Key benefits of Claims Process Automation for Insurance Providers

Advanced intelligent document processing platforms employ artificial intelligence technologies including natural language processing, machine learning and transfer learning. Together, they enable employees who process insurance claims day-to-day to build claims process automation models – without involving data scientists or even IT. That helps deliver a higher level of model accuracy and significant scalability in terms of an insurer’s ability to roll out automation models across the company.

Chief among the areas that are ripe for automated claims processing is the corporate email in-box. It’s common for insurance companies to have a single email address to which clients send claims information. Some use the same address for general information requests, including quotes on new business. Or, customers mistakenly use a generic address to submit a claim.

Many of these emails contain not only potentially complex requests, but attachments, such as ACORD forms, photos showing home or vehicle damage and the like. An intelligent document processing platform can essentially read and triage each email, determining where each should be routed.

The platform can also extract and read attachments, often dealing with them on its own. The Indico Unstructured Data Platform, for example, includes a large library of ACORD forms, often resulting in straight-through processing of the forms. In general, the Indico Data platform can ensure each email is entered to the correct workflow for efficient, automated processing.

No matter how an insurance company receives word of a client claim, it’s sure to come with plenty of documentation. Much of it will be unstructured, making it beyond the scope of a robotic process automation solution.

An intelligent document processing tool, however, can process any type of document, structured or unstructured. In the insurance first notice of loss scenario, that may mean accepting the initial claim (the FNOL), then validating the claim is covered by the client’s policy. Much of that process can be automated with a tool that “reads” the claim form, extracts pertinent data and inputs it to a claims management tool. Here again, STP may apply to simple claims while others can be prepared with all pertinent information already assembled for an adjuster, greatly reducing time spent on the assessment process.

A key concern in a highly regulated industry like insurance is the ability to explain why an automated, AI-based solution makes the decisions it does. If a claim is rejected, the insurance company must be able to explain in simple terms the reason behind that decision. A sound intelligent automation tool will make that easy, with an audit trail that makes clear – in plain English – the rationale behind each claim decision. Additionally, given insurance claims process owners create the automated models, the models naturally reflect the way they think during the claims assessment process.

Automation is crucial for insurance companies if they are to keep up with insuretech startups, or simply compete effectively vs. traditional competitors. It’s also important to helping detect fraud.

More than 7,000 insurance companies collect over $1 trillion in premiums each year, the FBI estimates, making them a prime target for illegal activity. The total cost of insurance fraud exceeds $40 billion per year, the FBI says – and that doesn’t include health insurance. That costs the average U.S. family between $400 and $700 per year in increased premiums.

Automation can help insurance companies do better. To learn more, see our page, “Intelligent Document Processing for Property & Casualty Insurance" or click below for an interactive demo, a free trial or to get in touch with any questions.