How to accelerate AI in Banks

With the exponential rise of AI usage in Banks, many financial organizations are still struggling with building efficient Model Development Life Cycles (MDLC) and the means to expedite business value realization and return of investment (ROI). There are several contributing factors which can give rise in less than optimal MDLC, such as, lack of proper data governance and processes around it as well as lack of performant AI solutions and platforms.

In this session, you will learn how to use most essential business value accelerators (BVA) to expedite Data Science Discovery, Data Ingestion, and Model Development leading to most optimal Model Business integration. This session will provide lots of valuable and real to life strategies and executable plans to help reduce your MDLC and time to market by at least 50%

Sections will include but not limited to:

• Overview of AI Acceleration in highly regulated environments

• Effective use of tools and processes in each phase of MDLC

• Hints and Tips on building effective meta use cases with the lines of businesses, e.g. Fraud, Anti Money Laundering amongst many others

• Agile Blueprints for Machine Learning (ML) and Natural Language Processing (NLP)

• Effective Data Governance Policy and Strategy

Author(s): Ramin Mobasseri

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