Exposure and catastrophe modelling platforms are among the most significant items that (re)insurers and brokers must include in their annual budgets. The licensing fees can be in the millions of pounds, without even including the high infrastructure cost or the specialised staff required to run the platforms. Increasingly, cat modelling teams and their budgets are coming under the purview of the chief actuary.
Many (re)insurers have processes that are closely tied to their chosen modelling vendor’s data formats, making it extremely difficult to switch to another supplier. One carrier told me some time ago that extracting themselves from a supplier relationship would be “like open heart surgery.” Thankfully, recent developments in the market should allow companies to reduce their reliance on single suppliers, as well as providing the flexibility to more easily adopt other modelling platforms — opening new business opportunities.
NASDAQ (formerly Simplitium) has created the Open Exposure Data (OED) format, which aims to be an industry-standard format for exposure data. Separately, transformations (essentially data mappings) are being created to allow (re)insurance businesses to convert data from the OED format to various catastrophe modelling platform data-import formats. Data can be scrubbed from the original statement of values into a single data format and then transformed into whatever cat modelling format each individual company requires.
There are two groups, on either side of the Atlantic, currently assessing the benefits and potential pitfalls of adopting an industry standard data format. Both groups are working on those transformations. In Europe, there is the Interoperability Technical Working Group (ITWG), while in the US there is a similar group called the Catastrophe Modeling Operating Standards (CMOS). The great hope is that both will converge reasonably soon and offer the same data standard for use by the global insurance markets.
The benefits of standardisation
If the global market adopts an industry standard format for exposure and cat modelling, several immediate and obvious benefits will ensue. First, (re)insurers could become much more model-agnostic, putting in place a largely consistent process upstream of sending data (via a transformation) to the relevant exposure or cat platform – regardless of the modelling platform in use now or in the future.
Second, (re)insurers would avoid having to rely on a single model supplier. With a common data standard as the lifeblood of the industry, they could use multiple model platforms simply by running multiple transformations from the same database of scrubbed data. They could also potentially switch model providers as needed, with much less effort, leading to increased competition and reduced cost.
Third, having all data – which could include not just exposure data but potentially also modelled loss and claims data – in a single repository can create a goldmine of information for interrogation by data scientists, allowing them to uncover hidden value. Those new business insights could deliver significant benefits for (re)insurers, helping them to refine existing products and create new products that meet previously unknown, or insufficiently understood, market needs.
Finally, having a single industry standard data format would give (re)insurers and brokers a stronger business case for automating their processes, secure in the knowledge that those processes will stay the same regardless of which downstream cat modelling platform they use in the future.
The development of a flexible, industry-standard data format is intuitively attractive to almost everyone with experience in the cat modelling process. As more actuaries are drawn into the complex world of catastrophe modelling, data management innovations that simplify their work will be welcomed with open arms.
Justin Davies is head of EMEA at Xceedance.
