The introduction in 2006 of the VantageScore model brought true competition to consumer credit scoring. The industry was long dominated by a single brand of credit score model. Since that time, regulators have regularly proclaimed the importance of protecting choice in the credit score marketplace.
Regulators that have recognized the VantageScore model include:
Consumer Financial Protection Bureau (CFPB)
Department of Housing and Urban Development (HUD)
Federal Financial Institutions Examination Council (FFIEC)
Federal Housing Administration (FHA)
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Federal Trade Commission (FTC)
National Credit Union Administration (NCUA)
Office of the Comptroller of the Currency (OCC)
Securities and Exchange Commission (SEC)
The ultimate indicator of thorough regulatory recognition is the thousands of lenders, including 7 of the top 10 financial institutions, which have successfully implemented the VantageScore model and use it millions of times each day in their businesses. The model has been implemented under the watchful eyes of regulators across all major credit categories.
On January 1, 2014, the Federal Reserve Board began accepting VantageScore data in its Capital Assessments and Stress Testing Report (FR Y-14M). This report, part of the Fed’s Comprehensive Capital Analysis and Review (CCAR) program, is required by law under both Dodd-Frank and the Bank Holding Company Act for all bank holding companies considered SIFI banks (Systemically Important Financial Institutions). This extends to domestic institutions and domestic subsidiaries of foreign institutions. Before 2014, FICO was the only credit scoring brand accepted in the FR Y-14M report.
The OCC recently revised its guidelines for banks that engage in mortgage financing, issuing a 235-page guidebook that, among other things, updates guidance to examiners and bankers on assessing the quality of mortgage banking risk management. The guidebook discusses credit scores but, in a nod to competition in the credit score market, does not mention the FICO credit score model anywhere. What’s more, the guidebook cites only one vender-provided credit score model, the VantageScore model. Page 225 of the guidebook’s glossary describes VantageScore as a model that uses “a single methodology.”
A 2012 ruling1 by the Federal Deposit Insurance Corporation (FDIC) changed the way large lenders define and calculate risk for their Deposit Insurance Assessments on higher-risk consumer loans. One of the key changes is that in defining what constitutes a higher-risk consumer loan, the FDIC replaced the traditional three-digit credit score used to set its risk threshold with “probability of default” (PD). Based on the rule, the new definition for a higher-risk loan is one that has a 20 percent or higher probability of defaulting in two years.
The rule specifies the use of PD values as a universal way of expressing loan-repayment risk. It allows the FDIC to assess and compare credit risk easily and uniformly, from lenders who use any commercially available generic credit scoring model, or their own proprietary credit scoring model, for internal risk evaluations.
1Source: 77 FR 11, October 31, 2012, at 66,000-66,024
In their preamble to final credit score disclosure rules implementing the amendment to Regulation V (Fair Credit Reporting), as required by the Dodd-Frank Wall Street Reform and Consumer Protection Act, the Federal Reserve Board (FRB) and the Federal Trade Commission (FTC) specifically named VantageScore.
Consumer Financial Protection Bureau (CFPB)
If all data about a consumer were the same at each of the three CRAs [Credit Reporting Agencies, i.e., national credit reporting companies, Equifax, Experian and TransUnion], the VantageScore for that consumer would be the same no matter which CRA’s credit report was used to provide the data.
— CFPB Report to Congress on Credit Scores, July 19, 2011, pages 7–8
Treasury Department, Federal Reserve, Federal Deposit Insurance Corporation (FDIC), Federal Housing Finance Agency (FHFA), Securities and Exchange Commission (SEC), and Department of Housing and Urban Development (HUD)
The Agencies’ own analysis, as well as work published in academic journals, indicates that borrower credit history is among the most important predictors of default. In many datasets, credit history is proxied using a credit score, often the FICO score determined under the credit scoring model devised by Fair Isaac Corporation. … Data on residential mortgages purchased or securitized by the Enterprises also show the importance of borrower credit scores as a predictor of default.
In developing the proposal, the Agencies carefully considered how to incorporate a borrower’s credit history into the standards for a QRM. The Agencies do not propose to use a credit score threshold as part of the QRM definition because such a standard would require reliance on credit scoring models developed and maintained by privately owned entities and such models may change materially at the discretion of such entities. There also may be inconsistencies across the various credit scoring models used by consumer reporting agencies, as well as among different scoring models used by a single provider. Consequently, in order to ensure that creditors continue to choose among different credit score providers, the Agencies would have to determine a cutoff score under multiple scoring models and periodically revise the regulation in response to new scoring models that might arise.
— Treasury Department, Federal Reserve, FDIC, FHFA, SEC, and HUD, “Credit Risk Retention: Proposed Rule” (Source: Federal 76 FR 83, April 29, 2011, at 24,121)
Federal Housing Administration (FHA)
While FHA’s historical data and analysis is derived from the “FICO-based” decision credit score, it is not FHA’s intent to prohibit the use of other credit scoring models to assess an FHA borrower’s credit profile. In this notice, FHA seeks comment on the best means for FHA to provide guidance to the industry on acceptable score ranges for other scoring models, to ensure that the scales used for all scoring systems are consistent and appropriate for an FHA borrower.
— FHA “Risk Management Initiatives: Reduction of Seller Concessions and New Loan-to-Value and Credit Score Requirements” (Source: Federal 75 FR 135, July 15, 2010, at 41,220–41,221)
Federal Housing Finance Agency (FHFA)
Credit Score Terminology. The proposed rule provided a market analysis to support the proposed adjustment of the housing goals levels for 2009, and discussed the effect of tighter underwriting standards of private mortgage insurers and the reduction in mortgage insurance availability for borrowers with low credit scores. A credit reporting corporation and a credit scoring corporation commented that FHFA’s analysis should not specifically reference “FICO” credit scores, stating that the reference implies endorsement of the Fair Isaac Corporation product and creates an unfair advantage. FHFA did not intend to endorse a specific product. Accordingly the market analysis in the final rule refers generally to credit scores rather than to a specific product.
— Federal Housing Finance Agency “2009 Enterprise Transition Affordable Housing Goals” (Source: Federal Register 74 FR 152, August 10, 2009, at 44,532–44,533)
Federal Reserve System
The Board also continues to believe—and few, if any, commenters disagreed—that the best way to identify the subprime market is by loan price rather than by borrower characteristics. Identifying a class of protected borrowers would present operational difficulties and other problems. For example, it is common to distinguish borrowers by credit score, with lower-scoring borrowers generally considered to be at higher risk of injury in the mortgage market. Defining the protected field as lower-scoring consumers would fail to protect higher-scoring consumers ‘‘steered’’ to loans meant for lower-scoring consumers. Moreover, the market uses different commercial scores, and choosing a particular score as the benchmark for a regulation could give unfair advantage to the company that provides that score.
— HOEPA rules adopted in July 2008 (Source: Federal Reserve System, 73 FR 147, July 30, 2008, at 44,532–44,533)