Easy-to-use, interactive, and accessible to lenders of all sizes.
Matched Pair Testing
Easily conduct automated matched pair testing by selecting custom control vs. target settings and establishing credit or pricing tolerances to identify similar or better situated applicants with different outcomes in underwriting and pricing. Individual files can be accessed directly from results screen for further review.
Fair Lending RELIEF includes detailed reports, easy to understand graphs, and an interactive tool that allows you to view the data behind the result. Easily review and analyze key fair lending risk factors across applicant demographic and geographic categories:
Analyze the geographic distribution of lending activity based on MSA, state, and county – inside and outside of an assessment and/or analysis area.
Identify potential application disposition disparities for all actions, including positive and negative outcomes.
Levels of Assistance
Evaluate differences in levels of assistance based on average days to disposition, as well as the lowest and highest number of days for individual applications.
Review and analyze pricing disparities using rate spread, APR, and interest rate, as well as key indicators such as average loan amount, credit score, and debt-to-income.
Assess potential steering risk associated with the type of loan (conventional, FHA, VA, FSA/RHS), channel (retail, wholesale, correspondent) or based on loans decisioned using an Automated Underwriting System (AUS) or manually underwritten.
Analyze performance based on Majority Minority Tracts (MMT), Majority Hispanic/Latino Tracts (MHT), and Majority Black/African American Tracts (MBT).
Review and analyze peer data to quickly identify credit needs and competitive concerns for a selected geography.
- Analyze peer performance using self-identified peers, 50-200% of your lending activity, or all peers
- Identify the number of loans needed to achieve parity for specific demographic groups
- Generate reports for senior management, marketing and compliance personnel
Import consumer application data and automatically assign proxy data for race, ethnicity, and gender, as well as Bayesian Improved Surname Geocoding (BISG) for both applicants and co-applicants.
Interactively review the geographic distribution of your lending for a selected assessment or analysis area based on Tract Income Level, Majority Minority Tracts (MMT), Majority Hispanic or Latino Tracts (MHT) or Majority Black or African American Tracts (MBT). Select filters to determine concentrations and gaps in lending based on loan characteristics.