use matlab in solvency ii frameworks
the european union solvency ii directive specifies the amount of capital eu insurance companies must hold to reduce the risk of insolvency. it requires insurers to use quantitative methods for policy and actuarial simulation, risk projection, and economic capital forecasting, and to report results across the organization.
sometimes, solvency ii is called basel for insurers. it consists of three pillars similar to basel, including quantitative requirements (similar to the minimum capital requirement of basel iii framework), supervisory review, and disclosure requirements.
common tasks associated with a solvency ii platform include:
- scenario generation, including use of copula methods
- monte carlo simulation, including policy-by-policy simulation and nested stochastic simulation
- portfolio replication and least squares monte carlo, for on-demand balance sheet modeling
- calculation of solvency capital requirements (scr) and market consistent embedded value (mcev)
- asset-liability modeling
- parallel and gpu computing for time-efficient simulation and parameter identification
- automated reporting
for detail, see matlab®, which is commonly used as part of, or in some cases, to drive a solvency ii platform.
examples and how to
- - video
- - video
- - video
- - user story
- - video
- - third-party product
- - example
software reference
- (functions)
- : find minimum of constrained nonlinear multivariable function (function)
- : monte carlo simulation of correlated asset returns (function)
- : generalized pareto mean and variance (function)
- treebagger class (documentation)
see also: insurance, risk management, monte carlo simulation, credit risk, asset-liability modeling, basel iv, fraud analytics, , modelscape