The question about the vast amount of data constantly being created through social networking is not whether but how it can be used by insurers. It's a topic on my mind because I'll be meeting with Max Drucker, CEO, Social Intelligence — a company that screens social media for claim and underwriting purposes — today at the IASA Conference, but also because of the somewhat troubling questions raised by an article in The Economist shared with me by Matt Josefowicz of Novarica this morning.
The article describes how some insurers are trumping other sources of data by information they can glean from social media. They may use this information to decide about whether and how to underwrite policies, or to serve as a substitute for medical examinations or to investigate the validity of claims, among other things.
What I wonder is how insurers will make good use of social media data while not eroding an already poor reputation with the public. The public is all too willing to accept sensational accounts of insurers as dedicated to maximizing their profits by denying claims, by whatever means possible, as a June 4 article related to CSC's (Falls Church, Va.) Colossus system shows.
[For more on insurers' controversial use of social networking data see Insurers Push Boundaries of Social Media Use in Claims, Underwriting .]
More data in the interest of accuracy, transparency and fairness is a good thing, but the public doesn't understand how much of a problem insurance fraud is and is likely to misunderstand insurers use of social networking data. On the other hand, maybe they'll understand that use in ways that insurers may themselves be likely to overlook, owing to a focus on data gathering at the expense of consumer trust. As The Economist piece's author writes:
Insurers’ interest in data mining will only grow, says Kevin Pledge, the boss of Insight Decision Solutions, an underwriting-technology consultancy based near Toronto. He has investors interested in a project to develop software to comb Facebook and Twitter for promising sales leads: a woman proud of her pregnancy might want to buy life insurance, for example. Insurance firms will also analyse grocery purchases for clues about policyholders, he predicts. But that raises some sticky questions about privacy. Mr Pledge himself has begun to forgo his supermarket loyalty-card discount on junk food and pay for his burgers in cash. Promising as data mining is, much will depend on how regulators, and consumers, react.