Financial Client Churn Detection Using Computer Vision

Explore a 42-minute conference talk from the Toronto Machine Learning Series (TMLS) on financial client churn detection using computer vision. Discover how historical data can be leveraged to predict client retention in wealth management firms. Learn about an innovative approach that converts client information into images and applies deep neural networks for churn prediction. Gain insights into the methodology's performance compared to traditional methods like LightGBM, and understand how increasing dataset size can enhance prediction accuracy. Delve into the speaker's expertise as a Senior Data Scientist at PureFacts Financial Solutions to uncover the potential of this novel approach in addressing one of the biggest challenges faced by wealth management firms.