Big Data and Anti-Discrimination – Lessons Learned from Unisex-Tariffs

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Big Data and Machine Learning increase the number of risk factors pricing is based on in insurance, both life and non-life. Since the Court of Justice of the European Union (CJEU) ruling on gender equality in 2011, all tariffs must be priced equally for men and women. Nevertheless, gender is an important and relevant risk factor for many insurance policies. Therefore, the distribution of men and women within the risk classes affects the final gender-equal unisex rates. Unfortunately, the percentage of men and women differs hugely between risk classes. There may even be strong correlations between gender and risk classes. To avoid gender discrimination, a new but simple approach to calculate unisex rates will be presented so that the distribution of men and women in different risk classes does not affect pricing anymore. As all new machine learning and AI-pricing have to comply with EU-Regulation, this may be a solution to meet the regulation and could help minimizing customer prejudice. This may be an example to avoid discrimination even for other risk factors such as nationality.

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