Though insurers have shed a historical aversion to claims technology adoption, a new report from TowerGroup entitled "Technology Direction in U.S. P&C Insurance Claims Operations: Transforming a People Business," suggests that many carriers have adopted only rudimentary claims systems and are missing opportunities to differentiate themselves in the marketplace. "Claims administration systems that insurers have purchased and are using strictly for compliance and process aren't enough in today's environment," says Karen Pauli, a senior analyst in TowerGroup's insurance practice and author of the report. "Claims systems have to have much more robust functionality now."
According to Pauli, the events of Sept. 11, 2001, and the passage of Sarbanes-Oxley compelled claims organizations to adopt technology because paper-based systems were ineffective for disaster recovery and compliance. Most claims departments subsequently purchased claims administration systems and eliminated paper files to some degree. Those new systems, however, were often rudimentary and featured only basic capabilities, such as document imaging and a first-notice-of-loss document with electronic entry and routing capabilities, she contends.
Going forward, Pauli expects that predictive analytics will be a key technology for claims operations. By leveraging data to refine practices and quickly respond to market changes, predictive analytics will allow claims organizations to continue to grow and evolve, Pauli writes in her report.
"If you are using predictive analytics and very basic claims come in, such as glass replacement or towing, technology can move those right along to service," Pauli says. "It's competitive advantage through superior customer service."
Predictive analytics and rules-based engines will also help insurers cope with another growing concern: the retirement of baby boomers. At two recent industry events that Pauli attended, claims executives identified employee retirement as a top concern, she relates. "It is a huge issue for claims [organizations]," Pauli explains. "They have to harvest all of that information through rules engines and predictive analytics before those folks leave."