Price Optimisation for New Business

TL;DR

This paper develops algorithms for price optimization in non-life insurance, considering market competition and customer acceptance probabilities, with applications to motor insurance data.

Contribution

It introduces new optimization models and algorithms for pricing strategies in competitive insurance markets, addressing both continuous and discrete scenarios.

Findings

Algorithms effectively optimize prices considering market competition.

Application to motor insurance demonstrates practical utility.

Models improve conversion rates for new business.

Abstract

This contribution is concerned with price optimisation of the new business for a non-life product. Due to high competition in the insurance market, non-life insurers are interested in increasing their conversion rates on new business based on some profit level. In this respect, we consider the competition in the market to model the probability of accepting an offer for a specific customer. We study two optimisation problems relevant for the insurer and present some algorithmic solutions for both continuous and discrete case. Finally, we provide some applications to a motor insurance dataset.