Optical Character Recognition (OCR) automation creates increased operational efficiencies within enterprises, which, in turn, brings improvements to the customer experience. OCR automation makes unstructured content (the vast majority of a company’s data, made up of things like emails, image files, and paper documents) searchable and usable by automated analytics tools. This allows staff to extract value from the content, meaning that they spend less time manually searching for the documents they need to do their jobs. It frees them up to work on what matters most: exceeding client expectations.
IMAGE: PIXABAY
The Changing Face Of Customer Expectations
Customer expectations have been undergoing a revolution in recent years. Online and mobile technology has increasingly fostered an anywhere, anytime attitude towards gratification. More and more customers want the right answer, right away—whether that’s a quick turnaround on an insurance claim or being able to get quick online approval for a loan. In a sense, the easy fulfillment and high-quality standards customers used to dream about have become the baseline expectation that companies now must fulfill.
In many cases, the urgency for companies to provide a better customer experience has been heightened due to the emergence of digital-born competitors. Companies like Esurance, with streamlined digital-only offerings, can do things for customers that weren’t previously possible—like processing claims or applications online, and solving client issues faster, more accurately, and with a greater degree of satisfaction. These companies are disrupting customer engagement and have left traditional companies scrambling to up their game, which has created a wave of digital transformation in which OCR automation plays a crucial role.
The Unstructured Content Problem
A big challenge for an established enterprise is that their digital transformation has to contend with the vast legacy storehouses of unstructured content that have accumulated over the years. Over decades, they may have collected and stored client files and records that include everything from policies to contracts to claims—often in unsearchable paper or digital image file formats. If the data is not processed into a format that can be searched and inputted into automated analytics tools, then it must be handled manually—which jams up workflows within an organization and hinders the company’s ability to deliver on customer expectations.
Consider a large insurance organization that has a number of processors working to clear customer claims. These are highly paid experts doing an important job. If they have to spend significant amounts of time searching for paper documentation in order to resolve claims, then workflows slow down and costs rise. As a result, customers will have to wait longer for their claims to be resolved. What the company needs is an automated method of processing their unstructured content.
One answer to these problems is to implement an automated OCR solution. OCR is the process of turning pixels representing characters in a scanned image into the actual text. When you scan a page containing the letter “T,” it is simply a collection of pixels in the form of a “T.” OCR is a powerful technology that recognizes that pattern of pixels as the letter “T”—making it possible for the information to be copied and indexed so that search engines can find the content.
Three Ways OCR Automation Improves The Customer Experience
Implementing an automated OCR solution offers significant benefits to a company and its customers, including:
1. Speed
Turning unstructured content into searchable data increases operational efficiency, making searches quick and easy. Highly paid and skilled experts no longer have to waste time hunting for the information they need, allowing them to work at the highest level of their capability. They can make quicker and better decisions, resolve claims faster, and give customers the answers they’re looking for more quickly.
In financial services, for example, a customer looking for a copy of a 20-year-old mortgage agreement might have to wait weeks to receive it if that document is hidden as a non-searchable, scanned image. However, if the agreement has been OCR’d, the bank could simply search for the customer’s name and instantly find the file.
In another finance example, one bank that Adlib works with had crafted a new deal with a client firm. Since the parameters of the deal had changed, the bank wanted to review the original contracts for comparison purposes. The problem was, because the contracts were more than six months old, they had been scanned and sent to an off-site storage location. It took the bank two weeks to find the previous agreement, which held up progress on the new deal. If the original documents had been processed using OCR, then a query in a search engine would have found them quickly and the client deal would have gone through much faster.
2. Accuracy And Utility
OCR can improve the customer experience by enabling companies to provide more accurate answers or services that have high utility for their clients. To achieve this, however, OCR needs to not just make a document readable, but it needs to do so with a high degree of accuracy. For instance, if a document is made searchable, but because of poor OCR the search tool is only able to read every fifth word, then the client may pull search results that aren’t good matches with what they’re looking for.
OCR is also beneficial when it comes to increasing the utility of information to improve the customer experience. For example, one energy company had a large image library that needed to be moved to a new archive. They realized that if they were to not just move, but also OCR the images, then the value of that data would be increased. The image library would become easily searchable, and the data could be used to improve quality control. For instance, if a part failed in a pipeline, the company would be able to easily search all the work orders and contracts in the library to identify all the pipes that used the same part, so they could proactively fix the issue for all customers.
3. Improved Offers And Better Service
OCR can automatically extract value from unstructured content, which enables companies to reduce client headaches and provide customers with the ability to interact with the company in the way that makes the most sense for them.
In the insurance industry, OCR enables clients to submit claims in many different formats—from photos to handwritten letters to faxes and emails. Automation with OCR can normalize all of those different formats and make the content searchable. Because OCR makes the content readable, the company can extract values from the data, such as policy numbers that can be validated against what’s in the organization’s system. This allows the company to understand what the client’s coverage is for that particular claim).
In this way, OCR enables the organization to automatically complete several early steps in the claims process, speed time-to-resolution, and improve the customer experience. (For other examples of the benefits of OCR in the insurance industry, see Four Benefits of OCR in the Insurance Industry.)
Making unstructured content searchable also means that an organization can find and extract data that might help identify a problem or opportunity for their customers. For example, if all bank accounts, insurance policies, and investment programs can be analyzed, a bank might be able to proactively suggest a package of products that better suits the customers’ needs than what they currently have.
Wrap Up
When enterprises use OCR data capture to extract value from unstructured content, workflows speed up and employees are free to focus on the company’s most important business and operational objectives. The increased accuracy and utility that high-quality OCR enables leads to better decisions, more targeted products and services, and improved customer experiences. These benefits make OCR automation critical to organizations’ efforts to digitally transform and better meet client expectations.
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