How to support claim adjustment and benefit payout processes? Tech trends, part 2: OCR technology and the cloud

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The first part of this article focused on workflow engines and their applications in processes related to claim adjustment and benefit payout. Today, we will turn to another important trend: OCR technology – what it is, how it has evolved and how it can now support the work of insurance companies. We will also discuss the cloud, which already offers huge possibilities, not just in terms of file storage, but also in data use and analytics.

How to support claim adjustment and benefit payout processes? Tech trends, part 2: OCR technology and the cloud

OCR technology in insurance

OCR technology is well known and widely used – not just by insurance companies but also a wide range of other businesses.

In recent years, OCR solutions have evolved with the advent of machine learning (ML) and artificial intelligence (AI). What not so long ago was seen as a thing of the future is now beginning to be used in practice. And yet not everyone understands and appreciates the actual potential of these tools. 

Just to jog your memory: OCR (optical character recognition) makes it possible to read text in an uneditable digital document (e.g. insurance policy, claim report or invoice scan) and then convert it into a structured text file format. This helps automate manual fact finding and processing tasks, which speeds up customer service, improves claims processing, and reduces human error. 

OCR applications: an example

For instance, suppose a customer reports a claim. When that happens, you will normally need to read the information included in document scans or a report form. By using OCR technology, you can process the documents in a matter of seconds to pull out the vital information (such as first and last name, claim description, policy number).

This data can then be automatically imported to your system, boosting the accuracy and efficacy of the entire claim adjustment process. 

Potential of modern OCR software

Let’s first refresh your memory of what OCR technology was like just a few years ago (and perhaps still is today in some companies). Initially, OCR solutions required robust document template software to be able to extract data effectively.

They could read the text on a page, but they couldn’t classify it. OCR just wasn’t able to tell if a given sequence of characters was a first name, a last name, or just a document footer.

An employee had to indicate a specific place in the document or specific keywords so that the software could use them to find the data of interest. OCRs of this kind worked well with documents that followed a certain formal template, such as ID documents, driving licenses, or policies. 

For documents where no single recognizable template existed (such as invoices), it would have been extremely difficult, and often well-nigh impossible, to design a working OCR solution. Another issue with older OCR technology was that it initially only recognised print, not handwriting. And this is where machine learning and AI stepped in to bring to us the joys of semantic OCR. 

OCR today

Today, the market abounds with solutions based on trained text-extraction algorithms, which can also classify documents, e.g., determine whether they are dealing with an invoice, a claim report, a refund request or yet another document type. 

Modern OCR software can automatically read handwritten documents and find the data you need.

The next step is to use advanced NLP, which makes OCR able not only to see that a given document is a claim report, but also to read and understand what kind of claim it is and check whether the data provided are correct and complete.

Should any piece of information be missing, the OCR software will alert the user or, if it is integrated with a relevant database, download the necessary information, using policy data or claims history. 

If necessary, it can also automatically anonymise the document. 

OCR and workflow in claim adjustment

Combined with a workflow engine, OCR technology can significantly reduce or completely eliminate manual labour. For instance, OCR software can automatically add tasks to adjuster groups or send an automated e-mail to ask the customer to fill out any missing data. And the (sorted, high-quality) data from the OCR can be fed into data warehouses for the purposes of customer behaviour or sentiment analysis. 

This can help insurance companies understand the behaviour of their customers better and identify certain behaviour patterns, so as to enable potential fraud detection, customer scoring or the selection of an appropriate claim adjustment path.

Cloud in insurance

As you may know, the cloud is still scarcely used in the Polish insurance sector; it is unfortunately still mainly associated with data storage. Instead of storing data on our own servers, we just hire the services of an external provider (be it Azure, AWS or Google). From the perspective of businesspeople, especially in the light of KNF (Polish Financial Supervision Authority) regulations, this spells a lot of trouble and brings few advantages.

And yet the cloud has huge potential, which has already been tapped by institutions such as banks. OCR technology as such is just one of the hundreds of reasons why you might want to look into cloud services more closely. Different providers offer a lot of ready-made services and solutions that you can just easily add to your ecosystem if you already use other cloud solutions.

Cloud solutions

Cloud solutions are perfect for proof-of-concept or MVP tests, allowing you to test a given section of the process in sometimes just a few days or weeks, and then to phase it out if it proves inadequate or, if it is a success, continue testing and developing it further. 

If you’re thinking of using the full potential of your data, you might also want to follow the example of financial companies that have deployed data lake or data mesh solutions. In this case, the cloud is a natural choice: you won’t be able to achieve the results you want without it. 

Tech trends in your company

As you can see, modern solutions help insurance companies increase the accuracy and efficacy of their processes, but also improve their ability to understand their customers and respond to changing market trends. Tech trends, such as OCR technology or the cloud, are becoming an indispensable tool in the pursuit of innovation and better strategy in today’s dynamic business environments. 

In the end, insurance companies that boldly take the challenge of new technology can get a considerable competitive advantage and deliver an even better experience to their customers.

Contact us if you want to develop your portfolio with advanced software tailored to the insurance sector and its demands. 

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    Filip Wachowiak