In today’s complicated financial landscape accurate models are a necessity for banks to remain competitive, but developing accurate models is challenging. Models are inherently complex — and if developed poorly can do more harm than good.
In this panel discussion, we cover how banks can use Machine Learning to gain a competitive advantage, while quickly aligning their business operation to regulatory requirements. We discuss current trends and expectations for model risk management regulatory compliance, and how industry-leading financial institutions are leveraging Machine Learning to provide a much stronger framework for model development and validation than traditional manual efforts.
- How Automated Machine Learning enhances compliance to model risk management regulation (FIL 22-2017, SR 11-7, OCC 2001-12)
- Key terms and functions required by new regulation
- How Machine Learning reduces model risk, while ensuring the implementation of cutting edge machine learning models