BI’s Article search uses Boolean search capabilities. If you are not familiar with these principles, here are some quick tips.

To search specifically for more than one word, put the search term in quotation marks. For example, “workers compensation”. This will limit your search to that combination of words.

To search for a combination of terms, use quotations and the & symbol. For example, “hurricane” & “loss”.

Login Register Subscribe

Willis Towers Watson enhances risk analytics tools


Willis Towers Watson P.L.C. has launched new analytical tools to help firms diagnose exposures related to cyber risk, natural catastrophes and workers compensation.

Additionally, Willis Towers Watson is releasing enhanced versions of its core analytics tools, the company said Wednesday in a statement.

Cyber Quantified is a predictive tool that measures an organization’s risk due to privacy breach and measures the impact and likelihood of network outage due to a cyber event.

The Workers’ Compensation Diagnostic allows firms to asses how well they are controlling operational risks and managing claims. This tool evaluates claim experience and benchmarks the results against a customized peer set.

The Global Peril Diagnostic helps organizations evaluate natural catastrophe exposures across their entire property portfolio and has been enhanced to be delivered via a web-based platform with increased interactive capability, including maps displaying property locations with site level scores for 12 natural perils.

Additionally, the tool now incorporates global hazard data from Munich Reinsurance Co.’s Natural Hazards Assessment Network, according to the statement.

“Our clients demand cutting-edge analytical solutions that deliver risk insights in new and easy-to-understand ways. We have made significant enhancements to our suite of offerings, allowing for more insightful collaboration and resulting in more strategic risk management and business decisions,” Ben Fidlow, head of Willis Towers Watson Core Analytics, said in the statement.

Read Next