Insurance Analytics Provide Accessibility and Reliability to Claim Metrics

Claims management analytics insight #5

Montreal, QC (Jan. 13, 2016) – Information-savvy claim managers need self-service capabilities when working with analytics. They expect to operate autonomously from the rest of the organization and they don’t want to rely on third parties every time they need to gather and view information. They also expect the information they drill into to be up-to-date, accurate, and reliable.

To meet the desire to operate autonomously, the data needed to review operations should be readily available in a dedicated environment that claim managers can treat as their own. They should have an analytical “sand-box” that is conceived exclusively for auto claims management purposes.

Providing claim managers with self-service capabilities requires that the solution is automatically refreshed at regular intervals, and without the need for manual intervention. If the claim managers need to make data refresh request of others, a crucial element of independence is lost. Some claims management responsibilities will need fresh data monthly, weekly, or even daily. The analytics solution should be as current and up-to-date as required by the business rules and strategic imperatives.

Claim Managers also want to base their decisions on information they know they can trust. Thus an insurance analytics solution should first and foremost deliver information a claims manager can trust. This implies that different strategies and processes should be implemented to ensure the integrity and completeness of the data, as it is gathered from various sources, integrated, and delivered as information through the claims management analytics solution.

To achieve this aim, the underlying processes must integrate and embody the following characteristics:

  • Relevance. All required data elements can come from an insurance company’s operational systems, its BI environment, and external feeds such as Body Shop Management Systems like Mitchell, CCC, ADP, or Audatex.
  • Standardized. All data should pass through a Generic Data Interface (GDI). The GDI serves as the “contractual” layer between the Insurer’s IT environment and the analytics solution itself;
  • Optimized and Abstracted. Information should be accessed through an Analytical Abstraction Layer (AAL). The AAL allows claim managers to access information and answer analytical questions using toolsets with which they are already familiar.

To tie accessibility and reliability together, Claim Managers should be able to leverage familiar analytical toolsets that are also the most efficient tools for the task at hand, minimizing the need for additional investments in time, money, and effort. Claim Managers expect up-to-date, accurate analytics to be available at their fingertips. Definitely, these things are not too much to ask.

About InEdge

InEdge is a leader in Insurance Analytics solutions. Experienced at quickly leveraging data, InEdge seamlessly and powerfully creates business advantage for its clients. Since its creation in 1994, InEdge has designed and implemented some of the most sophisticated analytical applications available today. Our clients add up to an impressive roster of Property & Casualty and Life Insurance companies. Our Analytics solutions improve and make easier decision-making at all levels for our clients. For more information, visit

Source: InEdge

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