Enabling the AI-Driven Enterprise

Opening the “Black Box”: The Path to Deployment of AI Models in Banking

Opening the “Black Box”: The Path to Deployment of AI Models in Banking

Recent technological advancements have accelerated the integration of AI and machine learning models into more and more banking processes. However, model risk must be effectively managed. If left unchecked, the consequences of model risk can be severe.  AI and machine learning models require constant monitoring and effective validation – this is not only a regulatory requirement but also sound business practice.

This white paper presents the cornerstones of effective modern model risk management in the age of AI and machine learning.

It provides:

  • An overview of AI and machine learning in banking
  • A summary of the regulatory background and the machine learning model lifecycle
  • An overview of the challenges and emerging best practices for the validation of models in an ever-changing world of AI and machine learning

Authors

Seph Mard
Seph Mard
Head of Model Validation, DataRobot
Peter Simon
Peter Simon
Senior Data Scientist, DataRobot
Ram Ananth
Ram Ananth
Head of Quantitative Practice, Advantage Reply