There are two major innovation-related topics that are top of mind for commercial insurers in Canada and elsewhere around the world, according to Saad Mered, chief executive officer of Zurich Canada. They are: data analytics and the use of artificial intelligence (AI).
“Both topics are interrelated because at their core is the issue of data,” said Mered. “Turning that data into insights and then into action is now a foundational capability that is critical for our customers […] and for us to have long-term success, capability and resilience. But this is a really tough nut to crack, and it’s keeping commercial insurers up at night in terms of planning and figuring out strategically how to incorporate data analytics and AI.”
The questions become: How can commercial insurers find out more about their customers? How can they gain more insights about commercial risks up front? Often, the answers lie in external data – the vast amount of public, open source and third-party data. But are there enough external data sources available to commercial insurers in Canada?
“Once we have that data, how do we uncover insights using capabilities that were once seen to be like science fiction to us (at least for my generation of leaders in the insurance business)?” Mered continued. “For example, today we’re using machine learning techniques on external data to evaluate fire risk on smaller SME clients and smaller locations that would be unaffordable to inspect through traditional risk engineering processes.”
Once the insights are in the bag, the next question is: How can insures deliver those risk insights to the right people at the right time? And as Mered added: “How do we make the life of our underwriters and our claims examiners more productive, more rewarding, and more intellectually pertinent?” That’s the challenge.
“With the current commercial insurance market conditions (rate increases, shrinking capacity, greater scrutiny in risk selection, etc.) the sheer level of submission flow hitting commercial insurers’ desks is massive,” said the CEO. “How do we more efficiently sift through these and clearly get the right submissions to the right people as quickly as possible so that we can be more responsive?
“Then, the next step is: How can we [use data analytics and AI] to prequalify the submissions and pre-underwrite them in a way that saves our team members a lot of time and gets them in better space to actually focus on the right conversations with our brokers and our customers?”
Genpact, a global professional services firm, is one finding answers to the questions keeping commercial insurers up at night. Sasha Senyal, global business leader, insurance, Genpact, said that when it comes to data, creating the right access is the first step to driving change in the insurance space.
“If you look at the insurance industry, it’s based on loads and loads of legacy data,” said Senyal. “How do we actually put that data into a place where we can do something with it? How do we look at claims data and combine it with underwriting data and see if we’ve actually underwritten the right set of policies? Being able to feed those insights back into the front-end sounds fairly simple and intuitive, but are insurers actually doing that?
“What happens is, insurers are looking at three different systems. They’re looking at their CRM system, their policyholder system, and their claim system. Have they considered bringing it all together to where they can actually drive insights across the value chain and across the customer journey? I don’t think we’re quite there yet. There’s still a bit of risk aversion, in my opinion, around getting on the [data] bandwagon, and I think that’s something that needs to accelerate.”
