Machine Learning in General Insurance Reserving – Method Comparison and Interpretation (Part 2)

The second session in a series of two talks on the topic of applying machine learning (ML) techniques in general insurance reserving. This talk builds on the first session focusing on validation, feature engineering, interpreting ML results and comparing performance to traditional reserving techniques for different claims characteristics. Attendance at the first session would be beneficial to attendees of this talk, but it is not essential. This talk was previously presented at GIRO 2021.

You can find Part 1 here.