The insurance industry is full of clichés regarding data: “data rich, information poor,” “data is the lifeline for insurers” and the old favorite “garbage in, garbage out.” Insurance is an industry that relies on solutions to help businesses gain insight into risk, cause of loss and resulting claims. They need to model ways to predict such eventualities. So why aren’t insurers investing heavily in data management?
The problem with most insurance companies is inconsistent, incomplete and inaccurate data that is spread across multiple operational systems, such as policy, claims and billing. These issues are leading insurance executives to make business decisions based on “gut feel” rather than reliable analysis.
Also, it’s not just about the quality of data, it’s also about the quantity of data. In 2005, we generated about 150 billion gigabytes of data. This year, we are expected to create almost 10 times as much and this is just structured data.
To remain competitive an insurer’s data must be clean, available, usable and meaningful – meaning it must be integrated and shared so users can take the right actions and make the right decisions. To address these issues SAS recently launched the SAS Insurance Analytics Architecture solution. A core component of this solution is an insurance specific data model. This comprehensive data dictionary covers all key insurance subject areas such as customer, policy, claim, financial accounting and reinsurance. The predefined logical and physical data models serve as a single version of truth that standardizes more than 5,000 insurance data elements, ensuring consistent terminology and reporting throughout the organization to support key business decisions.
To learn more about this solution read the success story and benefits that UK insurer AEGON gained from implementing SAS Insurance Analytics Architecture.
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