Benefits for Lenders

VantageScore assists credit grantors with lending decisions in a manual or automated environment:

• Reduce the time to review the application manually by setting a cut-off score strategy
• Use the score for tiered offers with multiple cut-off strategies; for example, extend the most favorable offer to your most creditworthy consumers and appropriately adjusted offers for those consumers that are in the middle segment of credit risk and those consumers that are more credit risky
• For deposit/no deposit (pass/fail) strategies, set one cut-off to request a deposit or determine whether a consumer would fall into a risk category that is unfavorable for your business need
• When acquiring customers, use VantageScore in conjunction with custom application and bankruptcy scores for more accurate decisions
• For account management, use VantageScore with a custom behavior score to determine appropriate cross-sell, activation and re-pricing decisions

Characteristic Leveling Overview

Credit characteristics are a foundation of consumer credit decisioning. Inconsistent definitions in attributes across the three credit reporting companies may result in vastly different risk perspectives when assessing credit risk. In particular, this is true for the majority of consumers whose credit profile is housed by more than one of the three credit reporting companies.

Characteristic leveling is the process that yields consistent and equitable attribute definitions across multiple sources of information. Simply put, this leveling ensures that when the same data is present in multiple sources - here, two or more credit reporting companies - it is interpreted in the same manner, keeping in mind that differences in the data itself may still be present.

For consumer credit grantors, using leveled characteristics creates a more consistent picture of a consumer's credit payment behavior, regardless of which CRC's data is being used. Therefore, with VantageScore, credit grantors can have confidence that they are making a consistent credit decision when applying the same characteristics to different sets of data.

Read the entire white paper about Characteristic Leveling.

Scoring the Thin File Population

VantageScore provides credit grantors with a reliable, predictive scoring solution with the decisioning insight required to extend credit with confidence to a greater percentage of thin file customers (consumers with three or fewer trades in their credit file). It is estimated that between 35 and 50 million adults in the United States may be considered unscorable, equivalent to 18 to 25 percent of the adult population. This result is a significant number who may be blocked from credit or incorrectly priced because lenders are unable to leverage their standard decisioning strategies.

Because it is difficult to assess the creditworthiness of thin file consumers, mainstream lenders largely ignore this vast category of potential consumers (or have had to default to costly manual underwriting processes), despite the likelihood that many would prove to be low-risk consumers.

VantageScore expands the trade update criteria from six months to 24, allowing VantageScore to score people who may have been "out of the credit market" for up to two years.

Additionally, VantageScore will include consumers whose oldest trade is less than six months old.

The ability to better distinguish between consumers with a clear track record of unfavorable credit behaviors from those simply starting to develop credit histories is a significant advantage. Individuals in the latter group typically include:

• Young adults just starting their careers
• Recently divorced or widowed individuals with little or no credit in their own name
• Newly arrived immigrants
• Previous bankrupts
• People who shun the traditional banking system by choice

Universe Expansion

The predictive power of VantageScore enables lenders to find more creditworthy consumers. The table below illustrates the lift in scoreable consumers using VantageScore over traditional credit risk scoring models. Keeping delinquency rates constant for the population in each score interval, the overall lift in scored consumers using VantageScore versus some traditional credit risk scoring tools is 8.1 percent; the lift in the subprime score interval increased to more than 11 percent.

VantageScore vs. a Generic CRC Risk Score

— Random sample of subprime mortgage consumers
— Lift of 8.1% overall; 11.4% lift in Subprime

Population of consumers with a mortgage tradeline and valid risk scores

Traditional CRC Risk Score score intervals	VantageScore scored population	CRC Risk Score scored population	Lift in percent scored
< 840	37,200,879	35,650,730	4.3%
< 710	20,770,817	19,222,143	8.1%
< 690	18,905,850	17,361,704	8.9%
< 660	16,443,381	14,992,740	9.7%
< 675	14,743,723	13,403,763	10.0%
< 645	13,008,548	11,738,798	10.8%
< 620*	11,968,160	10,746,894	11.4%
Total	133,041,358	123,116,772	8.1%

Powerful Risk Assessment

VantageScore was developed to better distinguish between consumers with varying levels of credit performance; rather than defining all consumers with incidents of poor performance as equally bad regardless of whether they have one bad trade out of 20 trades or 15 bad trades out of 20. Appropriately, VantageScore identifies the consumer with only one bad trade out of 20 as lower risk than the consumer with 15 bad trades out of 20. The benefit is that lenders can be much more precise in defining risk tolerance and thereby assign appropriate risk-based pricing.

Population Segmentation

VantageScore first groups consumers into one of 12 homogeneous segments and then calculates the consumer's VantageScore within the segment. Each population segment is defined by a combination of characteristics and score. This facilitates population stability by segment and reduced score volatility due to the multiple characteristic compositions. VantageScore identifies the 'best of the worst' in each segment and the segment IDs are provided to lenders with the consumer score, enabling lenders to determine consumer credit profile with more specificity.

No Authorized-User Trades

VantageScore excludes authorized user tradelines, whether with good or bad payment histories, from the final score algorithm. This approach ensures the risk assessment of a potential borrower represents the true credit risk of the prospect and not that of the actual borrower with whom the authorized tradeline is associated. This credit score will allow lenders to make accurate risk decisions during the underwriting process, ensure new account originations align with internal risk policies and do not pose a threat to the overall financial health of the portfolio once acquired.

Development Window Reflects Latest Economic Trends

VantageScore development utilized anonymous consumer credit files from the June 2003 to June 2005 timeframe, reflective of economic trends and shifts in consumer credit behaviors. The VantageScore model will be re-validated on a regular basis to maintain timeliness and optimize predictiveness.