A Quantum-Type Approach to Non-Life Insurance Risk Modelling

Abstract

A quantum mechanics approach is proposed to model non-life insurance risks and to compute the future reserve amounts and the ruin probabilities. The claim data, historical or simulated, are treated as coming from quantum observables and analyzed with traditional machine learning tools. They can then be used to forecast the evolution of the reserves of an insurance company. The following methodology relies on the Dirac matrix formalism and the Feynman path-integral method.

Keywords

• non-life insurance
• reserve process
• ruin probability
• quantum mechanics
• Hamiltonian
• path-integral
• econophysics
• learning techniques
• data analysis