During a panel at the 2022 Underwriting Innovation conference—the “only USA event dedicated to technology and innovation for underwriters”—OZ President of Global Insurance Practice Mark Smith spoke on the past, present, and future of third-party data integration.
We’ve condensed and expanded this illuminating presentation into the three points below…
1. Be Here Now
There is a lot more data available out in the market today than ten years ago. On one hand, you can get glimpses through insurtechs at how powerful that can be—the two-question quote. But in other, very important ways, I don’t think that as an industry we’re moving as quickly as we need to be to digitize that data, automate the current underwriting process, or utilize a lot of the other third-party data that is going to offer us the deeper insights that we need for new product development.
We want to say, Yes. The key questions are: How often do we say “Yes” to what we shouldn’t say “Yes” to? And, on the flip side, how often do we say “No” to what we should say “Yes” to? The right data and insights can help us get to a much better place when answering both of those questions.
2. Make a Legacy of Change
Two key issues need to be addressed for us to effectively harness and channel the power of all this data.
First, you must transform legacy systems from an implicit argument for stasis into a part of an evolving solution. Legacy systems are, I would say, more of an excuse versus an impediment because I think with our microservices architecture capabilities today you can—with the right integration expertise and services—make those systems work. And that opens up a world of possibilities.
The second issue is change management. To effectively implement any new processes or SOPs you need to nurture an open environment in which a single source of truth can be established—i.e., the foundation for an ecosystem-wide buy-in that is the prerequisite for success.
So, once the data is gathered, you provide it to the underwriter in a digitized fashion so they can understand it and, just as importantly, trust it. I’ve seen many companies invest in hundreds of data scientists who all did amazing work, but, in the end, nothing ever got implemented in production. Nobody trusted the data. Nobody trusted the analytics. We can build that trust with technology.
3. The Path to “Yes”
If you talk to most underwriters, they’ll say forty percent of their time is devoted to getting the data…pulling the data…finding the data…reading through the document…finding information they’re looking for. Maybe they get online and look at a review of the restaurant to see if they’ve got locks in the back or if it’s really a bar or whatever.
Generally speaking, though, a lot of underwriting decisions are made with less than the desired data.
Why?
Step one in my mind is to use that data we’re able to scrape off the web—which is almost all of it—to make the current underwriting process more efficient. We can automate better decisions.
Then we can move on to securing additional data that will provide actionable insights.
You have some insurtechs out there that are already providing a crime score, right? Or a weather score. You know, one billion in lightning strike claims; a couple billion in hail. How do we account for those things when we’re assessing the list? I can, for example, understand any prior claims, whether with me or a prior insurer. But what insights are out there that might inform other coverages? Insurtechs are already doing it. The industry should be watching that space to glean and incorporate the best ideas.
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