Processing an insurance claim appears, on the surface, to be an orderly, linear process. First a claim is investigated, then it’s evaluated, and lastly, it’s settled. Despite this apparently orderly sequence there’s often room for errors that result in claims leakage and significant losses for the insurer in terms of time, money, and impact on their reputation.
A combination of factors including human error, inconsistent processes, and siloed technologies result in claims leakage which “costs carriers over $30B annually, and accounts for 5% to 10% of all claims paid,” explained Frank Rocha of FinServ. Knowing this, what is it that insurers can do to address the problem without a massive time and resource-intensive effort? The answer lies in the use of new and advanced technologies including data and text analytics tools and customizable rules engines.
Thanks to these transformative digital technologies, claims leakage can be substantially reduced. According to a whitepaper by Cognizant, “paradoxically, emerging digital technology can restore the focus on human-centered, successful outcomes — and prevent leakage errors. Digital [technologies including big data analytics, text analytics, and customizable rules engines] are already helping claims organizations quickly evaluate new solutions’ benefits. Now it’s opening a real-time window into claims files.”
Using these capabilities, the analysis of in-process claims becomes more strategic, technical, and specialized. Where manual processes fall short, these new platforms enable the analysis of large data sets to be scanned for patterns and trends which include human error. Similar to big data analytics, text analytics allows for the search and extraction of words and phrases to identify issues and assess progress. Text analytics also burrows through unstructured data that, when digitized, is converted to structured (searchable) data. Lastly, through customizable rules engines, carriers can audit any condition for which data is available. It’s also important to note that rules engines work separately from a system’s core application code. Thanks to this, rules can be written and changed without needing IT skill sets to do the work.
By using data analytics, text analytics, and customizable rules engines, insurers are better equipped to guard against claims leakage. Where the tedious process of filing, evaluating, and settling a claim creates opportunities for mistakes and errors, this new breed of technologies allows for detailed analyses without disruption to other processes or systems. This makes for a quicker and more accurate claims process while lessening risk of claims leakage.