Completed Date: September 2015
Benedetti, Davide and Biffis, Enrico
Commercial Insurance business amounts to 600 billion USD. Yet, there is limited literature on the topic of commercial insurance in both academia and the industry. As opposed to natural hazards, for which studies based on catastrophe models are available, Large Commercial Risk (LCR) losses generated by human error, machine failure, and other non-natural hazards (e.g., fire and explosion) are poorly understood, and difficult to model, due to the complex nonlinear relation between hazard events and realized losses. This poses modelling challenges, especially due to the paucity of data available for model estimation and validation, and to complex nonlinearities in the relation between hazard events and realized losses, as in some cases small events may precipitate major disasters.
Despite the relevance of commercial lines for the global P&C business and the corporate sector, limited public information is available on their risk characteristics, in particular about extreme loss realizations, which make up a large proportion of the total claims value. There is therefore the tendency for underwriters to apply a considerable degree of judgment in pricing decisions, often giving too much weight to the value of reported claims, which may not adequately reflect the risk potential of the business and exacerbate price volatility in response to claims occurrence.
The Large Commercial Risks (LCR) project is in collaboration with Imperial College London Business School and aims at the following:
(a) To provide a dataset of LCR, for the Asia-Pacific Region (APAC) region.
(b) To provide a modelling framework for LCR in APAC.
(c) To provide pricing implications and comparisons between the APAC region and other parts of the world, in particular North America and Europe. A comparison of pricing and reserving approaches to LCRs will be facilitated by a benchmarking exercise carried out at London market level, based on anonymized loss curves and rating factors currently developed by the Imperial College Business School.
IRFRC Large Commercial Risks (LCR) Dataset
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- Benedetti, D., Biffis, E., and A. Milidonis (2015). Large Commercial Exposures and Tail Risk: Evidence from the Asia-Pacific P&C Insurance Market, Working paper