The Biggest AI Risk Is Governance You Cannot See.
Is your AI model risk management framework meeting what regulators actually require?
Model drift goes undetected. Audit trails go unmaintained. Explainability fails under scrutiny. BFSI institutions find out at examination. Not before.
Stop reacting. Start measuring.
Instantly assess AI model risk, governance gaps, and compliance readiness across leading banks, NBFCs, and insurers regulatory frameworks.
What Regulators Find That You're Missing
SR 11-7. MAS FEAT. RBI MRM. EU AI Act. The frameworks exist. Most BFSI AI programs don't meet them.
Undetected Model Drift Detection Failures
Most BFSI institutions deploy AI models without continuous model drift detection, ongoing validation, or governance monitoring required under SR 11-7 compliance frameworks. A credit model trained in 2022 is making 2026 decisions with no one watching.
Missing Algorithmic Fairness and Explainability Controls
Financial institutions increasingly face regulatory scrutiny around algorithmic fairness, explainability, and defensible AI decisions in lending and underwriting systems. A gradient boosted ensemble is not an acceptable answer to a regulator.
Manual AI Governance Creates Audit Risk
Spreadsheet based model inventories cannot support enterprise AI governance, defensible audit trails, or regulator ready AI model risk management programs. A model registry in Excel, updated quarterly by whoever remembers, is audit liability dressed as compliance.
Missing AI Audit Trails for High Risk Systems
The EU AI Act and emerging BFSI AI governance regulations require immutable AI audit trails, decision logging, and regulator ready documentation. Most institutions cannot produce them within 48 hours of a formal request.
AI Model Risk Exposure Scorecard
Answer honestly. 14 questions across 5 domains mapped to EU AI Act, SR 11-7, GDPR, HIPAA, NIST AI RMF & ISO/IEC standards.
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Contact & Company Overview
Strategy & AI Governance
Data Risk & Infrastructure
Model Transparency & Control
Monitoring, Drift & Lifecycle
Compliance & External Exposure
Email Address
Job Title
Company size
Frameworks Covered by the AI Governance Assessment
Every question in the assessment is anchored to specific regulatory requirements. Your score doubles as a pre-examination gap analysis across the frameworks that matter.
SR 11-7 Compliance
- US Banking — Federal Reserve and OCC model risk management guidance. Covers model development, validation, ongoing monitoring, and governance for US financial institutions.
- SR 11-7 compliance is the baseline for model risk management in banking.
RBI Model Risk Management
- Indian Banking — Reserve Bank of India guidelines for AI model risk management.
- Focuses on model inventory completeness, independent validation, documentation standards, and board level governance for Indian banks and NBFCs.
MAS FEAT Compliance
- APAC Banking — Monetary Authority of Singapore Fairness, Ethics, Accountability, and Transparency principles.
- Addresses explainability requirements and bias detection in financial AI models across APAC markets.
EU AI Act Compliance
- European Union — Applies to high risk AI systems in credit scoring and underwriting.
- Requires conformity assessments, immutable AI audit trails, human oversight mechanisms, and documentation retrievable within regulatory timelines.
NIST AI RMF Alignment
- Global Standard — NIST AI Risk Management Framework GOVERN, MAP, MEASURE, MANAGE functions.
- Increasingly cited as the baseline AI governance standard by US regulators and incorporated into examination expectations.
Visual Exploration and Decision Analytics.
By Samta.ai.
VEDA is Samta.ai’s enterprise AI intelligence platform built to unify fragmented financial, compliance, operational, and risk data into one trusted decision intelligence layer. By connecting core banking systems, risk engines, transaction streams, audit logs, and enterprise data platforms, VEDA enables faster risk visibility, intelligent analytics, regulatory readiness, and AI-assisted decision making across institutional operations.
Continuous Risk & Anomaly Intelligence
Detect emerging anomalies, portfolio irregularities, and operational risks early through continuous AI-powered monitoring and enterprise-wide analytics.
Credit & Liquidity Risk Visibility
Consolidate exposure, portfolio, and transaction intelligence into a unified real-time view for stronger credit and liquidity oversight.
Stress Testing & Scenario Analytics
Accelerate stress testing and scenario modeling with AI-driven simulations to evaluate financial impact and operational resilience.
Regulatory Monitoring & Compliance Readiness
Strengthen compliance readiness with centralized monitoring, policy intelligence, explainable reporting, and audit-ready governance workflows.
Designed for Regulated Financial Institutions
Built for the governance, compliance, and risk requirements of BFSI institutions operating under global regulatory frameworks.
Banks
Operationalize AI governance across lending, underwriting, and credit scoring systems.
NBFCs
Strengthen AI compliance visibility and regulator readiness across production models.
Insurance Providers
Monitor explainability and governance risks across automated decisions.
FinTech Platforms
Scale AI responsibly with enterprise governance controls built for regulation.
Know Your Exposure Before Regulators Do
8 questions. Under 2 minutes. One score that tells you exactly where your AI model risk program stands — and what to fix first.
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