2022 Hachemeister Prize Announcement

After a great deal of consideration, the Hachemeister Prize Task Force opted not to award the prize this year. However, the task force wanted to specifically recommend the following papers for additional reading for actuaries involved in pricing, but may be of general interest:

• “Addressing Imbalanced Insurance Data Through Zero-Inflated Poisson Regression with Boosting” by Simon C.K. Lee is a good paper that proposes a machine-learning procedure to improve predictive accuracy in regression by addressing the problem of imbalanced datasets, in which one or few classes dominate all the others.
• “Robust Estimation of Loss Models for Lognormal Insurance Payment Severity Data” by Chudamani Poudyal is a good paper that develops maximum likelihood estimator and method of trimmed moments procedures to address the common problem of dealing with truncation, censoring, and scaling when modeling insurance claims severity data.