Claims processing and costs under capacity constraints

TL;DR

This paper analyzes insurance claims processing delays caused by capacity constraints, proposing an optimal capacity selection method to minimize costs, supported by theoretical insights and a large-scale numerical study.

Contribution

It introduces a novel approach to optimize processing capacity in insurance claims handling considering delays and costs, combining theory with practical numerical validation.

Findings

Optimal capacity levels reduce claims costs significantly.

Delay-adjusted costs are crucial for capacity planning.

Numerical results demonstrate practical effectiveness of the proposed method.

Abstract

Random delays between the occurrence of accident events and the corresponding reporting times of insurance claims is a standard feature of insurance data. The time lag between the reporting and the processing of a claim depends on whether the claim can be processed without delay as it arrives or whether it remains unprocessed for some time because of temporarily insufficient processing capacity that is shared between all incoming claims. We aim to explain and analyze the nature of processing delays and build-up of backlogs. We show how to select processing capacity optimally in order to minimize claims costs, taking delay-adjusted costs and fixed costs for claims settlement capacity into account. Theoretical results are combined with a large-scale numerical study that demonstrates practical usefulness of our proposal.