Posts Tagged ‘modeling’
Here we review recent GC Capital Ideas posts on new product development as an emerging risk.
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.
In realizing the goal of profitable growth, (re)insurers require a trusted partner to help them manage a rapidly evolving regulatory and rating agency environment.
The insurance industry relies to a large extent on catastrophe models to manage catastrophe risk. Regulators and rating agencies recognize this fact by asking companies to justify their modeling approach. The underlying objective of such rules is to encourage companies to have a robust and consistent process to use modeling tools responsibly.
The Own Risk and Solvency Assessment (ORSA) requirements are the key element of the Pillar 2 qualitative risk management requirements. The purpose of an “own risk assessment” by each company is to prove the appropriateness of the standard formula or internal model results if the company has applied for a certified internal model. While the Pillar 1 solvency capital requirement is calculated on a one-year basis to show that a company has enough capital to avoid insolvency through the end of the year in a 1-in-200 year event, the focus in Pillar 2 ORSA is the forward-looking assessment of solvency capital adequacy. Companies need to provide a projection of the risk and capital position for the entire planning period (at least three years), which has to be consistent with the business case balance sheet and profit and loss projection. The aim of ORSA is to demonstrate that there is an adequate level of capital available to support the business plan for a longer period. Based on this planning projection of the risk and capital position, (re)insurers need to define meaningful stress tests and scenarios to show they would be adequately capitalized in adverse scenarios as well. If a company would face solvency issues in certain stress scenarios, it needs to show it has countermeasures in place in order to reach the strategic targets of the corporate and risk strategy again.
One purpose of enterprise risk management (ERM) is to help (re)insurers determine how much capital is needed to support the risks they assume (subject to risk tolerance). Instead of segmenting portfolios and handling each peril on a standalone basis, a robust ERM methodology would use a holistic approach to risk and capital management where threats are identified and monitored, all action plans are developed and risks are measured.
Guy Carpenter Announces MetaRisk® 8.1, the Latest Version of its Premier Economic Capital Modeling Tool Suite
The modeling of emerging and casualty catastrophe risks remains challenging and the models continue to vary in their approach, level of development and industry acceptance. With the potential scenarios numerous, diverse and constantly changing, there is no single model or approach that could contemplate all of them. Furthermore, the various disaster scenarios with which carriers are being increasingly confronted needs to be prioritized and synthesized within their enterprise risk management framework. By their very definition, there may be limited data on hand on which to base any modeling. As a result, much of the industry continues to rely on multiple models and actuarial approaches that encompass model applications, probable maximum loss (PML) estimates, realistic disaster scenarios, experience and exposure ratings to create a broad set of scenarios and deterministic views.
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.