New experimental techniques are allowing the generation of complex data sets that characterize signal-transduction networks. It is no longer possible to inspect these data by intuition to extract the ...

In this chapter, we examine the modelling of operational loss data, which can be applied in the modelling of internal loss data (ILD) and external data (ED). The use of ILD in the capital model ...

Aon’s head of catastrophe insight explains the role data science plays in quantifying natural disaster risk and the future of climate modelling. As part of Data Science Week on SiliconRepublic.com, we ...

Marginal models for multivariate binary data permit separate modelling of the relationship of the response with explanatory variables, and the association between pairs of responses. When the former ...

Just because your firm can use your existing data for AI risk modelling doesn’t mean you should. There’s a perception that AI can create accurate predictions based on any data set. That’s not always ...

Snowflake went public this week, and in a mark of the wider ecosystem that is evolving around data warehousing, a startup that has built a completely new concept for modelling warehoused data is ...

Data modelling around Covid, climate and economic shocks, house-price collapse and sharemarket crashes has mostly been wrong for decades, writes Dan Petrie. A recent cold snap only a month ago ...

1. Over the last two decades, a large number of camera trap surveys have been carried out around the world and camera traps have been proposed as an ideal tool for inventorying and monitoring medium ...

Acquisition builds on prior partnership that delivered Gearbox, an LLM-powered linking tool that enhances S&P Global's ability to serve customer AI needs NEW YORK, June 9, 2025 /PRNewswire/ -- S&P ...