E-Chat Tomorrow: Insuring the Future With Predictive Analytics


Actuaries use tables to predict risk based upon factors like age and gender for car or health insurance, and ethnicity, income, and community education levels for property insurance.

Predictive analytics lets insurance companies get more granular, analyzing an individual’s account data to determine risk, said Richard Boire, partner at Boire Filler Group, in a phone interview earlier this week.

“What we’ll do is we’ll take [an individual policyholder’s account] and we’ll look at the history,” Boire told us. With predictive analytics, insurance companies can mine historical data on policyholders, looking back 12 months for additional claims or other changes that might result in a different overall risk score.

In the case of property insurance, for example, including riders for building additions or other property alterations usually affects overall risk score, Boire said.

Boire Filler, in Pickering, Ontario, just east of Toronto, builds predictive analytics models for Canadian insurance companies. Its clients can then set individual policy prices based on changing risk factors.

For example, a female driver in her 20s would have a lower risk score and lower insurance rate than a male of the same age. However, the same female driver with three new claims on her auto insurance over the last 12 months would see her risk score climb significantly.

Conversely, a 20-year-old male who would normally see a high risk score based on age and gender might see that drop with a long enough driving history free from any claims. Heck, if this guy also wants property insurance his good driving may earn him points there, too. See this video blog on how one insurance company apparently has found a connection between lousy driving and careless home ownership.

Boire will join us Friday, March 2, for a live e-chat on predictive analytics in insurance pricing at 2 p.m. EST here on AllAnalytics.com. He will answer questions about how to best use data mining tools to detect risk scores for individual policyholders. If you're attending next week's Predictive Analytics World conference, in San Francisco, you can catch him there, too. Boire will be presenting on Monday, March 5.

How might the insurance industry benefit from predictive analytics in your view? Leave your thoughts on the board below, and be sure to join us for the live chat on Friday and feel free to drop some questions in the chat interface before the event to get us started.

Shawn Hessinger, Community Editor

Shawn Hessinger is a community manager, blogger, social media and tech enthusiast, journalist, and entrepreneur based in Northeastern Pennsylvania. He serves as community manager and blogger for BizSugar.com, a business news and information Website, and contributes regularly to the online business news source, Small Business Trends. He is the founder of PostRanger.com, an online content and media community, and has provided blogging and social media services and consulting for companies all over the world. He researches and writes on a variety of business, Internet-related, and other tech topics including business intelligence and analytics. He is also keenly interested in computer-aided data management as it relates to his various online ventures. A newspaper journalist with more than 11 years experience as a reporter and then managing editor, Shawn began blogging in 2006 and now provides a variety of consulting and outsourcing services in Search Engine Optimization, Web development, and online marketing to companies large and small. He is a strong advocate for the use of BI and related computer data management in business decision making, whether using software as a service (SaaS), cloud, or other applications, and in the opportunity these technologies provide to transform small startups and larger established businesses alike.

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Thanks everyone for joining us in today's e-chat!
  • 3/2/2012 11:49:17 PM
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Thanks everyone for joining us in today's e-chat on predictive analytics in the insurance industry and thanks for staying late! You can check out the full archive above and share the link with a friend. Thanks again!

Join us for a live e-chat on predictive analytics in the insurance industry 2 p.m. EST
  • 3/2/2012 12:51:20 PM
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Hope everyone will join us today for our live chat on predictive analytics in insurance pricing at 2 p.m. EST.

predictive analysis for fixing premium
  • 3/2/2012 3:39:46 AM
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1 saves

Predictive analyses are commonly used for credit scoring purposes. Here the accuracy and usability of results greatly depends on level of data analysis and quality of assumptions. This credit scoring has direct impact in fixing the policy premium and in financial services. In most of the cases the lending rates are proportional to the credit history and term risk. When companies are charging more premiums for customers with a bad credit score, others who are having a good credit score are not getting the benefits in same proportion.

I mean such analysis are using only for extracting more from customers based on different risk level and not for passing any benefits to them in return.

Re: Hard to fathom
  • 3/1/2012 5:42:51 PM
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As am I, Beth! As am I. See you at the chat and, of course, on the boards.

Hard to fathom
  • 3/1/2012 3:00:10 PM
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@Shawn, Insurance seems a prime candidate for predictive analytics and I'm looking forward to picking an insider's brain!

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