Discrimination-Free Insurance Pricing

ASTIN Bulletin open access FirstView 2021 https://www.cambridge.org/core/journals/astin-bulletin-journal-of-the-iaa/article/discriminationfree-insurance-pricing/ED25C4053690E56050F437B8DF2AD117

Posted: 10 Feb 2020 Last revised: 11 Oct 2021

See all articles by Mathias Lindholm

Mathias Lindholm

Stockholm University

Ronald Richman

Old Mutual Insure; University of the Witwatersrand

Andreas Tsanakas

Bayes Business School (formerly Cass), City, University of London

Mario V. Wuthrich

RiskLab, ETH Zurich

Date Written: January 16, 2020

Abstract

A simple formula for non-discriminatory insurance pricing is introduced. This formula is based on the assumption that certain individual (discriminatory) policyholder information is not allowed to be used for insurance pricing. The suggested procedure can be summarized as follows: First, we construct a price that is based on all available information, including discriminatory information. Thereafter, we average out the effect of discriminatory information. This averaging out is done such that discriminatory information can also not be inferred from the remaining non-discriminatory one, thus, neither allowing for direct nor for indirect discrimination.

Keywords: discrimination, differentiation, insurance pricing, individual policy char- acteristics, discriminatory covariates, direct discrimination, indirect discrimination, neural networks, complex algorithmic models, causal inference, confounding

JEL Classification: G22, G18, C13, C18, C45, C51, C54

Suggested Citation

Lindholm, Mathias and Richman, Ronald and Tsanakas, Andreas and Wuthrich, Mario V., Discrimination-Free Insurance Pricing (January 16, 2020). ASTIN Bulletin open access FirstView 2021 https://www.cambridge.org/core/journals/astin-bulletin-journal-of-the-iaa/article/discriminationfree-insurance-pricing/ED25C4053690E56050F437B8DF2AD117, Available at SSRN: https://ssrn.com/abstract=3520676 or http://dx.doi.org/10.2139/ssrn.3520676

Mathias Lindholm

Stockholm University ( email )

Universitetsvägen 10
Stockholm, Stockholm SE-106 91
Sweden

Ronald Richman

Old Mutual Insure ( email )

Wanooka Place
St Andrews Road
Johannesburg, 2192
South Africa

University of the Witwatersrand ( email )

Andreas Tsanakas

Bayes Business School (formerly Cass), City, University of London ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Mario V. Wuthrich (Contact Author)

RiskLab, ETH Zurich ( email )

Department of Mathematics
Ramistrasse 101
Zurich, 8092
Switzerland

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