It’s not unusual to hear about optical character recognition (OCR) as a solution for
underwriting automation and claims processing. But by itself, OCR can’t effectively deal with the unstructured data that is the hallmark of insurance documents.
OCR is machine learning technology that can convert documents such as PDFs into a machine-readable format. That’s useful, but it still leaves you dealing with templates to extract pertinent information.
Robotic process automation suffers from much the same problem when it comes to insurance automation use cases RPA is great at automating processes that involve the exact same steps each time. Say, for instance, an insurance data entry clerk entered the exact same keystrokes in the same order time after time into a claims processing system. That would be a process that’s ripe for RPA.
But, as explained above, that’s not at all how insurance processes work. Rather, they require a human being to make judgment calls about which data to extract and enter. Any insurance process that involves unstructured documents – which is most of them – will suffer the same problem. (RPA can, however, complement intelligent intake solutions in insurance process automation.
More on that here.)