Managing Model Risk, Bias & Regulatory Expectations in AI-Driven Lending
At Bharat Fintech Summit, industry leaders discuss how financial institutions can responsibly scale AI-driven lending while staying ahead of model risk, bias concerns, and tightening regulatory scrutiny.
- Pankaj RathiÂ
- Shashwat KumarÂ
- Majid AsadullahÂ
- Sushant Roy
- Shashank ShekharÂ
The session explores how model risk management must evolve for machine-learning–driven credit systems. From designing bias-aware models that expand financial access to turning responsible AI into a growth enabler, the panel examines governance frameworks, validation standards, and lifecycle management needed for regulator-ready AI in lending.
- Key Takeaways:
- Reimagining model risk management for ML lending
- Bias detection & responsible AI frameworks
- Governance, validation & auditability of AI models
- Preparing for tighter regulatory oversight
- Building accountable, adaptive credit systems
