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Why insurance regulators need to require sensitivity settings of internal models for their approval

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  • Borgonovo, Emanuele
  • Clemente, Gian Paolo
  • Rabitti, Giovanni

Abstract

According to the Solvency II directive, insurers can use internal models for solvency assessment, but regulators must approve these models. Sensitivity analysis is a crucial part of the approval process. However, the directive lacks clarity on the required sensitivity analysis. Various techniques exist in literature to assess the impact of model assumptions on output, each revealing different aspects of model behaviour. In this letter, we suggest a minimum standard for regulators to ensure model quality. We propose complementary sensitivity settings for internal model development, governance, and approval. Implementing these settings enhances the explainability of approved models and their reliability.

Suggested Citation

  • Borgonovo, Emanuele & Clemente, Gian Paolo & Rabitti, Giovanni, 2024. "Why insurance regulators need to require sensitivity settings of internal models for their approval," Finance Research Letters, Elsevier, vol. 60(C).
    • Handle: RePEc:eee:finlet:v:60:y:2024:i:c:s154461232301231x
    DOI: 10.1016/j.frl.2023.104859
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    References listed on IDEAS

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    1. Dacorogna, Michel M, 2017. "Approaches and Techniques to Validate Internal Model Results," MPRA Paper 79632, University Library of Munich, Germany.
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    More about this item

    Keywords

    Model governance; Explainability; Uncertainty and Sensitivity settings;
    All these keywords.

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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