Developed by Guy Carpenter and Arium, Ltd., Casualty Cat facilitates the study of single- and multi-peril casualty catastrophe risks in an insurer’s broader risk management plan. Through a rigorous analysis of inter-industry trading and supply chain data, carriers can assess key vulnerabilities, providing a foundation for risk transfer planning and execution.
The foundation of casualty catastrophe modeling — as with any other type of catastrophe modeling — is data. A carrier must have access to relevant and reliable information to use in the modeling process. And prudent Enterprise Risk Management (ERM) practices suggest that firms move beyond the basic requirements and advance their knowledge of risks that may not have been previously captured. In the past, the data for casualty catastrophe scenarios was either unavailable or simply not requested by underwriters. The maturation of this space, however, has led to improvements relative to both accessibility and use. Beyond exposures and limits, (re)insurers can obtain rigorous policy level data on the industries exposed to various liability claims. This is required for assessing vulnerabilities to both the classic and systemic elements of casualty catastrophes. High-quality data and the systems that capture it (along with corresponding industry classifications) have improved substantially for in-force casualty portfolios. Once sourced, improved casualty data can be applied to specific scenarios to identify future potential accumulations.
In order to address the interconnected nature of casualty catastrophes, Casualty Cat measures risk and impact by proximity to cause. Based on the spread of an event’s implications across industry and coverage lines, a risk accumulation profile is developed, showing a portfolio’s exposures and providing a starting point for risk mitigation planning.
Casualty Cat uses techniques grounded in network theory and measures the inter-industry links and connectivity between polices. The strength of each relevant link, the degree of connectivity, and directional flows indicate the likelihood of catastrophic casualty loss. The modeling and analysis of each risk’s industry classifications or line of business vulnerabilities to various systemic and classic propensity factors helps (re)insurers identify the classes and lines with the greatest catastrophic clash potential. By analyzing a casualty portfolio’s clash concentration at different industry classification levels and weighing multiple sources of clash intensity, a (re)insurer can begin to develop a systematic approach to identifying which areas in a portfolio call for additional probing. The analysis may unearth and identify unpredictable “black swans,” events with no discernable precedent, as well as locate and provide insight into a portfolio’s more predictable catastrophic “white swan” casualty vulnerabilities.
Heat Maps Make Exposure Visible
Consider, for example, an insurer covering a wide range of casualty lines, such as directors and officers (D&O), errors and omissions (E&O), and Third-Party Liability (TPL). The carrier writes a sizable book of professional risks (i.e., NAIC 54) and also specializes in insuring clients in the construction industry (i.e., NAIC 23). Using the Casualty Cat-generated heat maps (below), one can track line of business (vertical axis) and industry (horizontal axis) implications of a particular scenario.
Casualty Cat’s portfolio management analysis indicates that having risk concentrations in these areas increases a (re)insurer’s total catastrophe clash exposure (as depicted in the heat map below in red, orange and yellow). Its total clash intensity, however, results from varying degrees of underlying single source company (i.e., “classic Clash”) risks, as well as exposure to multi-company (”systemic clash”) events - depending on the industry. The carrier currently manages these exposures by applying lower maximum limits on professional and construction industry sectors that are particularly disconcerting.
This hypothetical casualty writer’s E&O for Professional, Scientific & Technical Services (i.e., NAIC 54) shows the greatest overall exposure to casualty catastrophes, as one may expect. As depicted in the heat map below, Casualty Cat reveals that these exposures show a tendency toward systemic risk rather than classic clash (as depicted by purple, grey, and green) and will be driven by the sheer volume of policies written — impacted by intense regulatoin and vulnerability to an economic downturn.
According to Casualty Cat, the next two highest exposures are TPL for the construction industry (i.e., NAIC 23), followed by D&O for the construction industry (as depicted in the heat map below by yellow, green, and grey). However, Casualty Cat suggests that these exposures exhibit more signs of classic clash intensity rather than systemic, perhaps arising from a longer and more complex supply chain, greater public exposure as well as the number of subcontractors involved.
Having identified the areas of highest accumulated casualty risk, the carrier can focus on what disaster scenarios trigger a catastrophic casualty loss in a particular industry segment. Casualty Cat can prompt a carrier to generate relevant scenarios that play to a portfolio’s vulnerabilities, testing capital adequacy and risk management strategies more effectively. A carrier can also consider whether current pricing adequately reflects the relative level of risk for that industry compared to others in the portfolio … and load for it accordingly.
Carriers then can apply metrics (such as the insureds’ exposed policy limits and premiums) to estimate losses, assess relative vulnerabilities, and assign risk loads — other portfolio management activities. No longer concealed, casualty catastrophe risks can become knowable and therefore manageable. Casualty Cat enables risk-bearers to take action and enhance their implementations of ERM.
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