Predicting Client Profitability with Automated Machine Learning

On Demand

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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