Actuarial departments have developed isolated computing capabilities since the advent of desktop actuarial systems in the 1980s. Those systems enabled actuaries to create and analyze financial models, price insurance products and meet regulatory requirements independent of the IT organization.
As useful as that independent approach may have been in its time, it fostered the proliferation of multiple actuarial systems through the enterprise that do not integrate tightly with core insurance systems. That presents a challenge for insurers trying to create a more reliable and current view of risk across the enterprise, according to Van Beach, director of business development for Milliman's MG-ALFA life insurance financial modeling solution.
Since the 1980s demands on financial models have grown exponentially, according to Beach. "These models are now used to produce a wide array of risk management calculations; they require coordination across a wider user base, they utilize an ever-increasing amount of data, and they have become more complicated and computation-intensive," he says. "Over time the complexities of these process demands have caused a drift in actuarial focus from analyzing risk to managing an increasingly manual and burdensome production of risk numbers."
Beach argues that IT organizations can now play a role in both tightly integrating actuarial departments within insurers' enterprise risk management capabilities and enabling actuaries to refocus their efforts on interpreting rather than collecting information. Beach identifies five key areas where strategic IT investment can improve risk management:
- Ensure quality data. Like all analytic processes, the starting point is data, and actuaries require a lot of it. In addition to in-force data, the volume and variety of assumption data required for the financial models presents a unique challenge.
- Improve control and quality of the actuarial process. Version control, audit logs, security, etc., are needed to provide the confidence in results required for actionable information.
- Reduce the actuarial process burden. Automation of data manipulations and model runs, creation of repeatable process flows, etc., will enable actuaries to spend more time on risk analysis and less time on production.
- Provide power. To understand risks, particularly those tied to future financial conditions, thousands of potential scenarios need to be considered. With greater access to computation power, the timeliness and quality of risk analysis improves.
- Increase access to risk metrics. As process flows and computational resources improve, actuaries can focus on providing timely, appropriate risk information to a wider audience.
Anthony O'Donnell has covered technology in the insurance industry since 2000, when he joined the editorial staff of Insurance & Technology. As an editor and reporter for I&T and the InformationWeek Financial Services of TechWeb he has written on all areas of information ... View Full Bio