Radius Analytics Industrialised risk modelling

Recent years have seen a deep recogntion of the profound value of data. “It’s the new oil” as the saying goes. However this data is almost worthless without analysis and meaningful summarisation. Data needs to be harnessed and channelled through models to mine its real value, and as importantly, to amplify its value.

The advent of LLMs has not changed this. In large organisations LLMs will primarily act as a declarative, linguistic and interpretive layer over the top of models, data and services in the form of API’s. They won’t be the models themselves.

In demanding modelling environments like credit risk modelling, in which banks face heavy regulatory scrutiny, modelling is an essential function, and yet models tend to be extremely fragile, as well as taking an inordinately long time to build.

With £35tn in assets affected by modelling worldwide, and USD$100m spent by banks individually to get through regulator-imposed stress testing periods, the need for improvement is extr