Insurance Industry Decision Support: Data Marts, OLAP and Predictive Analytics

Motivation: Data Warehouses and Data Marts increase the power and efficiency of an Insurance company’s Business Intelligence capabilities by supporting queries, OLAP and data mining. Web-enabling of these applications makes them more user-friendly. The potential benefits greatly outweigh the costs. Data warehouse/data mart implementation streamlines information delivery for decision support and significantly simplifies development of general linear predictive models that have become more popular with actuaries and statisticians in recent years.

Method: A data mart and OLAP system was implemented for a major property and casualty insurance company.

Results: Successful implementation substantially improved the insurer’s operational efficiency, providing enhanced analytical and reporting capabilities.

Conclusion: Business needs and business strategy must drive decisions about the structure and functionality of the Business Intelligence platform including the data warehouse and the data mart. The data warehouse must be well planned for the organization to realize the expected efficiencies and process improvement. However, even with a well-designed data warehouse and up-to-date software tools for data access and analysis, it is critical that the enterprise build and maintain its analytical expertise. Therefore, actuaries play a critical role in maximizing of benefits that these new tools can offer.

Keywords: Business intelligence, OLAP, data warehouse, data mart.