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

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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.

This report 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

Download your copy of the report now >>

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While you’re here…

Check out our upcoming event!

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MoneyLIVE Autumn Festival

Virtual Episodes across October & November

Broadcasting throughout October and November, our 5 virtual episodes see leading experts take to the screen and dive into the hottest topics in banking and payments, including agility and resilience, digital identities, purpose-led banking, social platforms and the future of FinTech.

Speakers include:

Matt Hammerstein, Chief Executive Officer, Barclays UK
Chris Pitt, Chief Executive Officer, First Direct
Tracey Davidson, Deputy Chief Executive Officer, Handelsbanken UK
Tom Wolfenden, Head of Retail Banking, HSBC

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