In Few Years, Social Network Data May Be Used in Underwriting

The insurance industry is paying increasing attention to what people and businesses post on social networking sites like Facebook, Twitter and LinkedIn.

Already, scouring Facebook and other social network pages of the insureds is a common practice on the claims side of the business. Many investigators say it’s one of the first things they do when looking into potentially fraudulent claims, including both hard fraud (staging auto accidents, etc.) and soft fraud. (over-reporting damaged values after a fire, etc.)

Currently, social network data are being used as sources of evidence in courts of law in claims cases. Individual underwriters are retrieving risk evaluation information on their insureds through manual searches on social sites.

But in a few years, automatically mined data from social networking sites could find their way into the underwriting pricing process. It could become a factor in determining premiums for both personal and business insurance, according to a new report from Boston-based research firm Celent. The report, titled “Using Social Data in Claims and Underwriting,” was published on Oct. 10.

Right now, most insurers are using social medium for sales and advertising, Michael Fitzgerald, Celent senior analyst and co-author of the report, told Insurance Journal. “Some are using it in claims. Underwriting is next.”

State regulators have not yet offered official guidelines in terms of overall use of social data. And such data are not yet approved for use in the pricing process, Fitzgerald added. But that could soon change.

“Just as insurers recognize a link between credit health and risk in auto insurance, social data may offer similar insights for insurers who set out to crack the data,” the report stated.

As users interact with multiple social networking sites, purchase items online, and communicate with others in public forums, they leave behind data about their preferences, lifestyle, operations and habits, according to the Celent report. This data can be used to develop a risk profile for an individual or for a company. On the corporate side, companies postings also include descriptions of new product offerings (hence new added risks), services and operations.

Another piece of useful information is the “social graph,” which shows how individuals or companies are linked together: a picture of who is friends with whom, who follows whom, and what friends of friends people have. In addition to identifying fraud organizations, these graphs can give insurers further insight into how an individual may perform as a risk, based on the behavior of those he or she is connected to.

Such a profile can be used to build a real-time risk profile that can be integrated into an insurer’s existing process and automation environment. They can be compared to any previous risk information about that entity to identify material changes that should be addressed from an underwriting perspective. The data can also be used to develop conclusions as to the attractiveness of a risk at renewal or at policy lapse.

Use of social data is still in its formative stages, but it’s developing rapidly. Celent predicts that over the next three years, social data will be “incorporated into core underwriting and claims processes” and become standard inputs into risk evaluation and settlement activities.

Celent contends that social data has the potential to join existing third party data sources such as CLUE (Comprehensive Loss Underwriting Exchange), motor vehicle reports, and MIB fraud reports to enable more accurate underwriting evaluation/pricing and lower claims costs.

Pew Research Center shows that as of April 2010, social networking sites are used by over 40 percent of U.S. Internet users. The young are still the dominant users (77 percent of U.S. Internet users in the 18-29 age group use social networks). But those in the older age group of 30 to 49 are also using social sites in big numbers (55 percent of Internet users in this group now use social networks). In the 50-plus age group, 23 percent of Internet users utilize social sites and the numbers are increasing.

This expansion into additional age groups is meaningful, the Celent report said, since many people in older groups are the target market for many lines of business including high net worth personal lines, life and annuities, and small commercial. And while online, boomer age groups perform commercially focused tasks that should also draw attention from insurers.

The report says claims professionals have been learning how to link relationships on social sites to gain information on profiles which use the highest privacy settings. Investigators report that “People always have friends of friends willing to ‘accept’ a new ‘friend,’ and that friend’s privacy settings aren’t always set, allowing us to access pictures and the ‘private’ claimant/insured’s comments indirectly, detailing events they attend, groups they’re associated with, etc.”

While bypassing certain privacy settings is technically possible, it also raises a different question: what is ethically or legally allowed when mining social networking sites, and to what extent should they be used for insurance purposes?

Celent suggests one way to deal with this issue is engaging with customers, seeking permission to use their social data, and then automatically gathering it. Depending on regulatory rules, insurers could offer customers discounts as an incentive.

There are plenty of hurdles. Companies need to develop more sophisticated authentication methods, (Is that the same John Smith who may be filing a fraudulent workers’ comp claim?) improved data extraction tools, and more advanced analysis techniques. The challenge for underwriting organizations is to develop methods and procedures for collecting, sifting, analyzing, and incorporating social data information into their existing system environments, the report said.

The report said there are untapped analysis opportunities in tapping into recent advances in actuarial science, predictive modeling, and tools to analyze social data and to discover and leverage “hidden relationships in social data.”