Mean-field approximations in insurance
By: Philipp C. Hornung
Potential Business Impact:
Simplifies insurance calculations for large groups.
The calculation of the insurance liabilities of a cohort of dependent individuals in general requires the solution of a high-dimensional system of coupled linear forward integro-differential equations, which is infeasible for a larger cohort. However, by using a mean-field approximation, the high dimensional system of linear forward equations can be replaced by a low-dimensional system of non-linear forward integro-differential equations. We show that, subject to certain regularity conditions, the insurance liability viewed as a (conditional) expectation of a functional of an underlying jump process converges to its mean-field approximation, as the number of individuals in the cohort goes to infinity. Examples from both life- and non-life insurance illuminate the practical importance of mean-field approximations.
Similar Papers
Disability insurance with collective health claims: A mean-field approach
Risk Management
Helps insurance companies predict group health costs better.
Mean-Field Generalisation Bounds for Learning Controls in Stochastic Environments
Optimization and Control
Teaches computers to make smart choices from data.
Mean-Field Price Formation on Trees: with Multi-Population and Non-Rational Agents
Mathematical Finance
Predicts stock prices with complex investor choices.