Research Results from Eotvos Lorand University Update Understanding of Risk Management (The Quality of Reserve Risk Calculation Models under Solvency II and IFRS 17): Insurance – Risk Management

2022 NOV 30 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Fresh data on risk management are presented in a new report. According to news originating from Budapest, Hungary, by NewsRx correspondents, research stated, “We analyse four stochastic claims reserving methods in terms of their capability to estimate reserve risk and how successful they are at predicting distributions and VaRs of claim developments in particular.”

Financial supporters for this research include Ministry of Innovation And Technology of Hungary.

The news editors obtained a quote from the research from Eotvos Lorand University: “Both actual data and hypothetical claim triangles support our results. The appropriateness of the Solvency II risk margin on a one-year horizon and of the IFRS 17 risk adjustment in the long run largely vary by the chosen risk model. Despite the fact that IFRS 17 does not uniquely prescribe the metric for risk adjustment, we expect that VaR will be widely applied by insurance firms. Overall, actual data suggest that VaRs are predominantly underestimated by the models.”

According to the news editors, the research concluded: “Nevertheless, the 99.5 % -VaRs under Solvency II are mostly sufficient on a 10-year-horizon to cover liabilities.”

For more information on this research see: The Quality of Reserve Risk Calculation Models under Solvency II and IFRS 17. Risks, 2022,10(204):204. (Risks - http://www.mdpi.com/journal/risks). The publisher for Risks is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/risks10110204.

Our news journalists report that additional information may be obtained by contacting N. Miklos Arato, Department of Probability Theory and Statistics, Eotvos Lorand University, Pazmany Peter Setany 1, C, 1117 Budapest, Hungary. Additional authors for this research include Laszlo Martinek.

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