Posts Tagged ‘Guy Carp’



December 22nd, 2014

Understanding Emerging Risks: Imperative for the Future

Posted at 1:00 AM ET

The downside focus of risk measures highlights what could be a key problem with the debate around emerging risks - when people think about risk they only consider the downside. Cars, penicillin, fossil fuels, the internet - all of these were once emerging risks, and they have caused global destruction through car accidents, antibiotic resistance, climate change, and now, possibly through cyber risk. But they have also brought far better travel, longer and much healthier lives for almost everyone, affordable electricity for people in their own homes, and an explosion of information on a scale never seen before available freely at the click of a button.

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December 18th, 2014

Cycle Mitigation: Part II

Posted at 1:00 AM ET

Incorporating reserve value added (RVA) into reinsurance decision making for long-tail lines is a step in the right direction. However, it is not the full story, as the decision is still typically made in the context of a single accident year and usually for a single line of business in isolation. The cycle correlations clearly show that this is sub-optimal. We are encouraging our clients a step further along the sophistication and hence simplicity/complexity spectrum.

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December 17th, 2014

Guy Carpenter Launches MetaRisk® Reserve™ 4.0

Posted at 5:30 AM ET

Guy Carpenter announced today the launch of MetaRisk Reserve 4.0TM. The latest version of this powerful reserve risk modeling tool delivers improved statistical models and an enhanced user interface.

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December 17th, 2014

Cycle Mitigation: Part I

Posted at 1:00 AM ET

So what can be done to mitigate such cyclical effects? The first steps are to acknowledge them and to try to quantify their impact. The latter is more of a challenge than the former. Most internal capital models are not truly multiyear and arguably fail to adequately capture both the correlation between lines of business and in particular across accident years. Cycle (and recognition pattern) scenario testing is a good way to achieve this. This provides a neat and practical way to correlate between years and lines of business.

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December 16th, 2014

Impact on Results

Posted at 1:00 AM ET

To consider the impact that these cycles may have on the financial statements and solvency positions of insurers there has to be an understanding of the magnitude of any change in ultimate loss and the likely timing of the recognition of that change. The profit or loss in any financial year is a combination of the profit and loss from that accident year and also any recognized changes in the reserves from prior years.

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December 15th, 2014

Reserving Risks

Posted at 1:00 AM ET

The previous sections suggested how “dark matter” can be lurking on an insurer’s balance sheets in the form of a casualty catastrophe or an emerging and not as yet fully understood risk such as cyber. While there have been significant advances in quantifying the uncertainty pertaining to these risks, it is worth considering how they may manifest themselves in the future and what can be done about them now to protect from the “dark matter” downside.

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December 4th, 2014

Casualty Catastrophe Risk Modeling: Part II

Posted at 1:00 AM ET

Casualty catastrophe occurrences have become increasingly common over the past decade. The recent 2008 financial catastrophe is the easiest to cite, due to its sheer size and the fact that it continues to unfold even today. But, there have been many others. The collapse of the “dotcom economy” led to scandals around initial public offering laddering and equity analyst conflicts of interest. Accounting firms were not alone in suffering financial loss related to such debacles as Enron, WorldCom, Tyco and Adelphia. While insured losses did not reach those of property catastrophes, economic damages were profound. Enron’s loss of USD66 billion in market capitalization alone - not including the economic damage caused to other companies - was more than double that of Hurricane Ike (approximately USD30 billion). The financial catastrophe is estimated to have caused economic damage of above USD1 trillion, with more likely to follow. When considered in the context of the Deepwater Horizon industrial accident, the casualty catastrophe that unraveled from the largest US offshore energy event over the past 40 years was by no means remote. Beyond the initial property loss of the actual drilling rig, liability risk in paying claims continues to extend and ripple throughout the supply chain involved as well as the environmental impact to numerous coastal and commercial businesses. Asbestos litigation, perhaps the longest casualty catastrophe on record, has paid out over USD70 billion and by some accounts may be entering its third wave. Therefore, asbestos is an emerging crystalizing risk that needs to be continuously monitored, measured and modeled for those who continue to be exposed to it.

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December 3rd, 2014

Casualty Catastrophe Risk Modeling: Part I

Posted at 1:00 AM ET

Casualty (or liability based) catastrophes have become increasingly frequent and severe over the past decade, exposing (re)insurers to much more risk than they may have realized and reserved for. One root cause can trigger a chain reaction that can bleed balance sheets and even imperil solvency. Until recently, casualty carriers had little choice but to accept this risk as losses emerged.

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December 2nd, 2014

Emerging Risk: RMS Global Probabilistic Terrorism Model

Posted at 1:00 AM ET

Risk Management Solutions (RMS) released an updated Probabilistic Terrorism Model (PTM) in July 2012, version 3.1.2. The new model revised the annual frequency of a terrorist attack on US soil. No updates were made to geographies outside the United States.

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November 26th, 2014

Emerging Risk: AIR US Terrorism Model

Posted at 1:00 AM ET

AIR implemented significant model updates in version 13 of CLASIC/2TM, released in 2011. The updates impacted hazard components such as the target and landmark database, event frequency estimates and exposure and policy conditions.

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