Increased reporting requirements have ramped up the pressure on insurers to provide regular insights into their work, and the Covid-19 pandemic only accelerated these pressures. The last year saw rapid fluctuations in insurance data and new trends emerging on an almost daily basis.

Willis Towers Watson's (WTW) ResQ platform puts significant deterministic and stochastic modelling power at the hands of users to assist with these pressures. Its modelling and reserving methods, already amongst the best in the industry, are accompanied by mechanisms which make it easy to structure, access and manage data sets across projects.

ResQ also enables a core analytical framework to be built and managed across projects with hundreds of reserving classes, thereby ensuring consistency in approach.

The company has continued to innovate this year to ensure the software meets the emerging needs of reserving teams, by performing quicker analyses more often, using more data, and providing more insights. In one example, ResQ helped a property and casualty insurer with multiple legacy data systems to cut down a data review from a five-day target to hours.

"We are constantly looking at the changing nature of the amount of data that's available, but also the technology that people are using," says Jamie Mackay, director at WTW.

"It is about understanding the consistency of something over time. So, whenever we look at deploying new techniques or methods, we look at how they can be enhanced and how we can improve on the existing framework that we have."