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  • Megan Macauley

Predictive Analytics Are No Longer a Luxury

QIS Quick Take: As pricing becomes more and more of a science, a new analytical tool helps insurers stay competitive.

About a year ago we introduced InsureWatch 2.0, the most recent result of our 28+ years commitment to helping property & casualty insurers stay profitable. Basically, InsureWatch combines a huge online database with a powerful analysis engine, accessed by a graphical, highly intuitive user interface. Together, these capabilities allow property & casualty insurers to obtain highly accurate competitive pricing information in a fraction of the time formerly required.


With a few clicks of the mouse, users can take single or multiple quotes and modify them to be rated within each ZIP code in a state, developing on-the-fly rate strategies to improve competitive pricing. They can also compare competitors’ rate plans going back more than a decade, and use that information to predict a given competitor’s probable future rate strategy.


Ever since we brought InsureWatch 2.0 into the field, customers have been telling us it was a major step forward in their ability to price accurately and competitively in their product and geographical markets. We’re still hearing that, and it makes us feel great. (Our relationship to our customers is very simple: if they do well, we do well.) Lately, however, we’ve been hearing something else as well. It’s not just that a tool like InsureWatch makes it easier to compete, our customers are telling us. In today’s market, the tool makes it possible to compete.


There’s a real battle for market share, and one of the chief weapons in this battle is high-speed, high-power data analytics. Without predictive analytics, insurers can find themselves overpricing profitable, low-risk coverages (thus losing them to the competition), and underpricing higher-risk coverages. Gradually loss ratios and loss costs increase, leading to a decision to raise rates, leading to acquisition and retention problems.


That’s called adverse selection, and it can lead to a downward spiral for the whole business. What causes it is information inequality: the insurer is unable to identify and price risk as accurately as its competitors. To prevent this—or to reverse it if it’s already started—the insurer needs to supplement its own data with a broader, more stable and more predictive data set. Then to make effective use of that data, they need a presentation and analysis tool that’s easy and fast enough to use to support quick, accurate underwriting decisions.


At Quadrant Information Services, our business is helping P&C insurers become better competitors in a competitive world. Check out what we have to offer—it may surprise you!

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