SCOR is backing a new research project in conjunction with the Institute of Mathematics of Marseille (I2M), titled: Triangle-Free Reserving.

This project will investigate methodologies for reserving that, instead of relying on aggregated loss data structured into triangles to project losses for each year, utilize the most granular level of available information. The research will build on the work done in “Triangle-free reserving - A non-traditional framework for estimating reserves and reserve uncertainty”, Parodi (2014), which presented a practical implementation of the “triangle-free reserving” framework. The idea of granular reserving has actually been around since the 1990s, although mostly in academic circles.
 

The idea behind this research is that traditional reserving methods use aggregate data because they were developed at a time when computing power was limited. However, using aggregated data results in information compression and ultimately loss of information that hinders an accurate estimation of the statistical distribution of projected outcomes — which is the aim of a reserving exercise. Furthermore, pricing is normally undertaken at a more granular level, and there is therefore a disconnect from pricing. Reserving measures the risk retrospectively, while pricing measures it prospectively — however, the risk is fundamentally the same.

The triangle-free framework uses a frequency/severity approach based on the collective risk model, similar to what is done in pricing. This framework has been established and is currently in use, for example in claim count development in pricing (Parodi, 2023), but many questions remain unresolved, of both a theoretical and a practical nature. This project aims to advance on these questions.

Go to the project page