Intelligent document processing with AI in the insurance Industry
Introduction
The insurance industry consists of many different companies: from small independent brokers and agents to international insurers and reinsurers. With so many different players covering so many diverse risks, it isn’t hard to imagine that this requires large amounts of documentation to go around, both in communications with the end consumer as well as between insurance players.
While we can find some standardisation of documentation in a few lines of businesses or between certain players, this isn’t the case for most of the industry. This means that almost all insurance players have to deal with the processing of a lot of incoming data flows, often from different channels.
The processing of both structured and unstructured documents is a core activity of every insurance player. From onboarding and underwriting to quoting, claims reporting, claims handling and policy renewals, there is a constant flow of communication between an insurance company, brokers and customers that involves countless documents.
Claims processing alone is an intricate process, often requiring a whole infrastructure of staffing, layed out processes and even a supporting IT system. Furthermore, human talent is one of the most valuable resources of an insurance company. Letting employees waste their time on the manual task of processing documents is therefore far from ideal. It’s no surprise that automating this process could result in many benefits for an insurance company.
Automating document processing
To understand how companies try to automate this process we have to understand how this flow of documents works. First we see an inflow of documents at the front end side. These could be e-mails, paper documents etc. They will then often be digitised using scanners or even OCR (Optical Character Recognition) so they can be easily stored or used for further processing. The next step is often the manual work of interpreting these unstructured documents so they can be transferred to the relevant business unit.
One way many insurance companies have tried to solve this is by using structured data, often realised by using (digital) forms and standardised documentation. By using standardised documents they can use rule-based solutions to automatically extract information from these documents and automate their processing. However, not all documentation can be standardised and important nuances can be lost. Furthermore, when forms need updating this means the updating of the whole rule-based solution, making this a costly endeavour. This means this solution is often only viable for just a part of a company's documentation.
Intelligent Document processing and AI
The rise of innovation and digitalisation within the insurance industry has also given rise to a solution to the document problem; Intelligent document processing (IDP). In short, IDP solutions transform unstructured information into usable data. This enables companies to automate this complex document processing and immediately distribute data to the right people. Paperbox is one of these IDP solutions, tailor-made for insurance companies.
IDP often uses multiple technologies such as OCR, Natural language processing (NLP), Computer Vision and machine learning (ML). OCR, NLP and computer vision enables these solutions to “read” unstructured documents and feed this into Machine learning models. These ML-models are then able to classify every document, differentiating a claim from a policy renewal. They will then extract all relevant information from the document and forward it within an insurance companies internal systems
The process here is now different from what we’ve seen before. Instead of a human process, the processing of these documents is now performed by this IDP solution. In Paperbox’ case we’ve made an intuitive UI for employees to process documents that the model does not have enough confidence to process automatically. So the “human in the loop” only gets triggered when the model asks for it. This way an IDP solution can also optimise the parts that it can’t automate and be a true Invisible helper to your employees.
Machine learning is very different from more rule-based solutions. In essence these models learn by “themself”, by means of examples. This has many benefits; first of all: scalability. IDP solutions don’t need to be re-made every time it is used in a different company using different documents as it learns from a specific company itself, often making it more affordable. Secondly, the model gets improved automatically, even after it went into production and is actively being used. So when there are changes in documentation the model will update itself and there is minimal need for manual updating.
Why IDP is essential to stay competitive
The first obvious benefit from using an IDP solution is the improvement of operational efficiency. An insurance company just needs to count the man hours spent on document processing that can be negated by an IDP solution and a business case is easily made. While this is the most straightforward way to calculate the benefits of such a system, there is much more value to be gained than just the cost savings.
Good customer service is often a very important goal of insurance players, this could even be an insurance player's most important differentiator from the competition. Backlog in documentation of claims could be detrimental to total lead time and could leave dissatisfied customers. IDP could guarantee a fast processing of client documents and can more easily handle peak times as it is much more scalable than human processing.
This scalability in and of itself can also be a very valuable factor of IDP. There has been a trend of consolidation throughout the insurance industry, and handling all the aggregated documentation can be challenging. IDP offers invaluable scalability to these growing players and avoids administrative backlog to hinder further expansion.
Innovation and the digitalisation of the insurance industry has been ramping up, a lot of insurance players have been starting to digitalise their whole operations. Unstructured Documents can create roadblocks to automation and negate the positive effects of digitalisation efforts. IDP solutions such as Paperbox only solve one part of the insurance processes but can still be essential in the total end-solution.
