Industry Insights

Top Five Business Processes OCR Can Improve

Optical character recognition (OCR) has been around for almost a century if we take into account telegram translation tools and a reading machine for the blind. Since the 1970s, barcode scanners have been using OCR technology, and the dotcom bubble introduced software for office use that could “read” documents.
Recent AI developments are about to get OCR to the next step, improving the accuracy of multiple formats and languages. We can expect that AI-based OCR will be able to differentiate between handwritten text and scanned documents and extract information even from graphic formats like posters and brochures. 
Here are a few business applications where OCR would save a good deal of work-hours and yield better results.

Document Management

Most organizations have their data stored in a very heterogeneous mix of digital documents and hard copies. If they want to retrieve data fast and accurately, it can be a challenge without an OCR system linked to an indexing and sorting tool.
Imagine a doctor who needs to compare the results of some lab tests a patient took four years ago with current values. If the document is stored as a hard-copy, you would need to go to the archive, find the file, copy the material, and compare it. If it was scanned and you use smart OCR on it, the comparison can be yielded by the computer automatically.
This applies to other business verticals as well, including finance, logistics, and law.

Invoice Management

Although invoices are also documents, they deserve special attention when it comes to OCR applications. OCR technologies allow processors to import data from hard-copy invoices and transform it into a digital format in a matter of seconds instead of retyping everything by hand. This step is necessary for data centralization, better and faster expense management, and stress-free document management. 
Another advantage of digitalization by OCR is the possibility to search through documents much faster than manually. This is a game-changer for payment processing departments because it can offer the opportunity to check particular facts about each invoice with just a few clicks, regardless of the invoice form. It is all about minimizing errors and cutting down the workload.

Travel Document Processing

Some of the most tedious work when it comes to document processing in an organization is related to travel documents. This is because it is a very complex category with many non-standard items which can range from tickets, hotel invoices, and lunch checks to fees and toll-passes.
When returning from a business trip, employees have to log into a portal and input all of the details for reimbursement by the accounting department. If you add to this the problem of multiple currencies and exchange rates, it can get hectic and intimidating for those employees who are not keen on numbers and paperwork. Not to mention that the time required for filling in all the necessary forms can take up to an hour.
The added value of OCR, when implemented in ticket processing software, is shortening the input time through mobile-friendly scanning, with the software then automatically transferring the data to the expense processing platform.
To be useful, such a system should be able to identify the document type, currency, amounts, issuing organization, country, and other necessary details. The only remaining job for the person recording the data is to confirm the accuracy of the OCR and make minor corrections, which should only take a few minutes. This technology is beneficial for companies where business travel is a big part of corporate life.

Insurance Policy Processing

Imagine you just had a car accident and you know you are facing heaps of paperwork to fill in to fix your car. The same heaps of papers need to be processed before you are given the OK to go to a service. But what if the forms could be scanned with a smartphone? As soon as you scan and file them, you have already taken significant steps toward getting you back on track. Another example is making healthcare insurance more efficient by automating data capturing by OCR.
The benefits of OCR technology here are that it eliminates delays, which can lead to stagnant claim processing and payment issues. Using OCR means streamlining the workflow as much as possible. 

Cloud Storage Searchability

Most organizations and even individuals have become used to keep all their files in the cloud, either in dedicated office suites, like those provided by Google, or unorganized, box-like environments, like Dropbox. It is the first step toward a paperless organization, but additional refinements are mandatory.
The best news is that Google Drive already has some basic OCR included. For example, it can turn PDFs and photos into editable documents automatically, although it still has problems in understanding charts, headers, and footnotes. OCR in the cloud is also useful in transferring contacts and other business information to corporate systems.

Possible Challenges

Although OCR has progressed a lot, there are still a few challenges it has to overcome in the next few years. The rise of big data means a wider variety of formats to be processed. Making these searchable, indexable, and accurate translates into fewer errors and less time spent on searching.
There are some requirements to ensure top OCR results:

  • Use original, hi-resolution images with high contrast and low noise. The dpi should be at least 300 for an optimum balance between quality and file size.

  • Prepare documents by checking their size.

  • Make sure the text is oriented so that the scanner reads it horizontally.

  • Use OCR in conjunction with other tools such as dictionaries, thesaurus, and filters.

OCR is not an innovation but an incremental improvement of the existing technology. Even so, it can help organizations process documents faster, more accurately, and with fewer employees. Efficiency and mobility are enough reasons to invest in this solution.

Emma Foster

Emma Foster

Emma Foster is a technical writer and business analyst in software development.

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