Data for Data’s Sake Doesn’t Work

Remote working caused by the pandemic has seen the industry’s perception shift on the value that innovative technology delivers, but Covid and the lack of face-to-face contact have proven to be a “double-edged sword,” a prevailing view during Insurance Day’s insurtech webinar.

Tom Anderson, Director of Sales, AdvantageGo, joined George Beattie, Head of Incubation Underwriting, Beazley, Lautaro Mon, Chief Product Officer, Charles Taylor InsureTech, and Andrew Johnston, Global Head of Insurtech, Willis Re in a virtual panel session moderated by Lorenzo Spoerry, Deputy Editor, Insurance Day.

During the session, participants discussed trends that will emerge over the next 12-18 months, if the industry is ingesting and analysing the right data, and whether Artificial Intelligence (AI) and machine learning are enabling insurers to analyse data and derive valuable conclusions from it.

Kicking off the webinar, Lorenzo asks the panellists to share their thoughts on key trends we can expect to see over the next year or so. Andrew Johnston discusses that no particular technology will make huge and transformative changes, but technology is now truly top of mind in company strategy with incremental improvements along the way. Commenting on this, Andrew says: “The issue of technology, in general, has been floated to the top of most decision-making bodies in the industry, and I think anybody who was questioning the value of technology probably isn’t any more.”

Tom Anderson agreed with Andrew, discussing how the focus will be on getting people to embrace technology. He also supported Andrew’s point about insurers adopting a more agile approach to deploying technology, giving themselves time to test innovative technology and allowing employees to digest changes in a paced fashion rather than dealing with a quantum leap. “You’re not going to see this massive leap; what you’re going to see are organisations that have evolved around technology.”

Data for Data’s Sake

Obtaining and using data correctly is a huge challenge; does the industry feel it has the right data, and is it digesting it and using it in the right way, asks Lorenzo.

George Beattie responds: “Everyone always talks about more data, better data, more granular data, insights from data. In order for any of that to be true or accurate, we need to understand what problem we’re trying to solve with that data. So data for data’s sake doesn’t mean anything. My prevailing thought would be, understanding data is really good if you take steps to understand the problem you’re trying to solve first. If you jump into data before doing that, then it ends up being very circuitous and very difficult to define the value of doing the work.” The other panellists all agreed with George that identifying the problem that data is expected to alleviate should be the first step in any data strategy.

To what extent are we successful in using machine learning and AI to analyse data and derive useful conclusions from it, was the next question posed to the panel.

Despite lots of investment in these areas, Lautaro Mon thinks there is still a long way to go: “From a data perspective, I think we spent ages focused on mandatory data, so that the data that we need to run in the insurance business per se, but somehow we now understand that there is a lot more data that gets involved in the process – more contextual data, social networks, etc.”

Answering this question, Thomas Anderson believes that as legacy software continues to evolve and be replaced, AI and machine learning will enable the industry to take on a more proactive than reactive stance in not only making better decisions on risk but in solving the problem in preventing loss and preventing issues happening in the first place: “AI and machine learning are absolutely going to be quintessential for figuring out certain pieces and parts of that puzzle that gets to that ultimate end game solution for you.”

To listen to the webinar in full, please click here.