SOLUTIONS In efforts to quantify potential loss, much of the industry continues to rely on multiple models and actuarial approaches that encompass items such as model applications, probable maximum loss estimates, realistic disaster scenarios, experience and exposure ratings to create a broad set of scenarios and deterministic views.


“GC ForCas has been developed as a platform with model components to cover US commercial lines losses resulting from casualty catastrophes.”


Cyber gaps and exclusions in traditional policies, along with the


emergence of standalone cyber insurance solutions for new risks, produces a situation where businesses struggle to fully comprehend the boundaries of their cover.


OPPORTUNITIES AND CHALLENGES          insurers, there is an opportunity for innovation with the development of models that can measure and quantify cyber risk to determine pricing, correlated loss and capital support.


With the opportunities come challenges. Data will be a key factor for


enabling further analysis and the development of models to enhance the understanding of cyber risk. The systemic, intangible and constantly     portfolios that could trigger a wide range of economic losses on a global basis.


The key function of modelling is trying to determine what the likelihood of


an event occurring is and, once that happens, what the size of that loss might be. But, the level of historical data that has been used to build probabilistic  have little information when assessing the severity and frequency of possible cyber catastrophe scenarios. Add in the potential for multiple insureds being implicated in a single breach, and the scope of the necessary modelling needed in this emerging risk class is daunting.


         quality of data available and continuing the development of probabilistic modelling, particularly regarding potential loss accumulations.


www.intelligentinsurer.com GC ForCas has been developed as a platform with model components


to cover US commercial lines losses resulting from casualty catastrophes. It is an experienced-based model that groups historic losses into three  leverages a variety of industry sources to model loss scenarios and line of business dependencies. Through the modelling process industry portfolio concentrations will be uncovered by mapping exposures and analysing the interrelationships among those industries.


The GC ForCas Cyber component has been developed to examine cyber  liability, network security liability, business interruption and data asset protection, among others.





                  catastrophe risk. Guy Carpenter’s MetaRisk and BenchmaRQ are standardised economic capital models empowering decision-makers with a deeper view of risk drivers.


Guy Carpenter has developed these and other tools and solutions to help our clients better understand, manage and quantify their cyber risks, with the goal of turning them into opportunities for growth.


For more information visit: www.guycarp.com November 2015 | INTELLIGENT INSURER | 37


New data and modelling applications are being synthesised and adapted within existing model frameworks allowing carriers to better underwrite and manage these risks. Other applications involve identifying and quantifying emerging ‘aggregating’ exposure concentrations such as those resulting from global supply chain dynamics. Other niche models, such as Guy Carpenter’s MetaRisk Reserve, can focus on various ‘crystallising’ emerging threats emanating from the accumulation of systemic reserves over multiple years.


As the level of sophistication and tools for deterministic modelling capabilities increases, the next step that arises is the more challenging leap toward a more probabilistic and holistic model approach.


A casualty catastrophe model must consider the complexities of damage and liability that will not be contained in one geographic area or one industry.


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