High Performance Computing For Competitive Decision-Making

By Matt Reid, Risk Management Solutions (RMS)

Today's re/insurers face an increasingly competitive market, mounting scrutiny from ratings agencies and regulators, and the constant demand for results from investors and shareholders. In order to thrive and grow in such a demanding environment, they must ensure that their decision makers have the information and analytical capabilities necessary to make intelligent and well-informed decisions, as quickly as possible. For those who manage catastrophe risk, the ability to make decisions that require large volumes of exposure data to be captured, analyzed, and modeled quickly is crucial.

In other industries where a competitive advantage can be gained through sophisticated and thorough analysis of large volumes of data, many market leaders have turned to high-performance computing (HPC) to maintain and expand their edge.

Once the domain of Super Computers and government funded laboratories, this technology is now available for commercial use and provides benefits for IT organizations, business users and the enterprises they support.

What Is High-Performance Computing? High performance computing consolidates computing resources onto a single grid where those resources can be shared by, and dynamically allocated to, any number of business units, users and tasks. This model typically results in higher utilization of compute resources, lower IT overheads and improved workflow capabilities while also enabling a single, high priority task to execute very quickly by commandeering a large proportion of the grid until it completes.

High Performance Computing environments provide IT organizations with the ability to configure and manage infrastructure from one central location, administer user capabilities, identify and empower priority users, structure resources around user groups and business functions, monitor key performance indicators, and run system diagnostics across the entire infrastructure. Clearly, HPC can provide demonstrable benefits to the IT organization but the real value comes through its ability to deliver significantly improved analytical capabilities to the enterprise.

Using HPC, analysts and underwriters can more efficiently employ hardware to scale and manage catastrophe model performance to match their immediate business requirements and gain deeper insights into their books of business.

As catastrophe modeling has become more and more sophisticated and more deeply embedded into many re/insurers businesses, there is a fundamental need to understand the models and clearly comprehend their underlying assumptions, limitations and capabilities. A clear grasp of model behavior and the inherent uncertainty in their output is fundamental to making sound decisions. At the same time, the high volumes of data and the time it takes to analyze that it is introducing 'data latency' into many risk management processes. By the time many re/insurers have completed the process of rolling up all their business into a consolidated view of risk, that position has changed as some policies/treaties expire and others are bound in their place.

The ability to maximize the utilization of computational resources, drive higher volumes of analyses and 'fast-track' priority work delivered by HPC environments enables these crucial activities to be better embedded into the re/insurance workflow. This allows decision-makers to make both faster and better judgments.

Those who effectively utilize the full potential of high performance computing and the advanced analytics that it enables will be able to make the most informed and timely risk-based decisions. And, those that make the most informed and timely decisions. are those that lead their industries.

About the Author: Matt Reid is senior director of solutions marketing at Risk Management Solutions (RMS). He has over 20 years of experience in software egineering, product marketing and communications.