The insurance industry has historically been a growing industry, capable of providing satisfactory returns without much concern regarding the impact that data might have on strategic decision making. Technology was not considered a critical factor in decision making. Decisions were often based on conventional wisdom, not on facts derived from the data which was painstakingly stored and then ignored. The realization that data stored in multiple databases within a company can provide a tremendous strategic advantage has compelled many insurers to join the data warehousing wave in an effort to gain market advantage and improved profits.

Building the Data Warehouse

Data warehousing technology allows insurance companies to consolidate information from disparate operational systems into one source for consistent, reliable and accessible information. This gives insurers the opportunity to bring wisdom and insight to the decision-making process.

There are many decisions to be made when building a new system. In the data warehousing arena, the key decision is whether to build a data warehouse, data marts or both. The solution that many insurers are adopting is a top-down approach that starts with a corporate data warehouse containing transaction-level detail. To complete the top-down approach, the insurance analysis applications--the data marts--are then created from the corporate data warehouse.

Many have attempted to skip the corporate data warehouse and jump right into building the insurance analysis applications. In general, those who have built stand-alone data marts have found that this approach does not meet expectations. Stand-alone data marts extract information from the operational databases of different sources or departments, but the data is not necessarily consistent across departments or business units. The end result is often a lack of integration and standardization. Data marts A, B and C may show different revenue and loss ratio results based on the source's specific calculation needs. This lack of standardization will always lead to a sub-optimal decision. The top-down approach, starting with a corporate data warehouse, will provide a standard and consistent basis for decision making.

It is important to build insurance analysis applications that will accurately reflect day-to-day operations. Several data marts are usually needed to provide information to different segments of the company and to allow for an accurate view of the business as a whole. In the insurance industry, there are three key data marts. A SALES AND RETENTION DATA MART allows the user to monitor new business production by class and distribution channels and also provides support for retention analysis and improvement. An EXPERIENCE DATA MART provides information to support risk analysis and pricing, giving the end user the ability to compare premium and loss information over a variety of time periods. A CLAIMS DATA MART provides all the information necessary to manage various aspects of the claim process, thereby improving reserve management and identifying activities which may be fradulent.

Benefits of Information Access

A common question when confronted with the decision to build a data warehouse, especially in a climate of tight profits and increasing costs, is that of the return on investment. While a return cannot be guaranteed, insurance companies can increase the likelihood of experiencing a tremendous rate of return by using a data warehouse to:

Become More Customer-Focused. Through the use of data marts, such as the sales and retention data mart, the organization can shift from a product-centered organization to a customer-focused organization. Detailed customer data has given insurers depth of knowledge about their customer base, enabling them to analyze relationships, spot trends and realize customer preferences. The result is better service for current customers and an increased ability to attract new customers.

The "typical" insurance buyer has vanished. Insurers can no longer count on all customers fitting into one of five segments for which they provide products. Leading insurance providers have discovered there are not just five to ten customer segments, but between fifty and one hundred segments. With the use of data marts and data mining techniques, insurers are taking steps to provide products and services to the most profitable of these segments.

Meet Competition Head On. As more competitors enter the market and globalization of the industry occurs, data warehousing will give the insurer the insight to make decisions which they may have been uncomfortable making before. In addition to identifying lucrative target markets, price setting is one of the most critical decisions an insurer makes. Data warehousing technology allows the company to more easily identify profitable segments and products, track expenses and distinguish trends and customer preferences. As a result, the company can more readily determine the best pricing strategy when new competitors enter the market. It may not always be necessary to reduce prices and jeopardize profits in the face of new competition. Data warehouse applications can provide insurers with the support to make the best pricing decision possible.

By obtaining supplemental information from external databases and combining it with a data warehouse, an insurance company can analyze the potential of new business opportunities, such as overseas markets, and more confidently make strategic decisions regarding new markets. Information such as class characteristics, loss ratios and pricing is critical when penetrating new markets, domestic or abroad. With data warehouse support, entering new markets is no longer a step of blind faith, but a conscious decision based on reliable facts.

Identify Potential Fraudulent Activities. With insurance fraud and abuse on the rise, data warehousing and data mining are providing relief to insurance CEOs. Many insurers now have improved methods of identifying and prioritizing suspect claims for review. A claims data mart provides a complete picture of the claims process. When combined with the previously mentioned external databases, claimant-specific information (such as injury type, previous injuries, payment history, employer and payee information) provides the insight to more readily discriminate between valid and fraudulent claims.

The claims data mart also allows better management of open claims. With the data mart, the claims manager can now match claim characteristics (such as type of injury, extent of disability and treatment associated with injury) with that of previous claims and more accurately estimate the cost associated with that type of claim.

Expense Reduction. With competition rising and pricing pressure increasing, expense control is a high priority among most insurers. By reviewing the cost of sales by segments such as distribution channel, state and line of business, insurers are better equipped to manage costs, thereby reducing the expenses associated with the policy acquisition process.

Insurance companies are successfully justifying their data warehouse investment in terms of increased productivity and lower costs. But it is the strategic benefits--the ability to analyze pricing structures, identify new markets and customer needs, and provide customized and value-added services--that are delivering returns of 1,000 percent or more on the investment to those that have implemented data warehousing and use the information in the most advantageous way. Although the returns are impressive, you won't hear much about them. Few in the insurance industry want to reveal their strategic weapons. One fact, however, has become clear: data warehousing is no longer a competitive advantage--it's a necessity for survival.

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