FairBorrow™.Ai provides an AI‑driven platform that analyzes both internal loan data and public sources such as HMDA to detect disparities, prohibited decision factors, and anomalies in mortgage underwriting. By delivering visual dashboards, geographic mapping, and automated compliance reports, it helps lenders improve decision consistency, reduce bias, and mitigate fair‑lending regulatory risk.
Funding
Funding not disclosed
Founders
Product
Problem
Financial institutions face regulatory risk and reputational damage due to inconsistent loan underwriting decisions that can contain bias against protected groups. Detecting disparities, decision anomalies, and compliance gaps across large mortgage portfolios is time‑consuming and often requires manual analysis of public datasets such as HMDA.
Solution
FairBorrow™.Ai applies generative AI and proprietary data‑management techniques to analyze both proprietary loan data and public sources (HMDA, Census) for fair‑lending compliance. The platform automatically identifies disparity factors, prohibited decision factors, and decision anomalies, delivering actionable insights that improve decision consistency and reduce bias. Users can run consistency checks on individual loans or bulk batches, and risk managers can review historical decisions to spot regulatory exposure. Results are presented through visual mapping tools, disparity metrics, and risk assessments that align with fair‑lending regulations, enabling lenders to proactively mitigate compliance risk.
Target Audience
Primary users are mortgage underwriters, compliance/risk managers, and data researchers at banks, credit unions, and mortgage lenders who need to ensure fair‑lending compliance and improve underwriting consistency.
Features
- AI‑driven analysis of HMDA and internal loan data to surface disparity of decisions across protected attributes (age, gender, race, ethnicity)
- Automated detection of decision anomalies where similar applications receive different outcomes
- Identification of prohibited decision factors and validation of permissible factors used in underwriting
- Full‑lifecycle risk dashboards covering application, steering, underwriting, pricing, policy exceptions, marketing, and redlining risks
- Geographic mapping and custom area visualizations for county, metro, and state‑level performance
- Bulk consistency checks for single‑decision or weekly loan batches, with team‑level aggregation
- Exportable compliance reports and alerts that integrate with existing risk‑management workflows