Predicting Client Profitability with Automated Machine Learning

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Presented by DataRobot

DataRobot is the leader in enterprise AI, delivering trusted AI technology and ROI enablement services to global enterprises. DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models.

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One of the biggest challenges banks face is identifying and successfully marketing to the most profitable customers. To stay competitive with tech-savvy fintechs, banks need to identify customers whose needs align with their offerings and avoid wasting effort and marketing budget on customers who aren’t likely to benefit from – or purchase – their products and services.

In this on-demand webinar, DataRobot’s Director of Banking H.P. Bunaes walks through the process of building a client profitability model with DataRobot’s automated machine learning platform and using it to improve profitability, client prospecting, and marketing ROI.

In this sesion H.P.:

  • Shows how to develop and test a client profitability predictor model with DataRobot using real data
  • Benchmarks profit vs. risk-averse strategies, compares the results, and proposes a high-profit strategy using the DataRobot model
  • Describes insights gained from client profitability predictors to inform prospecting and target marketing
  • Discusses benefits, use cases, and downside risks for client profitability models for credit card, wealth management, and auto lending lines of business
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