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arXiv · 2109.01570

Quantum support vector regression for disability insurance

Boualem Djehiche·Björn Löfdahl
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Abstract

We propose a hybrid classical-quantum approach for modeling transition probabilities in health and disability insurance. The modeling of logistic disability inception probabilities is formulated as a support vector regression problem. Using a quantum feature map, the data is mapped to quantum states belonging to a quantum feature space, where the associated kernel is determined by the inner product between the quantum states. This quantum kernel can be efficiently estimated on a quantum computer. We conduct experiments on the IBM Yorktown quantum computer, fitting the model to disability inception data from a Swedish insurance company.

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Boualem Djehiche, Björn Löfdahl. 2021-09-03. Quantum support vector regression for disability insurance. https://arxiv.org/abs/2109.01570

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