Increasingly, insurance-related analytics is moving from the purely analytic to real-time operational for leading insurance organizations and new-comers to the industry. The impacted areas range from from prospecting and conversion to claims handling including fraud management. And the anticipated results are impressive.
Analytics for Fun and Prospects (Is That A Zebra In My Quote?)
On January 31, 2013, Insurance Zebra – a new entrant to the US comparison quoting space – issued a press release indicating that it had secured US$1.5 million seed financing for its initiative. One of the financiers is Mark Cuban, high profile investor, owner of the NBA Dallas Mavericks, and guest on Shark Tank (the US version of Dragon’s Den).
The release notes that “Insurance companies will spend nearly $6B in 2013 to win new business from their competitors.” It quotes Cuban saying, “The insurance industry is ripe for disruption, and Insurance Zebra has a great opportunity to lead the charge. I’m excited to be part of it.”
How will it do that? In an article on TechCruch, Sarah Perez indicates that the company founder and CEO, Adam Lyons, has developed an analytics based ‘secret sauce’ which will simplify the quotation process, and allow completion of the transaction on-line. Perez writes:
“With the technology Insurance Zebra has developed, the idea is to not only offer real-time quotes via a one-stop shop experience, but also help users visualize how rates change as they step through the online form….
“The company uses public state filing data as well as data from insurance agencies to help better predict rates. It then combines that data with its own proprietary technology – and a little machine learning and A.I. – to arrival at the quote. When the consumer is ready to buy, Insurance Zebra then facilitates that transaction right on its own website.”
Lyons tells Perez that there are 10 major insurers on board with the scheme now and that the company has a pilot programme underway in Pennsylvania, which will expand over the next few months.
Finding Fraud Buried in Text
According to James Ruotolo, principal for insurance fraud solutions at SAS, writing in Insurance&Technology, current analytic models are being used to identify fraud now, but these may be just the tip of the iceberg. The next generation of tools – which include text analytics – may yield substantially greater results.
Ruotolo cites data from US Coalition Against Insurance Fraud which indicate that insurers recognize that much of the real value points for fraud detection are found in unstructured text internally (adjuster notes, e.g.), and externally (social media). However, only 40% of insurers surveyed are using text mining now. The good news, however, is that “many insurers say they plan to invest further in technology in the future.”
Do You Know More? Do You Want to Know More?
It is clear that analytics use in insurance is moving quickly from the actuaries’ desks to the front lines. We’d be interested in examples you have about operational analytics you’re aware of.
If you’re looking to find out more about analytics, the 2013 Insurance-Canada.ca Technology Conference, at the Toronto Downtown Sheraton Centre is the place to be on March 18-19. There is a full day stream devoted to Leveraging Data and Analytics.