New software and consulting offering automates the assessment, monitoring, and analysis of critical insurance claims data to reduce expenses, maximise recovery amounts and improve customer satisfaction
Master Data Management, distributor of Trillium Software, a business of Harte-Hanks and provider of industry-specific data quality solutions, is now delivering Trillium’s new Claims Data Quality solution for property and casualty insurance claims professionals. This new offering leverages Trillium’s deep data quality and insurance claims expertise to help insurance professionals automate the assessment, monitoring and analysis of critical structured data, as well as unstructured data elements with free form text such as in adjuster notes, providing greater insight and visibility into their claims data.
Says Gary Allemann, MD at Master Data Management, “Better quality claims data delivered through automated data quality processes enables more accurate forecasting of loss reserves, better management of allocated expenses, and the identification of missed opportunities for time-sensitive recoverables including subrogation and catastrophe coding. As a result, insurance firms can reduce overarching expenses, maximise 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 utilising 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 maximise 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 unique solution designed to meet the needs of insurance companies. It is a combined software and consulting solution, powered by the Trillium Software System and Master Data Management’s expertise and consulting experience. Insurance companies engage with Master Data Management’s consultants that use a proven data quality methodology to Assess and Quantify (identify data defects) in an automated fashion, deploy and apply insurance-centric business logic to measure impact, and manage and establish business-as-usual processes in order to automate data defect analysis and visualisation. 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 an overall 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.
Adds Allemann, “When insurance claims professionals have to make decisions based on poor quality data, this can lead to adverse department performance due to incorrect assumptions on loss reserves, catastrophe management, subrogation maximisation and litigation control. 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 minimise expenditures while maximising value,
- Subrogation and CAT Recovery – automated identification and remediation of claims for Subrogation and CAT coding to optimise claims recovery amounts and processes.