, especially around rental data, but other types of data, there is still more analysis to be done, and we only do it on such a limited basis because there is such variability in it. Mr. Clay. Well, how about young people just starting their jobs, careers? How do you gauge whether they are worthy of a home loan or worthy of a credit card? Do you take in extenuating circumstances, other factors to determine that? Ms. Thomas. For a young person just starting out--because I had several people on my staff under 30, which was good learning for me--they may have been paying rent to a parent, and they could demonstrate it, or they were paying rent on an apartment. So that is an example of one. They may have one credit card. Some have a bunch, and we worked on those. So that is data we can use, but they typically will be a thin file because they do not have enough, but it is the same thing. They can demonstrate payment history. Mr. Clay. Ms. Thomas, let me ask you, some young people that come right out of college are heavily indebted with student loans. Do you ever give consideration to them as far as purchasing a home and then rolling that student loan into the mortgage? Ms. Thomas. We give consideration to that, but if we see where there is a severe struggle with doing that, along with other debt, oftentimes what we will do is refer that young person to some credit counseling. They do not have to take it, but we want to get them in better shape now so that they can continue to progress not only with that mortgage, but other things as well. So sometimes we can say yes. Sometimes we have to refer them and hope they will come back after we have educated them. Mr. Clay. I see, after they have accumulated some time and credit history. Ms. Thomas. And understand what they can do to improve their situation. Mr. Clay. Thank you for your response. Mr. Catone, how do you view the use of such nontraditional credit score such as the FICO expansion score and the instant- merge credit reports? How do each of them reach their targeted consumer groups? Are the programs having a major impact on helping consumers get better access to credit? Mr. Catone. What I want to point out is that the financial services industry is very automated today. There is a heavy investment in technology, process, and things to make it very economical and fast to underwrite a consumer for any financial instrument. In cases where there is obviously not enough data and things of this nature, it falls into a special category. As the other panelists have noted, it goes into a manual process. It takes longer. It is more difficult. The consumer does not understand these things. So there are a variety of underwriting criteria depending on the program, Bank of America's program or what have you, that override and can adjust for different types of situations, credit counseling being one of those; other types of payment history data being those types as well. So I think you have to look at the underwriting standards that are in the industry today, specifically counseling. There are many studies out that have proven that pre-home purchase counseling contributes to the integrity of being able to repay that loan and budget and things of this nature. Mr. Clay. Thank you for that response. Thank you, Mr. Chairman. Mr. Castle. Thank you, Mr. Clay. We appreciate your being here and appreciate your questioning. We are going to bring this to a close. We appreciate all the panelists being here and for answering our questions. It is possible that some of the members may have additional questions for the panel which they will submit in writing to you in the course of the next 30 days. I do not know how likely that is; nobody has seemed to opine that way today, but that could possibly happen. So with that, I declare this hearing adjourned. And thank you again for being here. 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