Conformal prediction for frequency-severity modeling

The statistical modeling of insurance claims is a crucial task of the property and casualty insurance industry. An essential ingredient in this modeling process is the two-stage approach, encompassing a frequency model and a severity model. At the first stage, a frequency model predicts the number of claims, while, at the second stage, a severity model predicts the average financial impact or size of a claim, given that it has occurred. Together, these two models map relevant predictors such as the policyholder's age, geographical location, and claim history, to the response variables describing the frequency and severity of the claims. This classic approach, known as the frequency-severity model, has been instrumental in the process of risk categorization, premium calculation, and, in a broader context, risk quantification of business portfolios for specific industry segments [1, 2].