Here we begin a review of the contributions to GCCapitalIdeas from Guy Carpenter’s Chief Actuary, Donald Mango, in the last year.
ERM Did Not Fail: The profound financial damage that began last year has left the insurance industry looking for answers. Diligent underwriting and conservative investment strategies were not enough to prevent natural and financial catastrophes from bleeding balance sheets. Both firm leadership teams and key stakeholders have questioned the value of Enterprise Risk Management (ERM) frameworks, yet the conclusion that ERM failed may be hasty. After all, the insurance industry actually survived the events of 2008 reasonably well, with at least some of the credit going to their ERM efforts. Where risk management did fail, the underlying causes were deeper.
Optimize Capital Allocation with Co-xTVaR: In choosing a capital allocation method, firms must balance the sophistication of the method with calculation time and resource commitment. One approach, co-xTVaR, strikes a balance between theoretical soundness and efficiency. In a capital-constrained environment, using co-xTVaR to allocate the cost of capital can provide a clear competitive advantage.
ERM Advanced by Financial Crisis: As expected, insurers have continued to accelerate their development of Enterprise Risk Management (ERM) practices following last year’s financial crisis. The impact to both sides of the balance sheet emphasized the importance of tracking every risk a carrier faces and protecting capital from a wide range of threats. As ERM practices evolve, clear definitions and terminology become critical. A common language and framework will facilitate process and technical innovation, improving the transfer of practices across companies and simplifying the disclosure process - all of which will lead to more accurate risk evaluation.
Capital Modeling in the Age of Systemic Risk, Part I: Hidden risks lurk in nearly every insurance portfolio. Unexpected accumulations, correlated threats and unimagined financial market developments can take shape quickly and severely. When disaster strikes - either because of a storm or an economic shift - insured and asset losses can drain balance sheets, impair return on equity (ROE) performance and destroy shareholder value. The cost of systemic and hidden risks can impact every link in an insurer’s financial supply chain, with today’s losses causing capital costs to rise for months, even years.
Capital Modeling in the Age of Systemic Risk, Part II: To derive the greatest benefit from an ERM investment, risk management by metrics becomes essential. Every risk assumption, retention or transfer decision must be analyzed using the holistic model to determine whether it is shareholder value-accretive. A rigorous, disciplined capital modeling effort will help a carrier move confidently by supporting strategic decisions with an objective, quantitative foundation.
Capital Modeling in the Age of Systemic Risk, Part III: The net impact of prudent capital modeling and management - in regards to both rating agency evaluation and regulatory compliance - is a competitive advantage. (Re)insurers that accept the outcomes of rating agency or standard regulatory calculations may wind up either with gaps in cover (where de facto approaches are insufficient to address a carrier’s risks) or unproductive capital (where the norm requires over-allocation). The use of an internal capital model, on the other hand, allows a carrier to optimize its analysis to its own situation, with more accurate results and more informed decision-making.
Capital Modeling in the Age of Systemic Risk, Part IV: Even in the early stages of ERM and economic capital modeling, progress continues. Investments are being made in better risk identification methods and more resilient ERM structures. Capital modeling technology is advancing as well, including better coverage of asset-side risks. With property-catastrophe modeling fairly well established, attention is now turning to casualty catastrophes - a far tougher modeling challenge, as the dimensions of correlation are broader and more complex. Economic bubbles expand and burst with greater frequency and severity. Government intervention policies and practices could be reducing the relevance of the past for forecasting the future. Global interdependency, trading relationships and economic shifts are colliding with property catastrophes, which may be showing the effects of climate change.