Financial Regulatory Compliance

CRA develops and conducts statistical analyses to detect lending disparities or to refute allegations of discrimination. We also assess claims of unfair, deceptive, and abusive acts in lending, and analyze breaches of contract and damages. We have analyzed pricing, underwriting, and credit scoring models, and have calculated proxies for race, ethnicity, and gender using multiple statistical methodologies.

Our consultants support counsel in matters pertaining to class certification, fact discovery, loss causation/materiality, damages, and settlement/mediation. We can estimate predicted loan application outcomes and prices, determine average expected fees for loan originations, and calculate economic damages in both single and multi-plaintiff matters. Our experts have also testified in class action matters related to the origination or securitization of mortgage loan products involving:

• Reverse mortgages
• Forced-placed insurance
• Discrimination allegations
• Insurance false claims on FHA loans
• Loan modifications

Many FinTech lenders have begun to use machine learning, AI, and alternative data in their risk and marketing models. We help lenders assess their models’ credit performance and statistical validity. We also help to evaluate any tradeoffs between performance and fair lending regulatory compliance. 

CRA helps financial institutions and their counsel manage exposure to compliance issues. We perform statistical analysis to help clients continually evaluate and monitor their fair lending and other compliance risks, as well as respond to inquiries from regulators. Our team has extensive experience developing and validating financial models and in providing model risk management reviews, credit risk analyses, and reviews of marketing materials for UDAAP compliance.