Industry Moves Away From Multi-Model Approach Given Current Market Conditions
Insurers and reinsurers are increasingly adopting a core model strategy based around a detailed assessment of its capabilities, instead of the multi-model or blended approach as investment in modeling capabilities comes under pressure, says Matthew Eagle, Head of GC Analytics® - International at Guy Carpenter.
“Recent events including the Fort McMurray wildfire have demonstrated that catastrophe risk remains not only a capital issue but also an earnings issue,” says Mr. Eagle. “The lower earnings reported by a number of insurers and reinsurers in the second quarter of 2016 reflect this.” Yet ongoing rate pressures are decreasing market appetite for further increases in model investment to help better understand these risks. Add to this the resource intensive model validation required by Solvency II and the ability to maintain multi-model strategies is coming under significant pressure.”
These market dynamics are causing a fundamental change in how companies approach their modeling capabilities. “While model comparison remains important, clients, particularly in Europe, are migrating more towards a strategy based around a core model while working to gain a deeper understanding of the strengths and weaknesses of that model. Additionally, if a model is embedded in the underwriting process, the implementation is easier with a single model than with the multi-model approach,” asserts Mr. Eagle.
This kind of approach places greater onus on practitioners to play a proactive role in the process, rather than accepting commercial models at face value. According to Mr. Eagle, “insurers can no longer afford to be passive partners in this process - they cannot rely on others to understand their own risks. They must look to leverage the scale of the catastrophe model vendors while also being fully aware of their limitations. We have seen models under or over-estimating event losses, we have seen significant changes to model results following new releases, and of course, we have experienced the losses that were not yet on the radar screen.”
This heightened hands-on approach requires a more robust and standardized process for model evaluation. “Our Guy Carpenter Model Suitability Analysis (MSA)® framework for cat model validation is designed to give clients increased confidence and control,” Mr. Eagle says. “By providing an independent and unbiased review, we look to help standardize as much of the process as we can and to be fully transparent, working with a wide network of respected and credible academic and research partners.”
As the industry looks to expand coverage, new models will of course require platforms on which to run. “Many developers tended to build platforms to run their own models, but there are many other potential providers of models or at least model components which do not have the resources or skills to build a platform,” he explains. “As a result, we have supported initiatives such as the OASIS Loss Modeling Framework, which have not only helped to provide some standards for model components, but also created the computational engine that links the components together and carries out the loss calculations.”
Mr. Eagle continues: “Traditional commercial vendors have also responded by increasingly opening up their platforms to allow third-party models to be run from their environments. We believe we will increasingly see a distinction between the platform and the models themselves, although we should not lose sight of platform implementation issues such as correlation and uncertainty.”
As vendors open up platforms, this creates opportunities for insurers to develop bespoke models. “Instead of building yet another European windstorm model from start to finish,” Mr. Eagle states, “why not leverage the widely used and validated model components of existing models but replace components with bespoke elements reflecting the portfolio specifics?” Mr. Eagle concludes: “A new peril model may be perfectly reasonable, but we all know that each model comes with its own assumptions. Unless one is introducing new science and research, we suggest clients and their brokers focus on the pieces that leverage their own data.”