ORSA: Turning burden to boon

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Developing better ECM will likely make investment well worth the effort.

Insurance companies have a window of opportunity before them to improve the quantification of the various risks they face by using economic capital modeling. Doing so will better align risks with operating plans—and the budgeting and financial planning process—giving early adopters a formidable advantage over their competitors.

At first glance, it might not seem like an opportunity, since much of the impetus for quantifying risk is coming from regulatory pressures. Economic capital modeling (ECM) is part of the regulatory initiative, Own Risk and Solvency Assessment (ORSA). The work needed to comply is likely to cost carriers much time, effort, and money. The new ORSA-driven regulations, scheduled to go into effect for the fiscal year 2015 in the United States, mimic the European Union’s Solvency II ORSA directive and are being driven by the state insurance commissioners. The new rules are designed to give regulators the capability to examine and evaluate the strength of an insurer’s enterprise risk management framework and capital adequacy levels.

As part of the regulations, carriers must conduct annual risk assessments that describe in detail their enterprise risk-management policies and procedures, and express risk quantitatively in normal and stressed environments. Carriers must also conduct economic capital and solvency assessments, and issue three- to five-year projected financial statements. But the National Association of Insurance Commissioners’ requirements are principle-based, allowing plenty of leeway to the states to write any prescriptive refinements, and thus leaving flexibility to individual insurance companies.

Carpe diem

Despite the expense of compliance, there’s a strong case for spending the extra capital to invest in processes and procedures to get it right: ways that will meaningfully help carriers better measure various types of risk. In an age of increased computer power and sophisticated analytics, quantification of risk will eventually arrive in one form or another eventually for all insurers. Those carriers that put off investment in ECM risk being left behind by their respective peer groups.

Already, companies preparing for the NAIC’s ORSA principle-based guidance are developing very evolved, high-quality processes around risk procedures. These processes are helping them better allocate capital for various business lines and ultimately decide which strategies to pursue and which ones to jettison. They can also achieve better focus on any potential variation from operating plans.

Insurers already use quantitative measures for measuring balance sheet risk: On a macroeconomic level, they assess the impact of interest-rate changes of 100-200 basis points on interest income and the fair value of its debt. On a microeconomic level, insurers analyze market segment risk by mining the claims data they receive.

But when it comes to operational, reputational, and strategic risk, carriers have less of a clear picture on things. What happens to a company’s financial condition for every one percentage-point increase in the inflation rate, or if unemployment rises or gross domestic product falls?

In these areas, carriers tend to still use qualitative descriptors rather than quantitative ones. For risk levels such as likelihood and impact, qualitative descriptors might be receive an internal rating of 1-5, or use stoplight ratings of red, yellow, and green. 

Regardless of how insurers approach the ORSA regulation, the qualitative grades won’t advance them on how operational and strategic risk affect the bottom line. Rather than viewing it as a burden, carriers should view ORSA as an opportunity. In an age where innovation makes today’s business into tomorrow’s horse and buggy, operational and strategic risk have in itself become a major issue facing insurers. By digging deeper and developing an ECM process to evaluate each risk for each business line, carriers can make more informed decisions. ECM puts budgeting in stochastic terms, taking a randomly determined sequence of observations and producing revenue projections with upside and downside variations.

Quantification, bit by bit

For example, Milliman worked with a national health insurer to turn qualitative assessments into actionable quantitative values. It involved finding experts in the company for each particular risk and interviewing them to find out the range of potential financial impact each risk posed. For each scenario, we worked to determine what are possible outcomes in terms of types of impacts, from worst to most likely to best. Would these impacts mean a reduction in revenue, an increase in expense, or a reduction in asset value? It’s critical to express the outcomes—in terms of financial impact—as specifically as possible.

Developing ECM involves a thorough assessment of all risks in all segments. In a hypothetical example, the worst outcome of a particular risk might translate to an increase in expenses. We can then examine what the worst scenario will be over the next 12 months. In this example, say the worst outcome would be a $25 million rise in expenses, while the best would mean a $500,000 increase. We can then examine what scenario is most likely. By assigning a probability, we come up with a likelihood of a $7 million expense by assigning different levels of confidence to the outcomes.

By doing this for all the risks and assigning values in terms of financial impact, businesses can then act on the data, giving priority to the risks that are the most serious. By assigning a numerical value to each risk, carriers can compare all of them at once and act accordingly. For the national health insurer, it meant being able to assign financial impact to all major business lines and subsidiaries, in order to come up with a global picture of financial health.

In fact, ECM can be used for any type of company. Say a manager of a computer manufacturer’s particular geographic region wants a new capital allocation of $50 million to build a new plant in an emerging market, with projected annual revenues of $250 million by the third year after the investment. While it seems like a worthwhile opportunity, what are the risks in terms of labor costs, changing politics, tax laws, and governmental oversight? How will the severity and likelihood of these events affect the revenue-generating potential of the plant? By estimating all of these factors, what looks like a profit-making enterprise might show a reasonable probability of a looming financial disaster under certain circumstances.

Treat mandates as R&D

Business managers should never skip the step of measuring their own risk-taking activities. By using ECM, a company can eliminate or modify those areas that have risks that are too high to justify the reward. By designing, building, and testing models, carriers will achieve a much higher percentage of successful outcomes. Insurers should use the NAIC’s current ORSA recommendations as the basis for a research and development platform of sorts, with the mission of better quantifying their risks and enhancing their competitive advantage.

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