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Detecting financial crimes, predicting merchant dollar volume, anticipating adoption rates, and smart pricing ops are all popular use cases driving customer satisfaction and safer banking transactions. For major banks, building AI/ ML models for these use cases has had a transformative impact on account holder and merchant satisfaction.

As well, AI/ ML models deliver value in production, not as experiments in the data science lab.

In this 60-minute webinar, Evolutio and DataRobot experts describe how organizations are enabling AI-Driven Banking in the real world through four essential use cases, and they'll touch on the organizational change needed to get models working for the business.

Evolutio routinely works with major global banks and FinTech organizations that provide enterprise services to the banking world, and DataRobot is proud to work with seven of the top ten banks in the United States.

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[Agenda] Four Banking AI Use Cases - Getting ML Models to Production

TOTAL: 60 minutes

[10min] State of the Industry with Dennis Panos (Global Head of AI Strategy at DataRobot; formerly Bank of America; has a Master’s in Financial Engineering)

[30min] Four Banking Use Cases in the following areas:

• Fraud: detecting financial crimes
• Merchant Behavior: predicting merchant dollar volume
• Account Holder Behavior: smart cross-sell to capture 20%+ of a customer’s wallet
• Churn: anticipating adoption rates and better pricing ops for retention

[20min] Get AI/ ML Models to Production - Bridge IT Ops & Data Science with Scott Munson of Evolutio