Underwriting and credit risk management
Over the last 20 years, the consumer lending industry has become an analytically intensive and data-driven business. Although the credit card industry was the first to adopt analytical techniques in every aspect of its business, other consumer lending industries, including automotive and mortgage, are also employing sophisticated analytical techniques to improve understanding their customer base, to control credit risk, and to identify profit opportunities.
We take a rigorous analytical approach to assessing the economics of the consumer finance business to provide insightful solutions for our clients. Bates White’s experts possess hands-on industry experience and a comprehensive set of capabilities to assist participants in consumer finance-related disputes or regulatory matters. Our experience includes developing pricing, underwriting, and statistical modeling strategies to enhance the economic performance of consumer finance businesses. Our professionals have constructed sophisticated pricing strategies, developed mass customized marketing campaigns, conducted customer segmentation and profitability analyses, and devised approaches to combat adverse selection. Based on this background, Bates White’s experts have developed economic models and statistical tests for complex litigation disputes and frequently provide advisory services, litigation support, and expert testimony to a variety of corporate and legal clients.
- In the matter United States v. Wells Fargo Bank, served as testifying expert on behalf of the Department of Justice in connection with allegations that Wells Fargo defrauded the Federal Housing Administration (FHA) on loans that Wells Fargo underwrote and submitted for FHA endorsement. Determined damages arising from insurance claims on loans that allegedly failed to meet FHA-mandated underwriting guidelines. Wells Fargo agreed to a $1.2 billion settlement.
- Composed expert report analyzing the business model, operating performance, and expected credit losses for a subprime auto finance company. Estimated future cash flows for each quarterly static pool. Report included a detailed analysis on the expected performance improvement in credit losses related to the company’s recent adoption of a custom-built statistical credit scoring model. Forecasts included estimated loan defaults, repossession recoveries, interest and noninterest revenues, attrition, and servicing expenses.
- Served as testifying expert on behalf of a major issuer of retail credit cards involved in a confidential tax dispute with the Internal Revenue Service. Analyzed beneficial life of store credit card drawing on the company’s point-of-sale data, credit card data, marketing and promotion activities, and customer demographic information.
- Produced credit loss forecasts for a subprime auto finance portfolio transferred from original servicer to back up. Analysis relied upon credit loss performance for hundreds of auto finance asset backed securities structures. Demonstrated post-servicing loss experience was consistent with pre-servicing loss performance.
- On behalf of Mitsubishi Motors Credit of America (MMCA), provided direct and cross-examination testimony regarding expected credit losses for loans originated by MMCA and subsequently sold to Household Auto Finance in ADR proceeding of HSBC Auto Finance, Inc v. Mitsubishi Motors Credit of America, Inc. Demonstrated that the credit loss information submitted by the offeror during the due diligence phase of a loan portfolio sale accurately reflected the credit quality of the portfolio. Successfully challenged the purchaser’s damages estimate. The three judge arbitration panel, in ruling unilaterally for our client, found that the purchaser’s damages calculation was highly speculative and not supported by the evidence.
- For auto finance division of a top-10 credit card issuer, one of our experts developed and managed the credit risk management department and the marketing department of a major auto finance company. Built and instituted multiple prescreening and applications credit risk models to lower risk while raising response and approval rates. Created four new direct marketing programs. Aligned price and risk-on-product tiers to achieve above-hurdle ROI performance on all products and customer segments. Constructed target population segmentation algorithms to maximize ROI and NPV of marketing expenditures. Built and instituted credit risk models to lower risk while raising approval rate. Improvements resulted in 100 percent growth rates while reducing credit risk exposure.
- Provided statistical consulting on the development of initial artificial neural network systems for real-time detection of credit card fraud for a leading fraud and credit risk modeling software firm.
- Developed expert report for litigation on behalf of a prime auto finance company. Report analyzed company’s origination strategy, credit characteristics and loss performance relative to comparable benchmarks of similar portfolios. Report also included affirmative estimates of expected credit losses for finance company’s securitized portfolio.
- Developed state-of-the-art statistical models to account for default correlation for underwriting credit insurance. Models became the standard tools for the country’s largest credit insurance firm.
- Our experts have served as consulting experts and analyzed data for a major credit card transaction processor. Managed development and implementation of artificial neural network credit card fraud model and created strategies to integrate results into business systems. Expanded scope of original product to include capabilities for strategic pricing and account management campaigns.
- Provided expert consulting services as part of arbitration proceedings involving a dispute over residual value insurance coverage and reinsurance in connection with portfolio of automobile leases. Constructed a stratified sampling strategy to evaluate various coverage issues and audit key underwriting characteristics for the selected sample. Analysis included critiques of statistical sampling techniques used by other experts involved in the proceedings.