Solvency II and Basel III, the new standards for insurance and bank regulations, codify and unify capital, data management, and disclosure requirements for insurers and banks in order to protect companies and consumers from risk.
More specifically, with Solvency II the effect of every insurance contract capital market relation, optionally and risk source has to be modeled and measured. The goal is to ensure insurances have enough equity to cope with any forecasted risk. Considering the amount of heterogeneous assets and liabilities owned by an insurance company, algorithms such as Monte Carlo are suitable to estimate the result of different scenarios with a given accuracy and get metrics such as VaR (value at risk).
A typical process using a Monte Carlo algorithm regularly involves multiple steps:
- Defining a model for each asset, liability, economic scenarios, etc. using tools such as Quantlib, Bloomberg solution, Wall Street system, Apollo, etc.
- Create scenarios based on these models (It can easily go above 2 millions scenarios)