Chart highlights the result of a survey taken of 107 insurance and reinsurance professionals conducted by Guy Carpenter at the 2016 annual meeting of the Property Casualty Insurers Association of America when asked where they see the biggest growth opportunities.
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Chart highlights the result of a survey taken of 107 insurance and reinsurance professionals conducted by Guy Carpenter at the 2016 annual meeting of the Property Casualty Insurers Association of America when asked what they see as the biggest threat to their plans for growth.
Chart highlights the result of a survey taken of 107 insurance and reinsurance professionals conducted by Guy Carpenter at the 2016 annual meeting of the Property Casualty Insurers Association of America when asked which capital sources they will utilize more of in 2017.
Julia Chu, Managing Director, Guy Carpenter and Ashwin Kashyap, Director of Product Management, Symantec Corporation
Cyber risk is now an embedded feature of the global risk landscape, and preventative risk management and post-event remediation are gaining importance as shareholders, customers, supply chain partners, and regulators are increasingly focused on how companies are managing for cyber risks. Insurance is becoming an important piece of the strategy for helping businesses address these risks.
The obvious response to the issues emerging risks provide is to make sure reserves and capital position are more than robust enough for any eventuality - however remote - and then release them when the risks fail to materialize. But, there are many arguments against this as a practical strategy:
The chart below attempts to illustrate the solvency calculation issue. Suppose the best estimate is 20 and the assessment from modeling is that the 1-in-200-year ultimate loss is 100. If all else stays the same and with the simplifying assumption that the yield curve stays flat, one can say that the sum of the 1-year solvency capital requirements (SCRs) approximated the difference between 100 and 20 (i.e. 80). Yet, because of the discounting, when in time the change in own funds is recognized, is important. The black line represents a linear recognition pattern so the 1-year SCRs are all equal with increments of 10. The blue line represents a Binary Fast recognition so the first year SCR is 80 and the remaining years’ SCR are zero. This means that the deterioration is recognized quickly. The red line again shows binary recognition but with a slow pattern as the movement is only occurring toward the end of the liabilities’ life. The two curves in light blue and light red represent less severe versions of the binary forms.
As discussed in the Executive Summary of this report, the term “crystalization of risk” refers to the timescale over which we realize that the risk is manifesting itself and how this view changes until ultimate understanding of quantum is reached and all liabilities are discharged. The “Reserving Risks” section in last year’s report, Ahead of the Curve: Understanding Emerging Risks looked at how information emerges in the presence of reserving cycles. The profit or loss in any particular financial year is made up of not only the profit or loss from the same accident year but also any recognized changes in the reserves on prior years.
Technology Innovation Identified as Top Growth Opportunity for (Re)insurance Industry in 2017, According to Guy Carpenter Annual Market Pulse Survey
Technology innovation will provide the biggest growth opportunities for (re)insurers in the year ahead, according to a survey released today by Guy Carpenter & Company. Now in its fifth year, the annual survey polled executives from insurance and reinsurance companies during the 2016 Property Casualty Insurers Association of America (PCIAA) Annual Meeting held in Dallas, Texas. The goal of this year’s survey was to identify the top opportunities and threats to profitable growth in the year ahead, as well as examine the most significant disruptive forces impacting the industry.
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.