Forge Underwrite — Counterfactual Credit Decisioning
Causal credit scoring that answers interventional questions like 'What would happen to default rates if we adjust limits for Segment X?' — using causal inference for heterogeneous treatment effects.
Coming Q4 2026
In active development
Key Capabilities
Causal discovery learns DAG from historical portfolio data including income, utilization, and default patterns
Counterfactual estimation for per-segment treatment effects of credit limit changes
Debiased scoring that removes causal paths from protected attributes to credit decisions
AI-generated adverse action notices citing causal factors in plain, regulator-ready language
Get Early Access
Forge Underwrite is launching Q4 2026. Join the waitlist to be among the first to experience it.
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