Enterprising solutions: effective ERM allows insurers to exceed compliance and regulatory requirements.

Many insurers gradually have been moving toward an enterprise risk management framework for the past several years. One would expect them to be ahead of the curve. Since its inception, the insurance industry has been performing transactional risk management on a policy-level basis when assessing risks due to catastrophic events, or the probability of loss on a single life policy.

The primary external forces for ERM include regulatory and rating agency pressure, while internally there is a need to accurately monitor economic capital, perform asset/liability management and implement hedging techniques. These pressures have all driven the need for an effective ERM process.

Most insurers use administration or derivative systems introduced in the 1960s. While these systems don't come close to mimicking today's insurance processing, they do speed administrative functions in the home office with an economy of scale. Property and casualty companies have traveled a similar technological path, resulting in a myriad of systems with data in disparate, siloed systems. For both industries, when enhancements were required for a new line of business or functionality, especially related to analytics, it was usually easier to add stand-alone systems to the already highly complicated infrastructure. On the risk side, underwriting, asset and liability management systems were introduced in the 1980s, adding silos of risk information to an already highly disparate environment.

As a result, achieving effective ERM is very difficult. Data that's captured from silos has a negative impact on making actionable, accurate and timely decisions. An integrated data warehouse bridges the company's disparate databases and provides a single version of data by using consistent definitions, eliminating redundant information and improving accuracy. It also provides data on an integrated and highly granular basis, which is key for determining if the historical and projected performance of risk-related activities is proportionate to the economic capital required to support each activity.

The same enterprise concept and approach applies to the risk model. There's little value in doing economic capital calculations across the enterprise if they're not done consistently. Fed by the warehouse, which represents a single view of the business, the modeling system applies common measurements to project how the business may be impacted in the future. Considerations for the risk model include using a robust economic scenario generator, modeling assets and liabilities in the same model at the same time and reflecting management decisions. The fundamental improvement is the ability to analyze the results and provide rating agencies and regulators with an analysis of risks and a plan for mitigation.

The process must become an integral and frequently used part of the overall management of the company and be monitored constantly.

Understanding the current position of the enterprise, as well as different ways it could be affected by enterprise grade modeling, is essential. What appears to be a requirement is actually an opportunity for insurers to transcend siloed systems and processes, nurture capital growth and develop enterprise processes and active decisioning. Companies that embrace an enterprise approach to risk management and implement the strategies and technologies required to manage it not only will exceed their compliance and regulatory requirements in both depth and breadth, but also establish a strong competitive advantage.

Robert Dyer, a Best's Review contributor, is a senior insurance industry consultant with Teradata, a division of NCR Corp. He can be reached at [e-mail].