Insurance & Technology is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.


12:15 PM
Matthew Josefowicz, Novarica
Matthew Josefowicz, Novarica
Connect Directly

Insurers Challenged to Adopt Business Intelligence

Success in a challenging market requires that insurers tackle data management deficits and cultural resistance in order to effectively leverage business intelligence capabilities in an era of data abundance.

In Depth: Business Intelligence and Risk. Business intelligence makes insurers more-competitive risk managers. Overcoming Barriers to Integrated Risk Management. Case Study: Great American Unifies Business Intelligence on IBM Cognos Platform.
Many insurers are awash in data, but starving for information. Siloed systems and organizations, incompatible internal data models, and a history of poor reporting capabilities have led what should be one of the most data-driven, insight-based industries in the economy to be one of the most information-blind. But to their credit, many insurers recognize that leveraging their internal data is the key to improving their business, and are investing accordingly.

Business intelligence is one of the most common areas of new IT projects for insurers. In a recent Novarica survey, 43% of P&C insurers and 20% of L&A insurers listed business intelligence as one of their top three areas of investment for 2009.

The term "business intelligence" covers a broad range of practices, disciplines and technology configurations that relate to the storage, retrieval and analysis of structured data. At its most simple, business intelligence involves a database and a way to report on the contents of that database, or a "repository" and a "reporting tool." A repository could be the data storage component of a production system such as a claims system or policy administration system, or it could be a stand-alone data repository. Repositories can be either asynchronous (e.g., data warehouses and data marts), where data is stored for later analysis or retrieval, or synchronous (stand-alone operational data stores, or operational data stores contained within production systems), used to provide real-time data for transactional systems. Reporting tools include both analytic engines that perform data analysis and presentation layers that present the results of the analysis to a user or analyst.

Novarica's recent survey on business intelligence found that insurers still have work to do in this area:

  • Only about half of participating insurers currently had excellent or acceptable business intelligence capabilities in place, according to their own estimates.
  • Only about one-third reported significant business impact from their business intelligence investments, but roughly an additional third expected impact over the next 12 months.
  • Underwriting and new business lagged other areas (especially financials) in leveraging the value of business intelligence.

The study also found that the two greatest impediments to leveraging business intelligence to create value are the lack of data models and the difficulty of changing business user behavior based on analytics.

Inconsistent Enterprise Data

Inconsistent enterprise data is a bane to insurers across many areas, from effective STP to business intelligence. Without an enterprise standard to map to, insurers can't be sure that their analyses are valid. But with many insurers operating from an environment that mixes legacy systems of various vintages and companies of origin, data consistency is a major challenge.

User Resistance

However, it is the other challenge - changing user behavior - that is even more critical to overcome. An insurer can have the best data analysis in the world, but if it does not have the organizational incentives to use the insights of that analysis to change strategy and tactics, no business value will be created. Since insurance is largely still an "apprenticeship" business in which long-serving, highly knowledgeable staff have deeply entrenched beliefs and practices, changing behavior based on data analysis is often easier said than done. This "cultural" difficulty must be addressed at the same time as the technical difficulties.

Business intelligence is more important than ever because insurers are moving from an era of data scarcity to one of data abundance, and they need to adapt their mind-set and practices to their new environment. Insurers' internal data has grown at a dizzying pace, creating serious challenges in data quality and accessibility. At the same time the quality and quantity of external data, both individual and aggregate, has grown dramatically and is more available than ever. New analytic and processing capabilities have also arisen to enable insurers to build better models for risk analysis and pricing, and to streamline the underwriting process by accessing third-party data in real time. Insurers that can get control over their own data, marry it with broader external data sets to find the hidden gems, and incorporate those external data flows into a streamlined underwriting process will have a significant strategic advantage over their peers.

Investment Imperative

While the accessibility of external data and analytic capabilities are increasing rapidly, insurers' internal data quality is increasing much more slowly on average. Insurers need to continue to invest in business intelligence in order to close this gap.

The challenges of normalizing enterprise data and motivating business user change are significant, but insurers that do develop strong business intelligence capabilities and act upon the insights revealed will carry a sizable competitive advantage in the difficult market ahead.

Matthew Josefowicz is the director of the insurance practice at Novarica ( This article draws from two recent reports: "Business Intelligence in Insurance: State of Play and Expectations for the Future"; and "How New Data Sources and Predictive Analytics Are Changing Insurance Underwriting"

Register for Insurance & Technology Newsletters