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David Bassi, an executive director in Ernst & Young’s financial services organization, focuses on insurance data and analytics. He has more than 20 years’ experience in the industry, including management positions at AIG, Plymouth Rock Assurance and Swiss Re. At Digital Insurance’s Dig|In event earlier this month, Bassi moderated a panel titled “Analytics and Innovation: A Symbiotic Relationship.” After the session, he sat down for an interview with editorial director John McCormick. An edited version of their conversation follows.

Digital Insurance: Your panel focused on how analytics can be a platform for innovation. Tell us how?

David Bassi, EY: Analytics is the foundation for a lot of recent innovation. Insurers are using chatbots to quickly answer questions that come into call centers. They’re leveraging Internet-of-Things devices to create new customer experiences. With these new applications, there’s a huge analytics base that’s needed to make those things possible.

Continuing with chatbots – the application has to be able to identify what a person’s asking, what they’re interested in and what they want to know. It has to know the context of the query. To answer the customer’s questions, it takes a huge amount of analytical power. Same thing with IoT. Think about smart home products: An insurer might want to provide a discount to people who are putting in water sensors. But there’s a huge amount of analytics needed to determine if the water sensor is picking up a leak or if someone is just taking a long shower.

DI: Where are insurers good at using analytics for innovation and where are they not?

Bassi: I think insurers are learning in many cases. Think about what some of the consumer-goods companies are doing in terms of interfacing with customers and around the customer experience. They’re gaining an understanding of what people’s preferences are and how they can create products and services in response. There are probably some things insurers can learn from them.

Among the things insurers are doing pretty well is understanding the implications of the data exhaust that’s coming out of things like IoT devices -- where the data can be central to understanding risk.

Digital Insurance: The amount of data coming in from IoT devices is incredible. Are insurers capable of really digesting all this information?

Bassi: They are capable. It will take investment in infrastructure. Now, the good thing is, they don’t need to directly ingest those streams of very “green” [unstructured] data. They can partner with companies that are creating those devices and processing IoT analytics to identify the events that are really important.

A good example is telematics. Devices in cars are capturing thousands of data points in very rapid succession. I don’t know many insurers that are actually ingesting that raw stream. Instead, insurers work with companies that can isolate events like hard braking, hard cornering, hard acceleration, high speeds. That information comes from the data stream but is used in sort of a derivative form when it gets to the insurance company.

That’s probably the model we’ll see in the short term. Again, talking about a water sensor, there are data points that signal an event is likely to happen. It knows that when water is flowing out at a very rapid rate for too long, it’s probably a leak. So the insurer just needs to isolate events. It doesn’t actually have to deal with the entire data stream.

Digital Insurance: We’re talking about all this IoT data. There’s a ton of information coming from people’s cars and their homes. How big of a concern is data privacy for consumers and insurers?

Bassi: The people I’m talking to in the insurance industry are very concerned about appropriate uses and data privacy. And, because of that, I don’t think we’re seeing a lot of uses of data that people would consider inappropriate. In fact, you see lots of customer benefits. You see people’s willingness to trade off -- sharing information for convenience. Of course, the customer has to be confident that there’s a reasonable level of security. They have to be confident that people aren’t going to use their data inappropriately.

Digital Insurance: So there’s a lots of innovation happening. But will traditional carriers be able to find the talent, like data scientists, that they need to keep innovating? We keep hearing that the best and the brightest are being lured away to Silicon Valley.

Bassi: I have a contrary view on that. I actually think, presented in the right away, the analytics problems insurers are solving are fascinating for most data scientists. The problem is that the insurance industry isn’t framing the opportunities particularly well.

Two years ago, if you started talking about innovation and talking about the symbiotic relationship between innovation and analytics, people might’ve scratched their heads a little bit. I still show up in meetings where the analytics people don’t look like, don’t talk like and don’t really interact particularly well with the innovation people. As insurance companies break down the barriers things will get really exciting.

Some insurers, such as the ones on my panel -- AIG was represented by Rob Bauer, who heads the innovation and sharing economy practice group; Assurant was represented by Barb Bufkin, executive head of business development; and MetLife was represented by Peter Chiang, VP of global digital strategy and transformation -- have really identified people who understand how to create value with analytics. Those firms have less trouble attracting the right talent.

Digital Insurance: Obviously, you’re talking about more traditional insurers, but the insurtech companies probably have an easier time finding good people.

Bassi: Interestingly, one of the things a person at an insurtech recently said to me was that when he got into the business he thought the hard part was going to be attracting analytics talent, innovation talent. But he said that wasn’t hard at all. Once he shared his vision with prospective hires, recruiting was easy. What he was having trouble with was attracting the professionals with deep insurance background who wanted to take the risk and make the jump to an insurtech.

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Analytics Predictive analytics Big data Artificial intelligence Machine learning EY