Insurers handle, on average, more than 100,000 documents every year, which take a huge amount of time and effort to process manually, and are open to human error. Most of them contain unstructured data (which accounts for 80 per cent of data produced globally), meaning the documents don’t follow a predefined or known structure: for example, insurance contracts and policies.
Most document-processing software, even when leveraging AI, cannot process all the possible variations of the content. In addition, natural language approaches based on statistical models will also fail to accurately analyse unstructured documents because the amount of similar content is not high enough to enable generalisation.
One promising approach you may have heard of is intelligent document processing (IDP), which is used to automate data extraction and processing by combining artificial intelligence (AI) and natural language understanding (NLU) with tools such as optical character recognition, thus improving efficiency and margins and reducing cost.
