Case Study: Assets Under Management predicts customer churn with Kortical AI

Assets Under Management - Customer Case Study

Assets Under Management, a finance company, needed a better way to predict customer churn and cash outflows in a rapidly changing market. They worked with Kortical using its AI/AutoML platform to tackle the challenge of identifying which clients were likely to move assets out months in advance.

Kortical joined and preprocessed multiple data sources, then built and iterated over 10,000+ machine learning models to create a time-series churn prediction solution with explainable outputs. The result was the ability to predict 57% of customer churn by targeting less than 2% of the customer base, helping Assets Under Management identify a large portion of funds leaving the business and quickly produce actionable customer lists for sales teams.