Actuarial reserving techniques using aggregated triangle data are ubiquitous in the property casualty insurance industry. By instead starting with the modeling of individual claim behavior using predictive modeling techniques and a modeling framework that describes the full life cycle of a claim, there are numerous benefits including greater reliability of reserve estimates, faster recognition of underlying mix changes, and avoidance of problems in pricing due to differences in development. Component development and emergence models used in conjunction with simulation of currently outstanding claims and simulation of claims still yet to be reported form an alternative framework for generating estimates of reserve need. Algorithmic case reserves at the claim level and algorithmic IBNR estimates at the policy level, actuarially determined and designed to be unbiased, provide valuable information for downstream analyses, a bridge to the generally accepted triangle reserving paradigm, and a means for demonstration of reliability for actuarial purposes.
Author: Chris Gross – Chief Executive Officer at Gross Consulting