AI for finance, built to the audit bar.
Risk, fraud, KYC, and decisioning systems with the explainability and audit trails regulators expect.
- Pilot to production
- 0-12wk
- Fraud detection lift
- 0-50%
- Audit-ready outputs
- 0%
- Tolerance for unexplainable decisions
- 0
AI in finance is different. We treat it that way.
Models in finance must be explainable, auditable, and stable across regulatory cycles. We build them with model cards, fairness evals, and decision logs from day one. Not as an afterthought.
- Risk modeling, fraud detection, KYC, and lending decisions
- Explainability surfaces calibrated for regulator review
- Model risk management aligned to SR 11-7 and equivalents
From discovery to production.
- 01
Discover
Map the regulatory perimeter, the data lineage, and the model risk requirements before any modeling starts.
- 02
Prototype with evals
Backtest on historical data; evaluate fairness, stability, and explainability alongside accuracy.
- 03
Deploy
Production serving with full audit trail, decision logs, and override paths your control functions can use.
- 04
Operate
Continuous monitoring, periodic revalidation, and the regulator-ready documentation that goes with it.
Building an ML system that has to survive a regulator audit?
Book a 30-min consultWhat you get.
Documentation regulators have read before.
Model cards, validation reports, decision logs, and revalidation cadences. We have shipped to firms operating under SR 11-7, GDPR, FCA, and equivalents. The paper trail is part of the work, not a bolt-on.
- Model cards and validation reports written for regulator review
- Decision logs and override paths sufficient for audit
- Revalidation cadence and drift monitoring built into operations
Common questions.
Ship AI in finance, not despite the regulators.
Free 30-minute consultation with a finance specialist.
Schedule consultation