Isotonic recalibration under a low signal-to-noise ratio

Mario V. Wüthrich and Johanna Ziegel

Scandinavian Actuarial Journal, 2024, vol. 2024, issue 3, 279-299

Abstract: Insurance pricing systems should fulfill the auto-calibration property to ensure that there is no systematic cross-financing between different price cohorts. Often, regression models are not auto-calibrated. We propose to apply isotonic recalibration to a given regression model to restore auto-calibration. Our main result proves that under a low signal-to-noise ratio, this isotonic recalibration step leads to an explainable pricing system because the resulting isotonically recalibrated regression function has a low complexity.

Date: 2024
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DOI: 10.1080/03461238.2023.2246743

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