Risk assessment for life insurance
Life insurance has the particularity that a total balance sheet approach over a multiple period time horizon is indispensable to grasp the inherent risk captured in sometimes very complicated products.
Whether your company uses a stochastic internal model or a non-stochastic standard formula for solvency II, the Risk Platform that will manage the modeling has to fulfil a number of very challenging requirements.
These requirements cover the input data and parameters, the actual model and the output and reports.
Data and Parameters
Risk models need a lot of input. Sufficient granular policy data that reflects the current state of both the assets and liability portfolio have to be gathered from different sources. The data has to be cleansed and reconciliated with accounting data. The periodic process to gather this data has to be carefully monitored.
Responsibilities and roles have to be set. Rules that translate efficiently the specificities of the products, profit sharing and assets managing based on the predicted results of the company and the different branches have to be produced. Materiality is a key concept in doing so. Parameters that are subject to frequent recalibration like prospective death tables and mortality adjustments have to be produced and stored. Periodically changing economic parameters have to be gathered from external sources. This input has to be produced in an atomised, auditable and traceable way.
Too often data gathering and storing are totally apart from the modeling. This means a serious risk for errors and a substantial loss in control over the total process. Only a fully integrated platform can give the quality that is required for solvency and ORSA.
Once the data gathered, a modular model must predict the cash flows. The best way to construct such a model is to start with a one-year period, in which the interaction between assets and liabilities is fully designed and tested. Once this done a loop should produce the multi-period results.
Although classic tools seem to focus persistently on predefined peaces of “generally useable product models and management rules” the inadequacy of such codes becomes more and more apparent. Actuaries experience the need for extensive amounts of own code to reflect the true nature of the company and it’s products.
The black box nature of these predefined codes is not only the cause of much uncertainty for the developers of models, it is also not in line with the demands of solvency II that asks for a full understanding of the model by the risk manager. If tailor made programming is needed, a tool that combines the flexibility of excel with the programming force of higher programming languages and the demands for auditability and traceability is indispensable.
Of course the output of the model should at least be the standard output needed for solvency. But a model should produce far more then that. Don’t bother to make a sophisticated model if it will serve the soul purpose of producing list with figures that will end up in a closet somewhere. The model should provide a clear insight in the insurance and financial risk for your company.
An interactive reporting tool based on an organized data warehouse of all the different results, best estimates and shocks is the only way to allow state of the art ORSA and sound decision-making.
The OOliba approach
At OOliba, we are proud to integrate three levels: actuarial design level, ICT integration level and management decision model.
The OOliba ERM Platform offers you unrivaled integration capabilities, unifying life, non-life and health risk management techniques.