Background:

The increasing adoption of advanced analytics, Artificial Intelligence (AI), Machine Learning (ML), automated decision systems and quantitative models across the financial sector has significantly transformed the manner in which Banks, NBFCs and Financial Institutions assess risks, price products, manage capital, detect fraud and support strategic decision-making. As financial institutions increasingly rely on complex models for critical business and regulatory functions, the potential risks arising from model errors, incorrect assumptions, data limitations, misuse, inadequate governance and overdependence on third-party/vendor models have emerged as key supervisory concerns globally.

Model Risk can lead to inaccurate business decisions, financial losses, reputational damage, regulatory noncompliance and systemic vulnerabilities. The increasing use of AI/ML-driven models and black-box algorithms has further amplified concerns relating to transparency, explain ability, validation and governance. Recognising these emerging challenges, regulators including the Reserve Bank of India have been emphasising stronger governance frameworks, independent validation mechanisms, robust controls and enhanced board oversight over model risk management practices.

Objective:

Against this backdrop, CAFRAL is organising this one-day Virtual Program on Model Risk to sensitise participants to the evolving model risk landscape and provide practical insights into governance frameworks, validation practices, regulatory expectations and emerging challenges associated with AI/ML-led risk modelling.

Program Highlights:

• A Regulatory Perspective on Model Risk Management
• Model Risk Management: Governance and Controls
• Fintech AI & ML led Risk Modelling
• Model Validation & Monitoring
• Vendor and Third-Party Products