Tapping The Credit Underserved Market

Excerpt from: {see} Digital Magazine - Issue #4
Published: July 15, 2008


Alternative Data and the FICO® Expansion® Score

The consumer credit markets function fairly efficiently for 80% percent of the U.S. adult population. But for those individuals who do not have a FICO score, their "thin file" is a barrier to participation in the mainstream economy. It is estimated that 50 to 80 million individuals have limited access to credit and capital, primarily because their credit history is “thin” or non-existent and cannot generate a credit score. This impedes lenders' ability to make credit decisions that can enable an individual to buy a home, car, insurance, get a job or start a business.

The Federal Trade Commission, exploring "whether there are any common financial transactions not generally reported to the nationwide consumer reporting agencies (CRAs) that would provide useful information in determining a consumer’s credit rating" concluded that utility payment data are promising.

From a consumer perspective, the FTC’s idea is that vendors doing business involving recurring payments made following receipt of a product or service like electricity could potentially supply that payment history to fill out "thin" and "null" files so that they become "scoreable."

Consumer advocates also view this strategy as a way to balance an individual’s credit file with positive payment history that not only builds out a “thin” file but also offsets any negative data. For example, utility companies typically do not report all payment history for each customer (full file reporting) but do refer collection problems to collection agencies which report the negative information to credit bureaus.

Therefore, when a nonpaying utility customer possessing a thin credit file is referred for collection, that customer’s file will contain a report of nonpayment from the collection company). However, that report will not be balanced by the consumer’s history of positive payments, which might be extensive. Balancing negative data with positive payment history data would provide a more accurate picture of the consumer’s capacity to assume credit, and improve a creditor’s basis for estimating risk.

Total credit-underserved market is about 50 million consumers: Fair Isaac estimates that of the 215MM credit eligible adults in the US, around 50 million are unable to receive a traditional FICO® risk score. The US House Committee on Finance estimates that between 50 and 80 Million are not participating in the credit markets because of little or no credit history.

Scoring has democratized access to credit. Credit bureaus and FICO® scores have helped lenders provide unprecedented access to credit for the majority of the US population. However, this system has failed to adequately meet the needs of "unscoreable" consumers who have been avoided or declined by traditional credit granting methods.

The challenge of evaluating consumers with no credit reports and no credit scores
Without a credit history and FICO score, lenders must process their credit applications the old fashioned, time-consuming, and costly way. Each applicant must provide documents such as copies of rent and utility payments, verification of employment history and home address, and others. Even if their applications are approved, they often pay higher interest rates because, with little or no credit history to consider, lenders have difficulty assessing credit risk accurately.

Alternative data sources and FICO Expansion Score offer a tremendous opportunity to small businesses that focus their attention on this credit-underserved market:
The underserved credit market is emerging as an economic driver of credit data alternatives because of both its size and the cultural characteristics. The underserved credit market consists of a growing Hispanic and Asian immigrant population and it also includes long established communities of African-, Hispanic- and Asian-Americans. Furthermore, the credit-underserved market includes senior citizens whose numbers are swelling as the baby boomers age; it includes the newly divorced, and young entrants into the full-time workforce, some of whom moved directly into the workforce from high school and others joining the labor market following high education. This complex set of populations may have thin files for many reasons unrelated to their ability to repay debt.

Alternative data and the FICO® Expansion® score help lenders and other businesses remove the guesswork and inconsistency of working with this credit-underserved population. The FICO Expansion score is a credit risk score from Fair Isaac designed specifically to help lenders extend credit to consumers in new markets. Because it is based on non-traditional credit data, it can effectively predict risk for the growing number of US consumers that fail to receive a traditional FICO® score due to non-existent or "thin" credit histories.

It helps lenders better serve the "credit-underserved" market. Because it uses alternative data sources, the Expansion® score helps lenders confidently extend credit to consumers that are typically excluded from the traditional credit-granting process due to insufficient credit histories.

It helps "new-to-credit" consumers gain access to credit faster. It can help consumers gain access faster to traditional credit products like credit cards, car loans, or home loans from reputable lenders by evaluating financial relationships that are absent in credit bureau reports.
It's a credit risk score. It accurately predicts the likelihood that a consumer will become seriously delinquent in the 24 months following scoring. It looks at many factors, and the relationship between them, to give the best possible forecast of each person's future credit performance.

3-digit score. Complex data on a consumer is distilled into an actionable numeric score. And because it is a FICO® score has similar scaling to the Classic FICO scores making it easy for lenders to use.

It's based on alternative data sources. The FICO Expansion® score evaluates data from multiple non-traditional data sources to provide a complete view of the consumer's credit risk.

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