Potential Applications of Quantum Computing for the Insurance Industry

TL;DR

This paper explores how quantum computing, particularly amplitude estimation, could revolutionize insurance contract valuation by significantly speeding up complex Monte Carlo simulations, with practical circuit implementations tested on real hardware.

Contribution

It demonstrates the potential application of quantum algorithms like Amplitude Estimation to insurance valuation problems, including circuit design and hardware testing.

Findings

Quantum algorithms can potentially accelerate insurance valuation tasks.

Quantum circuits for insurance payoffs are feasible on current hardware.

Amplitude Estimation shows promise for practical insurance computations.

Abstract

This paper is the documentation of a pre-study performed by AXA Konzern AG in collaboration with Fraunhofer ITWM to assess the relevance of quantum computing for the insurance industry. Beside a general overview of the status quo of quantum computing technologies, we investigate its applicability for the valuation of insurance contracts as a concrete use case. This valuation is a computationally intensive problem because the lack of closed pricing formulas requires the use of Monte Carlo methods. Therefore current technical capabilities force insurers to apply approximation methods for many subsequent tasks like economic capital calculation or optimization of strategic asset allocations. The business-criticality of these tasks combined with the existence of a quantum algorithm called Amplitude Estimation which promises a quadratic speed-up of Monte Carlo simulation makes this use case obvious. We provide a detailed explanation of Amplitude Estimation and present two quantum circuits which describe insurance-related payoff features in a quantum circuit model. An exemplary circuit that encodes dynamic lapse is evaluated both on a simulator and on real quantum hardware.