The catastrophe modeling firm RMS estimated the economic loss for property risks to be between USD2.5 billion and USD3.5 billion (1). This estimate includes only residential, commercial, and industrial property and contents. Catastrophe modeling firm AIR estimated the insured loss to be between USD1.7 billion and USD2.9 billion for property risks (2). Both catastrophe modeling firms’ estimates exclude infrastructure, business interruption and contingent business interruption.
Posts Tagged ‘modeling’
Reserving and Capital Setting: Sizing the Problem, Part III: Quantifying Emerging Risks; Expert Judgement
Data quality and availability should also be examined in depth. Because the risks are new, the data may not be captured correctly to power the model, which will lead to further uncertainty and may even preclude the use of a model altogether.
Once the risks have been identified and ranked, the next step is how to quantify the likely impact on the financial results of the firm. The first and most obvious question is what available quantification techniques are available for each risk on the list. This will depend on the availability of relevant data and commercially produced models.
Loss reserves are arguably one of the most difficult risks to estimate and monitor. In fact, inadequate pricing and deficient loss reserves have been the leading cause of property/casualty company impairments. According to A.M. Best, from 1969 to 2009 they triggered approximately 40 percent of all impairments - four times more than those emanating from natural catastrophes (1). There are many uncertainties in managing long-tailed, heavily legislated lines of business that can be triggered from emerging risks. Unforeseen inflation and anticipated legislative changes over a 10 to 30 year period present many demands. In order to prepare for emerging risk scenarios, future trends and related uncertainties need to be explicitly identified, contemplated and estimated.
As businesses, both large and small, throughout all sectors of industry, become more and more reliant on technology to improve service efficiencies and functionalities, cyber risk has become one of the most pressing public topics addressed in corporate boardrooms and by governments across the globe. The corresponding awareness of a business’s susceptibility to a cyber-attack has grown along with a spate of high-profile attacks. Consequently, cyber risk is now an embedded feature of the global risk landscape, not only as a privacy/network liability, which is where much of the publicity has arisen, but also as a peril affecting traditional insurance lines. Therefore, preventative and post-event remediation are gaining importance as shareholders, regulators and rating agencies are increasingly focused on enterprise risk management activities for cyber risks.
In addition to internal risk management, models are typically used in risk transfer negotiations. Both traditional and alternative risk markets require extensive analysis of portfolios when considering risk transfer. Sharing a portfolio’s standardized model output is critical to imparting the loss potential of a particular portfolio from which risk-capital can be unlocked to support the risk financing needs of a reinsurance buyer. Using technology is critical when partnering governments with the private sector. Whether partnering with developed or emerging economies, these tools bring together the risk knowledge and historical data of the public sector with risk management techniques of the insurance industry. The result is an enhanced understanding of risk that provides stability and attracts partners.
Public sector-related data can be expansive, containing census data, property risk characteristics, historical loss information, risk rating matrices and natural hazard event scientific tracking. In order to facilitate packaging the sometimes unwieldy data in a way that is useful for risk decision making, utilizing outside resources to improve data transparency can be valuable. Public sector resources devoted to building tools that measure risks that are perceived as “uninsurable” can unlock private sector funding.
Guy Carpenter & Company today announced the formation of a strategic alliance with Symantec Corporation, a global leader in cyber security, to create a cyber aggregation model. The model will include a comprehensive catalogue of cyber scenarios from which insurers can derive frequency and severity distributions to measure the potential financial impact of loss from both affirmative cyber coverages and “silent” all-risk policies where cyber is the peril, but no cyber exclusions exist.
Mark Murray, Senior Vice President
Technology and innovation continue to change the world around us, creating both opportunities and new challenges for the (re)insurance industry. Advances in risk quantification such as predictive analytics and capital modeling, to name a few, are changing the way we underwrite, price and manage risk. Similarly, technology is allowing A.M. Best (Best’s) to advance the analytics of risk supporting its assessment of balance sheet strength. Taking advantage of stochastic modeling technology, the evaluation of risk within Best’s capital model is undergoing a fairly substantial overhaul to broaden the lens used to analyze risk relative to capital. The technology allows efficient production of multiple capital metrics adjusted for a range of risk levels rather than risk represented by just one data point, providing deeper insights into balance sheet strength, risk profile and risk appetite. The benefit of this overhaul will be a rating that provides greater differentiation among companies, a more informed dialogue around capital versus risk and a more concise measure of “excess” or “deficient” capital. This new lens on capital will significantly influence the way (re)insurers view, measure, communicate and possibly even manage risk.