Expert analysis on AI compliance in financial services — SR 11-7 guidance, ECOA requirements, fair lending risk, and model governance for banks and fintechs.
Agentic AI in financial services needs more than post-hoc monitoring. The XeroML Governance Gateway adds inference-time policy enforcement, pre-action controls, self-healing remediation, and regulator-ready audit evidence.
A practical guide to applying SR 11-7 model risk management requirements to LLM-based AI agents in lending, fraud detection, and risk management at US financial institutions.
How AI lending agents must generate ECOA-compliant adverse action notices. Covers Regulation B requirements, specific reason codes, and the compliance risks of unexplainable AI decisions.
How AI underwriting models create fair lending risk through disparate impact, proxy discrimination, and unexplainable decisions. A practical guide for compliance officers at US financial institutions.
General-purpose observability tools track uptime and model performance — but they cannot produce audit trails, adverse action notices, or jurisdiction-aware compliance reports that regulators demand.
Breaking down the true cost of compliance failures in financial services — fines, remediation, reputational damage, and consent orders. Why AI governance is no longer optional.