Credit Decisioning
Built for Scale.
AI underwriting, SHAP explainability, and governance — production-ready for lenders who can't afford guesswork.
Designed for institutions operating under SR 11-7 · FCRA §615 · CFPB guidance
Products
Three tools. One credit stack.
From underwriting to explainability to governance — every layer you need, purpose-built for regulated lending.
Architecture
How It Works
Input
Applicant profile submitted via API or Product Lab
Rules
Hard constraints evaluated — FCRA-compliant rejection gates
Inference
ML model scores the application, SHAP computes factor weights
Decision
Structured JSON response with audit trail — under 500ms
See a Decision. In Real Time.
Every decision returns a structured, auditable JSON payload.
▊Case Studies
Real outcomes. Real institutions.
Expanding Credit Access for Thin-File Applicants
+18%
approval lift
Income-first ML model closes the gap for applicants with no credit history.
Read case study →Credit Decisioning for the Gig Economy
+31%
approval lift
Employment-length-tolerant model captures repayment capacity traditional models miss.
Read case study →Implementing Model Governance for a Regulated Lender
0
regulatory findings
SHAP explainability + immutable audit log meets SR 11-7 model risk guidance.
Read case study →Ready to modernise your credit stack?
Book a 30-minute technical demo with our team. We'll walk through the underwriting pipeline, live SHAP explanations, and governance dashboard using your data or ours.
No commitment. Demo uses real synthetic data. Set up in under 5 minutes.