Skip to main content Skip to Footer


Reaping the benefits of Analytics: For insurers, six ways to make your business intelligence smarter


Many insurers are still struggling to achieve a 360-degree view of their customers. A primary reason is that senior executives are unaware of the opportunities their business intelligence systems can provide.

Despite their hefty and increasing investments in data warehouses, architectures, analytics and business intelligence (BI) platforms, many insurance companies still are not getting the value they want, and need, from their BI initiatives.

In essence, past business intelligence initiatives in insurance amounted to the status quo: simple spreadsheets.

For insurers to achieve the desired ROI from large BI investments, they will need to tweak their programs to provide the right information to employees quickly and in a format that helps them analyze, evaluate and react to changing market conditions to drive business results.


How is it that carriers, supposedly with better data and systems, are still generating reports that offer little insight and impact on the business? There are three primary reasons:

  • First, the emphasis of BI initiatives was on the technology rather than the real business asset: information. To extract value from their large amounts of customer data, carriers need an integrated and governed approach to improving data quality and conformance.

  • Second, design of the new BI systems replicated the same segmented, isolated reports already being used by department-specific users instead of emphasizing enterprise-wide insight.

  • Third, BI was viewed as an IT project, guided and controlled by IT rather than the enterprise. Without an understanding of what is possible through new BI systems, executives on the business side did not inquire about the reporting, analytics and intelligence potential.


Customer acquisition and retention over the next three years will depend heavily on an insurers’ ability to deliver customized experiences to their different customer segments—an ability that will rely on predictive analytics to convert data into usable insights on customers, agents and markets.

Historically, predictive analytics in insurance has focused on risk segmentation or pricing. However, it has far broader uses for insurers; it can be applied to key operations of the business to optimize performance in every area. For example, predictive analytics can answer key questions in moving from analysis to action, such as:

  • Would a skills-based routing for underwriters make sense, and if so, what does the performance information tell me about how to respond with respect to size, industry, geography, or coverage for a given risk?

  • How do I get the most return from distribution spend? Is there more opportunity with brokers located in cities or in rural areas?

  • Who are the best claim vendors from a customer service and loss perspective for a given loss profile?

  • Which of the litigators are best for a given type of loss or industry?


To gain more insight and value from their BI investments, insurers will need to go further toward the holistic view by taking six key actions:

  • Establish a core set of data most relevant to the entire enterprise

  • Establish core governance to manage values and definitions

  • Start controlled clean-up efforts

  • Rapidly develop tools for business use

  • Embed intelligence into reports

  • Build solutions that offer broad and granular insight.