Explainable AI for paid-up risk management in life insurance products

Lluís Bermúdez, David Anaya and Jaume Belles-Sampera

Finance Research Letters, 2023, vol. 57, issue C

Abstract: Explainable artificial intelligence (xAI) provides a better understanding of the decision-making processes and results generated by black-box machine learning (ML) models. Here, we outline several xAI techniques in order to equip risk managers with more explainable ML methods. We illustrate this by describing an application for the more effective management of paid-up risk in insurance savings products. We draw on a database of real universal life policies to fit an initial logistic regression model and several tree-based models. We then use different xAI techniques, including a novel approach that leverages a Kohonen network of Shapley values, to offer valuable perspectives on tree-based models to the end-user. Based on these findings, we show how non-trivial ideas can emerge to improve paid-up risk management.

Keywords: Machine learning; Shapley values; Kohonen networks; Risk analysis (search for similar items in EconPapers)
JEL-codes: C10 C35 G22 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:57:y:2023:i:c:s1544612323006141

DOI: 10.1016/j.frl.2023.104242

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