How COVID-19 Will Boost Adoption of AI-Powered OCR in Banking

OCR (optical character recognition technology) technology has been around for over 30 years. Banks were slow to adopt AI-based document digitization. The main reasons for that were lengthy approvals, security requirements, and bureaucratic constraints. But throughout the years, OCR in banking became popular.

Now during the COVID-19 pandemic, banks aim to reduce personal contact. They try to limit the number of customers that can visit them in person. Yet, they still use loads of paper. Because of the documents, you need to apply for accounts, loans, process cheques, deposits, etc.

Recent research says that the strains of the COVID-19 can stay on paper for up to 5 days. So banks and financial institutions are now racing to adopt OCR software in their day-to-day. The ability of OCR to scan and recognize handwritten texts, images, convert them to a readable format, and analyze documents made it irreplaceable for many banks. In this article, you will learn about how COVID-19 boosts the adoption of AI-Powered OCR in banking in 2021 and beyond.

Digitizing Data in Banking

Even before the COVID-19 pandemic, banks were on their way to implement more artificial intelligence with the help of data science solutions. That includes more machine learning but also other data science techniques. In 2018, just after the technology sector, the financial section was the one that spent the most on AI services.

Today, AI can manage a lot of tasks. Such tasks are machine learning systems trade, engaging with customers, fraud detection, helping banks comply with regulatory requirements, etc.

If a bank wants to transfer to more automation, they have to digitize their paper documents. That means it will convert all of its data which will also be available in the future. This change would be helpful to all banks. By having everything digitized, you could finish all processes faster and easier. However, making this change could be challenging and not so easy.

What Can Optical Character Recognition (OCR in Banking) Do?

In today’s world, which is moving fast, the bank is probably the institution that uses OCR the most. Document digitization within the banking sector itself is possibly the best utility. Banks mostly use OCR to achieve better and safer transactions that are secure. It reduces risk and also reduces any chances of having issues.

The OCR software in banks can also scan handwritten documents that could be of great importance. Usually, those documents are loan documents or such. Besides that, the incorporation of facial recognition software through OCR is remarkable as well. It provides more security at ATMs and makes them safer.

AI business process optimization has made a difference. Using machine vision technology, OCR recognizes written letters and characters. Then it reproduces and stores them in digital format. All OCR needs is a high-resolution camera to recognize the information. It digitizes the information after scanning it and puts it in a database.

Businesses that implement OCR capabilities to convert PDFs and images save a lot of resources and time. It usually implies scanned paper documents. Once it is transferred and processed, the information is much easily used by businesses.

You need to install OCR (optical character recognition) software in a system with a good camera. That means that the camera should produce high-resolution images since it will most likely be images of paper documents. It recognizes characters and letters (by shape) and reproduces them in a digital format.

Optical character recognition digitizes all of the information that you scan from a document. That information is stored in a database that contains customer information and some essential records. OCR in banking can also help if a bank has a backlog of physical documents from their clients. That is the case if they are willing to use new data to uncover novel business insights.

AI-powered OCR can process many characters, fonts, and languages, including Chinese, Latin, Arabic, and Indian. It saves time by minimizing human involvement in document translation by recognizing handwritten texts.

Companies can also use OCR with facial recognition. It is mainly used to verify text on a photo ID (or similar documents). Companies are starting to use these types of advantages, even those that have not used OCR in the past. However, these advantages might be difficult since not every employee knows how to operate with AI. That is probably the biggest downside to this.

Examples of what OCR can digitize for banks:

  • Cheques for remote deposits
  • Details of credit or a debit card
  • Applications for loans, credit cards, bank forms, etc
  • Bank statements
  • Quickly route the mailroom’s intake to the staff instead of distributing physical letters.

It reduces the cumbersome paperwork, saves costs, automates processes, streamlines workflow, and enhances customer service.

The Advantages of AI-powered OCR

  • It enhances the health and safety of employees and customers by making interactions with the bank contactless and reducing contact with paper surfaces.
  • It saves time, space, and money. AI-powered OCR routes digitized documents through the primary data stream to make them accessible to employees, experts, customers, and analysts. OCR enables quick backup, editing, and recovery of the data. It reduces the extent of physical space required to store papers.
  • It uncovers new revenue and customer engagement opportunities by offering valuable business data insights that were earlier unexplored from a backlog of physical documents about previous clients.
  • It speeds up and simplifies the mailroom process. OCR can digitize the paper mail received by the bank to email to the recipient straight away.
  • Powered by other AI technologies, such as RPA and natural language processing, OCR can enhance transaction security. It almost fully automates risk assessment and fraud detection of any paper document by extracting and factoring in data from physical records. AI-powered OCR deciphers different text variations and highlights format changes or corrections.

The ability to take out only the text from a digital image is only one side of OCR capabilities. Data can also be extracted from other types of documents. Some of them include hand-printed text, bar codes, checkboxes, et cetera. The most significant advantage of all of this is that paper is being eliminated, and its usage is reduced.

By having OCR technology, businesses can:

  • Reduce the costs
  • Speed up processes
  • Automate document routing
  • Secure data
  • Have better service by ensuring that employees have accurate information

The OCR technology (mainly OCR in banking) continues developing and improving and soon will reach higher levels of accuracy.

Conclusion

OCR in banking is possibly the crucial technology that will help automate business operations in banking. It will help replace a lot of types of paper documents that banks still use across the industry. This technology is beneficial to banks that have not stopped using paper. But now, with the COVID-19 pandemic, this process will most likely accelerate and will help with the paper replacement.

On the other end, bank customers can also benefit from OCR technology. They can use smartphone apps that will help them scan checks and other paper documents. It will also allow them to make a deposit remotely. Usually, the app will simply take a high-resolution picture tiit then sends to the banks’ database through an OCR application.

We have mentioned that banks can also use OCR for more robust security and more risk management. If we use OCR with different automated operations, it can become another security layer. Companies could use OCR for this reason since it could also help them with their fraud detection systems.

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