A Simulation of the Insurance Industry: The Problem of Risk Model Homogeneity

We develop an agent-based simulation of the catastrophe insurance and
reinsurance industry and use it to study the problem of risk model homogeneity.
The model simulates the balance sheets of insurance firms, who collect premiums
from clients in return for ensuring them against intermittent, heavy-tailed
risks. Firms manage their capital and pay dividends to their investors, and use
either reinsurance contracts or cat bonds to hedge their tail risk. The model
generates plausible time series of profits and losses and recovers stylized
facts, such as the insurance cycle and the emergence of asymmetric, long tailed
firm size distributions. We use the model to investigate the problem of risk
model homogeneity. Under Solvency II, insurance companies are required to use
only certified risk models. This has led to a situation in which only a few
firms provide risk models, creating a systemic fragility to the errors in these
models. We demonstrate that using too few models increases the risk of
nonpayment and default while lowering profits for the industry as a whole. The
presence of the reinsurance industry ameliorates the problem but does not
remove it. Our results suggest that it would be valuable for regulators to
incentivize model diversity. The framework we develop here provides a first
step toward a simulation model of the insurance industry for testing policies
and strategies for better capital management.