OCR in Banking: Streamlining Document Management for Accuracy & Compliance

Optical character recognition (OCR) technology is an effective way of digitizing paper-based documents. The banking industry heavily relies on physical documents, so it can greatly benefit from OCR. But there’s more—OCR in banking is also crucial from a compliance perspective. Digitizing documents can enhance their security and help banks protect data.

With the banking industry prioritizing paperless processes for a while now, it only makes sense to have technology that makes it easier to digitize paper documents. However, some banking processes still involve paper (think checks, ID documents, and forms). At the same time, banks also need to make their workflows more efficient. OCR caters to all these requirements head-on.

This article dives into the application of OCR technology in banking, its importance for enterprises in this sector, and how they can utilize it to improve document handling and data collection.

What is OCR in Banking, and How Does it Work?

OCR is the technology that transforms printed or handwritten text into machine-readable text (for example, DOC or PDF files). It usually involves scanners to capture the image of the physical document and software that analyzes the digital image of the document for text or symbols. The result is a digital document that can be edited, modified, and copied. The text also becomes searchable, so particular sections or words can be quickly found, even in a large document.

OCR may be standalone software or part of a document management system. The tool may even be integrated into different systems, such as customer relationship management (CMS).

The tool itself follows a multi-step process:

• Image Preprocessing: The OCR software initially prepares the image by enhancing its quality, removing noise, and converting it to grayscale.
• Text Identification: This step identifies image areas containing text and those without text.
• Character Segmentation: The localized text is divided into individual characters or words (varies by software).
• Feature Extraction: Key characteristics of each character, such as its shape, size, and orientation, are extracted.
• Pattern Matching: The extracted features are compared to a database of known character patterns. The most likely match is selected.
• Post-processing: The recognized text undergoes further processing to correct errors, such as misidentified characters or incorrect word segmentation. It may even correct the spelling.

MST’s OCR software can accurately capture text from images of physical documents (printed or handwritten) and retain the format as closely as possible to the actual document. It automates data collection through documents, streamlining processes like account opening and loan application.

Benefits of OCR for the Banking Industry

While any business can benefit from digitizing paper documents with OCR, those in the banking industry are uniquely positioned to rely on it more extensively. The simple reason is the industry’s persistent use of paper. Despite a strong drive towards paperless operations, many processes still involve paper. For instance, numerous banks require customers to sign on paper when registering their signatures for financial transactions.

OCR technology in banking caters to various technological and operational needs. It’s an investment that’s likely to pay for itself in the short term because of the increase in efficiency and productivity and decrease in errors.

Automation and Efficiency

Manual data entry is highly inefficient. Looking at a document and then typing the text into the software will take an employee a long time. That same time can be reclaimed with OCR and spent on more valuable tasks. OCR automates this process, saving banks losses in employee productivity. Within seconds, the tool can extract all the textual information from the document’s image.

As a result, OCR automation enables workflows to progress much faster, and documents can be digitized at scale.

Improved Accuracy and Reduced Errors

OCR minimizes human errors in data entry, which ensures the accuracy of banking records. Consider this: a minor clerical error caused Citigroup a shattering $900 million problem. Such costly errors can be prevented with automated digitization and data extraction of documents. In banking, there’s no room for error. Even a single incorrect number in statements can lead to significant issues.

Keep in mind that accuracy depends on the quality of the document’s image and the tool’s capability. Still, most OCR tools can outperform humans in accuracy.

Cost Reduction

By automating document workflows, banking institutions can reduce operational costs and free up staff for more critical tasks. Simply put, a loss in productivity equals a loss of money. OCR in banking prevents employees from spending unnecessary time on turning paper documents digital. They merely need to scan a document, and a digital copy will be ready with a few clicks.
Similarly, the accuracy of OCR also results in cost savings. As evidenced by the Citigroup example, errors in data entry can lead to substantial losses.

Regulatory Compliance

OCR empowers banking institutions to comply with international and local regulations. These regulations typically ensure financial accountability and data protection. And they’re non-negotiable. If banks want to stay in business, they must comply.

Banking OCR solutions are compliant with such regulations in two ways. First, these solutions feature built-in security features like encryption to ensure documents aren’t compromised (MST is one solution that takes security very seriously). Second, digitizing documents helps reduce the risk of compromise of physical papers, such as a form with a customer’s personal information.

Data Accessibility

OCR makes previously inaccessible data in paper documents searchable, editable, and easily integrable with systems frequently used by banks. The digitized documents can be utilized with proprietary software and other third-party solutions. This further enhances the workflows as data moves from one tool to another seamlessly.

Some banking OCR solutions, like MST, can readily integrate with content and enterprise resource management systems.

Key Applications of OCR in Banking

Here are the typical OCR use cases in banking:

• KYC and Customer Onboarding: Know Your Customer (KYC) is a part of regulations to prevent money laundering and terrorism financing. It typically involves a form to gather information on the customer’s source of income/funds. All that information, of course, is private. Those forms can be digitized with OCR and saved in a private server/cloud.
• Loan Processing & Underwriting: Many loan applications and supporting documents are submitted in paper formats or as images online. OCR automates the extraction of loan application data. When integrated with internal systems, the information can be directly fed into the system, which analyzes it for risk during underwriting.
• Cheque Processing: Even with the advent of digital banking, many consumers, including businesses, use cheques for payments. Those cheques must be scanned for processing. OCR helps extract the necessary information such as cheque number, account number, recipient’s name, date, etc.
• Mortgage Document Processing: Mortgages are the signature product of most banks and involve a lot of paperwork. From applications to supporting documents, OCR tools can quickly obtain the information staff or the system needs to create a quote or give approval. They also allow banks to digitize those lengthy deeds and agreements and back them up digitally.
• Auditing & Reporting: OCR facilitates the auditing of financial records, ensuring regulatory compliance with critical laws like MiFID II and AML. After being processed by OCR software, physical copies of vital and sensitive documents can be backed up digitally. If and when needed, those documents may be presented to authorities. Similarly, data extraction from documents can make reporting a breeze.

The Role of OCR in Regulatory Compliance

OCR is a powerful tool that can significantly enhance a bank’s ability to adhere to regulatory frameworks. Here’s a glimpse of OCR for regulatory compliance in banking:

• Anti-Money Laundering (AML): OCR automates the analysis of transaction records and client documentation, ensuring banks can track suspicious activities more effectively. This helps banks identify and report potential money laundering activities, reducing their exposure to financial crime risks.
• KYC Regulations: OCR streamlines the onboarding process by automatically extracting and verifying data from customer identification documents, helping banks meet KYC requirements. This reduces manual effort, speeds up the onboarding process, and improves customer data accuracy. KYC is basically part of the AML regulations.
• Basel III Endgame: Basel III Endgame is a set of international banking regulations designed to strengthen the global financial system by increasing capital requirements and improving risk management practices. OCR improves the speed and accuracy of data processing, helping banks provide accurate risk management data and maintain the required capital reserves. This enables banks to assess their risk exposures more efficiently and make informed decisions about their capital allocation.
• PSD2 & Open Banking: By integrating OCR, banks can quickly adapt to PSD2 and open banking regulations by making customer financial data more accessible and easier to manage. This allows banks to provide customers better access to their financial data and enables third-party providers to offer innovative financial services.

Emerging Trends in OCR Technology for Banking

Here are recent technological advancements in OCR in banking:

• AI-Powered OCR: Thanks to recent innovations in Artificial Intelligence (AI), the quality of OCR’s output has improved manifold. OCR technology can incorporate generative AI to enhance documents in real time. With contextual awareness and training on large language models (LLMs), AI-enabled OCR tools can extract information with low error margins.
• Cloud-Based OCR: Cloud-based OCR tools can reduce server processing load and make the tool accessible anywhere. They essentially function as software as a service (SaaS), which users can access from any location and with any platform (desktop or mobile). For instance, a sales representative can scan and upload documents to the system or email them to their manager on the fly.
• Mobile OCR: Mobile devices with OCR capabilities enable remote workers and customers to easily submit banking documents such as IDs, cheques, and receipts for processing. This is achieved through the mobile app version of OCR software, which accesses the mobile’s camera for scanning.

How MST’s OCR Solutions Help Banks

MST’s eViewer has a native OCR tool that can complement the tech stack of any banking institution. The OCR technology works with scanners to capture documents and convert them into a digital format of your choice. For instance, a printed financial statement or appraisal report can be quickly transformed into a PDF file.

The eViewer can be integrated with the bank’s systems, mapping the data on forms or IDs to fields in a database. Whether the bank uses its systems or from another vendor, it can easily integrate the eViewer and the OCR tool within it.

MST’s OCR solution helps streamline processes such as customer onboarding, identity verification, refund processing, cheque deposit/cashing, and more. It can also digitize all critical documents, ensuring compliance with data protection regulations.

Once digitized, the document can be shared securely on the internal network and even with external stakeholders via a secure, encrypted connection. Users can view, sign, and edit a document based on their permissions. And that’s another big feature—role-based access. The digitized, machine-readable copies of physical documents can be protected with access controls.

Conclusion

OCR in banking solves several challenges: paper trails, loss of productivity, and security. It turns printed or handwritten forms, letters, and other documents into ready-to-use digital files. Bank employees no longer need to manually enter data. It’s an efficient, cost-effective, and simple solution that should be made available to most bank employees.

MST provides an advanced and reliable OCR solution within its eViewer, a product written in HTML5 that can be operated on any platform. Many big finance companies already use MST to make their document processes smoother and quicker.

Learn how MST can help your bank!