3 Ways AI Solves the Unstructured Data Problem in Property & Casualty Insurance
July 15, 2021 / artificial intelligence, Insurance, Intelligent Document Processing
From claims processing to underwriting, the property & casualty insurance business is driven by documents, the vast majority of them of the unstructured variety. Companies that find ways to automate processing of property & casualty insurance documents can transform their businesses and get a leg up on the competition, including insuretech startups.
To date insurance companies have largely relied on automation tools based on templates and rules to automate document-intensive processes. But such tools don’t fare well with the unstructured content that dominates the business (a topic covered in this previous post). What’s required is an approach to automation that takes advantage of artificial intelligence technology to enable property & casualty insurance companies to effectively process even unstructured content.
Following are three ways AI can enable intelligent automation and help solve the unstructured document problem in the property & casualty insurance business.
Real AI enables cognitive capabilities
First, an intelligent automation tool, or what Gartner calls “hyperautomation,” can “read” documents much like a human does. They’re based on a database of millions of labeled data points, enough to give the tool context behind most any document. Intelligent automation tools also take advantage of AI technologies including natural language processing, machine learning, and transfer learning, which enables insurers to build models to automate the process of extracting crucial data from virtually any kind of document or image. Essentially, the tool can read, analyze, and understand unstructured documents just like a human does.
Such capabilities are beyond the scope of rule-based engines and templated approaches to automation. They work only with highly structured content and for processes that follow repetitive steps. Once an unstructured document comes along for which there is no template, the automated process comes to a screeching halt.
The rise of the citizen data scientist
With a truly intelligent document processing tool, the employees who understand property & casualty insurance processes best – those who actually perform the processes – are the ones who use the tool to build automation models. These so-called “citizen data scientists” greatly expand the scope of automation efforts because the company no longer has to rely on scarce, expensive data scientists to create automation models.
What’s more, nobody understands the processes better than those who are actually performing them. Having those same people create automation models helps to improve the model accuracy.
Delivering explainable AI
An intelligent process automation tool also makes it easy for companies to understand why the models make the decisions they do, delivering on the concept of “explainable AI.” This is critical for highly regulated companies such as insurance firms, which may have to explain to a regulator why a given client was denied a policy or a claim was rejected. Intelligent automation tools leave an audit trail that makes it simple to answer such questions. And again, the models are built by business process owners, so it’s their own thinking behind them.
Indico clients have had great success automating numerous processes in the property & casualty insurance business, from first notice of loss and claim adjudication to underwriting and servicing. They’ve been able to increase process capacity, grow revenue without adding expense, free up employee time for higher-value work and generally compete more effectively.