Market-based insurance ratemaking: application to pet insurance

TL;DR

This paper presents a market-based method for pricing pet insurance policies using observed market data, especially useful when historical data is unavailable, validated through synthetic and real datasets.

Contribution

Introduces an iterative two-step market-based pricing method for new insurance markets, with an R package implementation for practical use.

Findings

Validated on synthetic data showing accurate risk characterization.

Successfully applied to real pet insurance rate data.

Provides a practical tool for emerging insurance markets.

Abstract

This paper introduces a method for pricing insurance policies using market data. The approach is designed for scenarios in which the insurance company seeks to enter a new market, in our case: pet insurance, lacking historical data. The methodology involves an iterative two-step process. First, a suitable parameter is proposed to characterize the underlying risk. Second, the resulting pure premium is linked to the observed commercial premium using an isotonic regression model. To validate the method, comprehensive testing is conducted on synthetic data, followed by its application to a dataset of actual pet insurance rates. To facilitate practical implementation, we have developed an R package called IsoPriceR. By addressing the challenge of pricing insurance policies in the absence of historical data, this method helps enhance pricing strategies in emerging markets.