Fair Lending

We perform comprehensive, independent validations of Fair Lending analytics across all model types and use cases:

1. Underwriting and Credit Decisioning Models

We evaluate credit models for potential disparate impact across protected classes (e.g., race, ethnicity, gender, age) using methods such as:

• Adverse impact ratio testing

• Proxy methodologies (e.g., BISG, surname/geocoding)

• Comparison of approval, decline, and referral rates

2. Pricing and Rate Assignment Validations

We review pricing models for fair and consistent application across similarly situated applicants by evaluating:

• Risk-based pricing logic

• Fee and rate dispersion analysis

• Exception tracking and discretionary pricing practices

• Alignment with rate sheets and policy documentation

3. Marketing, Targeting, and Prequalification Models

We review models and segmentation strategies used in marketing or pre-screening to ensure:

• Inclusive outreach across demographics and geographies

• No disparate targeting or exclusionary practices

• Transparent eligibility criteria for offers and outreach campaigns

4. HMDA & LAR Data Integrity Reviews

Accurate and complete HMDA reporting is critical for fair lending compliance. We conduct a detailed end-to-end validation of your Loan/Application Register (LAR), including:

• Data mapping and transformation reviews from origination and servicing platforms to the LAR

• Field-level accuracy checks (e.g., race, ethnicity, sex, age, income, action taken, denial reasons, pricing)

• Cross-system reconciliation to ensure consistency between application systems and HMDA submissions

• Review of edit check resolution processes and exception tracking

• Verification of applicant data input sources, including the accuracy of collected demographic information