Big Data Land Mines For Insurers To Avoid In 2015

Before data was big, Google was a verb, or Gordon Moore wrote his law, insurers were using math and statistics to predict the future.

As early as the 2nd millennium BC, Babylonian sea merchants paid lenders extra for the promise of help if their ships were to sink. They set prices by correlating data points to calculate the likelihood and potential cost of a disaster at sea. Data was sparse, and one would assume neither merchant nor lender consistently got a good deal.

In 2015, property, casualty, life, and health insurance companies are awash in data. This situation creates the opportunity for both underwriters and policyholders to arrive at increasingly accurate prices using big data analytics. Insurers also can use big data to better win and retain customers, improve operations and enter new markets. But in a dynamic landscape, insurers need to step gingerly around three potential land mines.

Land Mine 1: Customer Relations

While previously policyholders might have felt their insurance company misunderstood their situation and justification for a claim, today insurers can know almost too much. They can spot fraud more quickly by cross-checking dates and locations of reported health clinic visits and flagging claims that prove geographically impossible. They can gather a wide range of insights on customers’ lifestyles, and health trends across their demographic, before pricing life insurance policies. Maybe in the future they’ll re-price your health insurance based on Jawbone feeds to the local doctor’s office.

So big data threatens to change insurers’ reputation from “aloof” to “big brother.” To combat this possibility, they will need to over-communicate privacy policies and empower policyholders wherever possible. Insurers have some wins in this area. 

  • Usage-Based Insurance (UBI) programs, in which car sensors feed individual driving profiles that dictate auto insurance pricing, are gaining popularity. Many parents, commercial fleet managers, and individual drivers are deciding to prioritize safety and cost savings over privacy. Both parties know more about their risks, and the resulting insurance price is more accurate. In addition, concerned parents and fleet operators are better able to reduce their risk.
  • Virtual Privacy Expert is an online privacy Web service developed by ID Experts and Enquiron that insurance providers can deliver to their corporate customers alongside cyber-insurance. Companies can use Virtual Privacy Expert to assess their security posture and configure their own privacy and security policies and an incident response plan. Both parties know more about the risk, leading to a better price, and policyholders are empowered to reduce that risk.

In both these cases insurers use big data analytics to generate new revenue, improve retention, and reduce risks for their customers. They play the role of trusted partner, rather than of Big Brother.

Land Mine 2: Data Sources

Conventional actuarial tables have long fed insurance policy features and pricing. Insurance companies have aggressively adopted new analytical technologies in order to cast a wider data net, sharpen their operations, and build new offerings. They are one of the heaviest users of Hadoop, as attested by Hortonworks, which touts the ability of its platform to capture, cost-effectively, 100% of geospatial data feeds on policyholder automobiles, in order to support the UBI use case described above.

The key also is to embrace unstructured data from less conventional sources such as social media. Platforms such as Twitter and Facebook can help with fraud detection, as well as sentiment/event tracking that can prove critical in the event of a major disaster. With the next Hurricane Katrina, insurers will need to track social forums to proactively locate and address its most heavily affected customers.

“If one word could sum up the focus of insurers in 2015, it is ‘technology,'” writes Shaun Crawford, global insurance leader for Ernst & Young in the company’s 2015 Global Insurance Outlook. “Across all regions, insurers are capitalizing on data analytics, cloud computing, and modeling techniques to sharpen their market segmentation strategies, reduce claims fraud, and strengthen underwriting and risk management.”

Land Mine 3:  Don’t Assume You Can Do It All In-house

Black Swan incidents, which Nassim Nicholas Taleb describes as rare and unpredictable events that produce extreme effects, have thrown insurance companies into disarray at key points since the turn of the century. Witness 9-11, Hurricane Katrina, and the implosion of house prices across the globe that fed the Great Recession. Because the events are so rare and so damaging, their risk is extremely difficult to price.

Another looming event is climate change and the likely symptoms we already are seeing in the form of extreme weather. Assessing the impact on property and health risks requires new and evolving data and analytic techniques. CSC offers a ClimatEdge for General Insurance service that helps insurers quantify catastrophic weather risk as they build and price their policies. As our world continues to change, the 20th century rule book no longer applies, and outside expertise can help.

Big data creates compelling opportunities and new risks for the insurance industry. Early indications show they understand the challenges and are preparing to meet them.

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