Affiliations: Dublin Research Laboratory, IBM Research, Mulhuddart, Dublin, Ireland | Department of Management Science and Engineering, Stanford University, Stanford, CA, USA
Note: [] Corresponding author: Léa A. Deleris, Dublin Research Laboratory, IBM Research, Mulhuddart, Dublin 15, Ireland. E-mail: lea.deleris@ie.ibm.com.
Abstract: Engineering risk analysis, traditionally applied to engineering systems, relies on the decomposition of the system under study into subsystems and of the scenarios affecting it into basic events. The same principles are applied to the study of insolvency. In particular, we introduce a model designed to estimate insolvency risk for property and casualty insurance firms. Specifically, our approach relies on a set of models, which together describe how an insurance firm operates. Beyond firm-specific estimation of insolvency risk, our objective is to gain insights into the drivers behind insolvency and to compare those with industry wisdom and historical data. One of our findings suggests that the current practice of adapting pricing to market conditions (soft or hard markets) may in fact be sensible in terms of insolvency risk. Another finding shows that while small companies are associated with higher insolvency risk, the effect of size is noticeable either for very small firms or for firms who do not adjust their sales level to their surplus value.
Keywords: Insolvency risk, simulation, dynamic financial analysis, engineering risk analysis, property and casualty industry
