Managing opportunity and spreading awareness of big data capabilities are critical tasks for successful data management leaders, according to a panel of insurance technology executives speaking at the IDMA 2014 Annual Meeting and Seminar in Philadelphia this week.

The case for big data is self-evident and especially telling for the insurance industry, said Heather Wilson, chief data officer at AIG. “When you look at retail or telco industries, they are constantly checking touch points for online shopping,” she said. “[In insurance] you might touch your customer once or twice in a year through a premium or through a portal if there is a claim. There is no industry better suited for big data than insurance.”

Also see 10 Big Data Companies You Might Not Know

For Wilson and others, investment and commitment to big data opportunities are table stakes for surviving modern risk markets. As opposed to single bets, it’s a process of balancing obligations and customer interests in an aggressively competitive way.

“What’s really exciting now with the explosion of data and evolutions of technology is how we can effectively leverage and explore the massive amount of data that we have and capture internally, structured and unstructured, along with the sea of third-party data out there, said Erik Roen, VP claim business intelligence & analytics, Travelers. For Roen, it’s a considerable upgrade of the old workforce/process/technology orientation to a more real-time view of operations.

A piece of his role has been to inform the broader community of what was not attainable in the past. One powerful vein of knowledge at Travelers is now being delivered in the form of unstructured claim notes entered by adjusters that previously fell outside any cumulative knowledge base. “Our adjusters love unstructured claim notes that were very difficult for us to mine, but now we have 500 million entries in big data environments with really great search and metadata tags,” Roen says. “That allows our folks to mine that information in milliseconds. It lets our scientists leverage that in predictive models, and that is something we didn’t even think possible some years ago.”

Also see Adoption of Predictive Models Increasing Among P&C Insurers 

In a similar vein, web analytics support multiple constituents including the data science community, claims, pricing and underwriters. As Travelers begins a direct-to-consumer business, web analytics now support marketing and social media with analytics on about 1.5 billion web advertisements posted per month.

It tells Roen and Travelers where visitors arrive from and how far they follow or when they abandon the process. “We’re looking at web impressions in numbers that are incredibly big now on an almost real-time basis,” Roen says. “We’re planning based on some of that feedback, which is something we didn’t have a couple of years ago.”

Jorge Rosas, VP of operational analytics, Field Operations Services Division at Chubb said his company’s interest is most driven by the need to understand why customers are contacting the company, understanding the drivers and communicating the results to management.

“When big data comes up for operations it’s our opportunity to look at thousands and thousands of transactions and talk [internally] about how much a transaction is costing me in a predictive model about the cost of success or non-success,” Rosas said. “Management didn’t have that before, it was more seat of the pants.”

AIG’s Wilson calls herself a “data dealer” and views here role as one of managing risk through data and information. “We make a promise with a policy when you come forward with a claim. But we’re about safety and soundness,” she said. “To use that data, to mine it, to look at what risk out there for a commercial or individual client is all about what could happen and what the drivers are that could make a risk realized. Those are things we are trying to figure out to help our clients.”

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