Solvency II’s Standard Formula provides inadequate credit for some reinsurance
Reinsurance broker Aon Benfield has recommended that reinsurance buyers use a partial internal model to boost the value of reinsurance under the Solvency II framework, which is scheduled to come into force in 2012.
A new study by Aon Benfield, ‘Solvency II for Reinsurance Managers’, found that a partial internal model, can increase the benefit of reinsurance within Solvency II’s non-life capital requirement by 25% and even more in certain cases.
The study argues that a partial internal model is crucial to obtain a more accurate picture of premium risk. It asserts that Solvency II’s Standard Formula for determining solvency capital requirements does not provide adequate credit for non-proportional reinsurance on casualty lines. In particular, the study said, the existing proposal in Solvency II’s fifth quantitative impact study (QIS 5) penalises larger insurers by providing no noticeable benefit from purchasing non-proportional reinsurance while an internal model would provide that advantage.
“In a Solvency II world, reinsurance is the most obvious place to start with an internal model,” said Marc Beckers, head of EMEA analytics at Aon Benfield, in a statement. “Under the current proposal, the benefit of an internal model compared to the Standard Formula is largest for reinsurance, particularly for non-proportional property cat and casualty reinsurance. Rather than looking to raise capital to fund any shortfall in net assets, companies may consider reinsurance options to reduce their capital requirement.”
He added: “Furthermore, volatility of earnings will increase as a result of fair value accounting (Solvency II and IFRS Phase II) and reinsurance is the cheapest and most efficient way to reduce this volatility.”
The study also points out that catastrophe risk will become a main driver for capital with the benchmark to withstand a 1 in 200 year event. It adds, however, that the methodology for the standardised scenarios for catastrophe modelling overlooks key data features such as location granularity, occupancy (residential versus commercial versus industrial), limits or deductibles.