An Initial Approach to Optimizing Insurance Quotes with Quantum Computing

The aim of the paper a case study to demonstrate what is currently possible with quantum computing. It is about the problem of multidimensional optimization of insurance quotes to enhance the conversion rate with a given risk appetite and profit expectation.

In the German insurance market insurance quotes are already optimized independently in many dimensions. E.g., it is quite common to optimize insurance prices based on customer’s data. Optimization of the presentation and “next best offer” are also occasionally seen. It is less common to optimize the product version offered based on customer’s data. A quantitative optimization of the price based on the insurers’ portfolios is not yet used in private insurance, because the complexity of calculations makes this analysis too time consuming.

The paper is motivated by the problem that a multidimensional and dependently optimization of all problems together is currently still too time consuming to be used for a just-in-time calculation at the point of sales. The quantum computer technology offers an approach to solve these problems in significant less time.

In this paper, we show an approach to solve the complications calculating a multidimensional optimization for the price, the specific product version and product presentation based on customer data and the insurers existing portfolio. The paper presents a representation of the problem as an NP-complete problem like SAT, which is than transformed to an Ising and QUBO representation. This can be used as a suitable input for QBSolv, the Solver provide by DWave as an interface to the quantum annealer.

As a result, the paper compares the quantum annealer calculation and the classical computing in aspects of performance and handling. It gives an outlook about the possibilities given with further developments in quantum computing and how insurance companies can use these.

Overall, the paper presents a practitioners’ case study for quantum computing, especially quantum annealing, and ai applications to optimize the insurance quote process.