With the emergence of Solvency II in Europe and upcoming Solvency-II-style supervision in other parts of the world, insurance companies find themselves in need of more powerful analytical tools than ever before. An example that illustrates this need is the modelling requirement dictated by Solvency II. For the more complex business, like traditional with-profits products, this essentially requires life insurance companies to apply a so-called nested stochastic approach to calculate the Solvency Capital Requirement (SCR). For most members of the industry, these types of calculations are complex and computer-intensive, which means that actuarial and risk departments are finding it extremely challenging to obtain results with the required precision and within the required timelines.
In recent years, a number of different proxy approaches were introduced to make SCR calculations more manageable. Clearly a reliable proxy approach involving relatively little effort is what companies are aiming for. However, enhanced operational and governance as well as regulatory requirements have recently put more emphasis on documentation (i.e., to describe each step of the entire calibration process in an auditable way) and validation (to demonstrate thoroughly the adequacy of a proxy), and actuarial and risk departments are challenged to ensure overall compliance with those.
In the last couple of years, we have observed several of these approaches being applied by various insurers, and in quite a few cases these approaches turned out not to be robust in an insurance context and were applied without sufficient accuracy. This led, for example, to SCR results which fluctuated over time for no apparent reason—a situation which is certainly not acceptable. Regulators have noticed these issues and a general problem—how to ensure that the proxy approach applied is really adequate.