Trillium Releases Data Quality Solution for Claims Professionals

Trillium Software, a provider of industry-specific data quality solutions, announces the availability of its new Claims Data Quality solution for property & casualty insurance claims professionals. This offering leverages Trillium's data quality and insurance claims expertise to help insurers automate the assessment, monitoring, and analysis of structured data, as well as unstructured data elements with free-form text such as adjuster notes.

By managing the quality of claims data and automating data quality processes, insurance companies will more accurately forecast loss reserves, manage allocated expenses, and identify missed opportunities for time-sensitive recoverables including subrogation and catastrophe coding. Insurance firms can reduce overarching expenses, maximize recovery, improve overall claims operations efficiency and identify opportunities to grow their business.

"The quality of insurance data related to improperly reserved claims, misclassified expenses or loss reserves deeply impacts business results and decision-making at insurance companies—and keeps claims professionals up at night—especially in light of regulatory and competitive market pressures," says Stephen Applebaum, senior analyst for property & casualty insurance at Aite Group. "By utilizing a solution such as Claims Data Quality, claims professionals can create more visibility into their data in order to more effectively accomplish insurance operations processes that could potentially maximize recovery, improve operational efficiency and increase customer satisfaction. Moreover, the higher the quality of data used to drive the many business analytics programs being adopted, the more valuable will be their output."

Claims Data Quality is a combined software and consulting solution, powered by the Trillium Software System, a data quality software platform. Insurance companies engage with Trillium Software consultants using a data quality methodology to assess and quantify data defects in an automated fashion; deploy and apply insurance-centric business logic to measure impact; and manage and establish business processes in order to automate data defect analysis and visualization.

Trillium also can create the business logic and measurement processes to correct data and monitor progress towards defined objectives, and implement ongoing data quality processes to prevent future data problems.

Clients receive a data assessment that reviews all current claims data across repositories, systems, and processes to identify areas that need improvement. This includes an examination of structured data contained in fields and unstructured data from claims adjuster notes and other sources. Resulting analysis, reporting and data assessment information can be delivered in any requested user interface or format—from business intelligence dashboards and scorecards to spreadsheets and files.

"Insurance claims professionals are making decisions based on poor quality data, which can lead to adverse department performance due to incorrect assumptions on loss reserves, catastrophe management, subrogation maximization and litigation controls," says Michael Chochrek, insurance solutions principal consultant, Harte-Hanks Trillium Software. "Our answer to these data quality challenges is based on deep insurance claims subject matter expertise, world-class data quality assessment capabilities and a proven data quality methodology to help claims professionals understand and solve their data issues."

The solution helps address a number of uniquely-claims-based data problems such as:

• Loss Reserves: proactive, automated identification of potentially inaccurate loss reserves in order to adjust reserves in a timely and accurate manner to match the true claims exposure and mitigate costly manual remediation processes;
• Allocated Expenses: automating identification and matching of case files to specific claims activities to minimize expenditures while maximizing value,
• Subrogation and CAT Recovery: automated identification and remediation of claims for subrogation and CAT coding to optimize claims recovery amounts and processes.