Evaluating the Best OCR Tools for Financial Document Automation
Compare and contrast common document recognition tools to find the right one for your business.
Hannah de Regt
Data software expert and Chief Operating Officer at BaseCap Analytics
In the financial sector, automation is key to reducing operational inefficiencies. A crucial tool in this automation journey is Optical Character Recognition (OCR). From processing invoices to reviewing complex financial documents, OCR tools can transform tedious manual data entry tasks into seamless digital workflows. In this blog, we’ll explore the best OCR tools available for financial document automation, their types, and essential features to consider when evaluating them.
Using OCR Tools in the Financial Sector
OCR technology has revolutionized the way financial institutions process documents. Gone are the days of manual data entry from printed documents. Financial institutions now use OCR to automate invoice scanning, digitize contracts, extract key information from tax forms, and more. For example, JPMorgan Chase implemented AI-based OCR technology to automate and analyze complex legal documents, saving thousands of hours each year. This was reported in The Wall Street Journal as part of their effort to reduce time-consuming manual processes.
OCR helps financial companies meet compliance requirements, streamline audit trails, and ensure accurate data entry. Whether it’s extracting payment information from invoices or automating the collection of tax data from forms, OCR tools play a vital role in improving operational efficiency.
Types of OCR Tools Available
Traditional OCR
Traditional OCR technology relies on basic pattern recognition to convert scanned images into text. While effective for printed documents with standardized fonts, traditional OCR struggles with more complex data sources such as handwritten notes or non-standardized financial forms.
Intelligent OCR (AI-Based)
Intelligent OCR, or AI-based OCR, is more sophisticated, using machine learning to recognize patterns, context, and the structure of documents. This approach is especially useful in the financial industry, where document types vary greatly and require an adaptable system. For instance, AI-based OCR can be used to analyze loan agreements, contracts, and financial statements, intelligently extracting relevant data. According to Forbes, AI-driven OCR tools have been instrumental in helping companies like Capital One improve loan processing times by as much as 30%.
Handwriting Recognition Tools
For financial documents that include handwritten notes or signatures, handwriting recognition tools come in handy. These tools can scan and interpret handwritten text, such as notes on client files, checks, or financial statements, ensuring that even non-digital inputs are captured accurately.
Mobile OCR Apps
With the increasing need for mobile-first solutions, OCR apps designed for smartphones allow financial professionals to capture data on the go. These apps can scan and process receipts, invoices, and other financial documents directly from mobile devices. TechCrunch reported that these mobile solutions have become increasingly popular among small businesses and financial consultants who need to stay productive while traveling.
Cloud-Based OCR Solutions
Cloud-based OCR tools provide scalability, security, and flexibility. Financial institutions that process high volumes of documents can benefit from cloud-based solutions that store and process data in a secure environment. These tools offer real-time processing capabilities and eliminate the need for expensive on-premise infrastructure.
Learn more about the importance of document validation for risk management in the financial services industry.
Popular OCR Tools and Software for Financial Documents
BaseCap Analytics
BaseCap Analytics provides advanced data validation to make OCR solutions more accurate. Finserv companies like mortgage lenders use BaseCap to compare the output of OCR solutions like LoanLogics or Azure Form Recognizer against data in their system of record. That means analysts don’t have to manually compare CSV spreadsheets against handwritten forms ever again. BaseCap’s OCR solutions are ideal for processing large volumes of invoices, contracts, and reports. The AI-enhanced platform helps financial institutions validate data at scale, improving efficiency and reducing errors.
Azure Form Recognizer
Azure Form Recognizer is a powerful tool that allows users to quickly and accurately extract structured data from various types of documents, including invoices, receipts, and contracts, which can drastically reduce manual data entry efforts. Azure Form Recognizer also integrates seamlessly with other Microsoft services, allowing businesses to automate document processing workflows and scale their operations efficiently. With support for both pre-built and custom models, it offers flexibility to handle diverse document formats and structures. Additionally, its cloud-based infrastructure ensures scalability, high availability, and robust security, making it a trusted choice for organizations handling sensitive financial data.
LoanLogics Intelligent Data Extraction and Automation (IDEA) Services
LoanLogics Intelligent Data Extraction and Automation (IDEA) Services deliver significant advantages in mortgage document processing by using advanced machine learning and automated document recognition (ADR). These services reduce the need for manual data entry by automatically classifying, indexing, and extracting data from both structured and unstructured documents. IDEA ensures up to 99% data accuracy and offers transparency in identifying missing or critical documents. By integrating these capabilities with rules-driven automation, LoanLogics helps lenders streamline workflows and ensure compliance. For more details, visit their page.
Azure Form Recognizer does just that…recognizing key data points in your documents for restructuring.
Google Cloud Vision OCR
Google’s Cloud Vision OCR is a powerful tool that offers machine learning-powered text recognition capabilities. Financial firms use it for tasks such as extracting data from PDFs, invoices, or forms, and integrating the output directly into their systems. Google Cloud Vision’s API also offers language support for multiple languages, making it a flexible choice for global financial firms.
Tesseract OCR
Tesseract OCR, an open-source tool developed by Google, is often used by financial institutions looking for a free yet powerful solution. While not as feature-rich as paid software, Tesseract OCR can be customized and integrated into existing financial document processing systems for more basic OCR tasks.
Adobe Acrobat OCR
Adobe Acrobat offers built-in OCR capabilities that allow users to convert scanned financial documents into editable text. Financial professionals often use Adobe Acrobat to convert scanned contracts, tax forms, and other important documents into a digital format that can be stored and searched easily.
Microsoft OneNote OCR
Microsoft OneNote includes a basic OCR feature that allows users to scan and extract text from images. Though not as robust as some other options, OneNote OCR is useful for financial teams looking for a quick and easy way to digitize small volumes of data.
Key Features to Consider When Researching Financial OCR Tools
Accuracy and Reliability
Accuracy is critical when processing financial documents. OCR tools must reliably convert text without errors to ensure compliance and avoid costly mistakes. Unfortunately many document recognition tools suffer from a “3-percent accuracy gap.” OCR mistakes require manual review, negating the benefits of using OCR in the first place. Tools that integrate AI and machine learning typically offer higher accuracy, especially with complex documents. In addition, adding an automated data validation layer to your OCR engine can prevent bad data from ever entering your data systems.
Supported Formats
Ensure that the OCR tool you choose supports all the file formats you typically work with, such as PDFs, JPEGs, PNGs, and TIFFs. In the financial sector, the ability to handle a wide range of formats is essential for processing different types of documents.
Language Support
If your financial institution deals with international clients, it’s important to choose an OCR tool that supports multiple languages. Many advanced OCR tools offer extensive language support, ensuring that data from global documents is accurately captured.
Image Preprocessing Capabilities
OCR tools that include image preprocessing features, such as image cleanup and text enhancement, are especially useful for documents that may be poorly scanned or have low resolution. These features improve the accuracy of data extraction.
Integration with Other Systems
Look for OCR tools that integrate seamlessly with your existing financial software, such as ERP systems, accounting platforms, or document management systems. Integrating OCR into your workflow ensures that the data captured is immediately usable.
Customization and Flexibility
Customization options allow financial institutions to tailor the OCR tool to their specific needs. Whether it’s automating specific tasks or setting up custom workflows, flexibility is key in making sure the tool fits within your existing processes.
Cost and Licensing
Finally, consider the cost of the OCR tool, including any ongoing licensing fees. Some tools offer flexible pricing models that can scale with your company’s growth, while others may require a significant upfront investment.
Document recognition is just one part of a technology stack that allows enterprises to better understand and trust their data. Learn more about data observability for financial services.
TLDR
By leveraging OCR, financial institutions can automate document processing, improve data accuracy, and reduce operational costs. However, Optical Character Recognition often suffers from accuracy issues due to the complexity of document types. Adding a data validation layer to your OCR solution ensures that only quality data enters your data systems.
Choosing the right OCR tool comes down to understanding the specific needs of your organization. Evaluate options carefully by considering key factors like accuracy, integration, and cost, and you’ll be well on your way to a more efficient and streamlined document workflow.
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Ask the Data Gator!
COO of BaseCap
Optical Character Recognition (OCR) is the process that converts an image of text into a machine-readable text format. For example, if you scan a form or a receipt, your computer saves the scan as an image file. You cannot use a text editor to edit, search, or count the words in the image file.
LoanLogics, a trusted partner of BaseCap Analytics, provides highly specialized document templates for the financial sector. Through Automated Data Extraction (ADE), users can collect and structure the loan file data that’s important for business reviews. Then, they can use BaseCap to automatically validate that data against hundreds of policies or “rules.”
OCR stands for “Optical Character Recognition.” It is a technology that recognizes text within a digital image. It is commonly used to recognize text in scanned documents and images.
OCR tools can process a wide range of documents, including printed text documents, handwritten notes, receipts, invoices, business cards, and even digital images or PDFs containing text. These tools are designed to recognize and convert text from various formats into editable and searchable digital text.
About BaseCap
BaseCap is the intuitive data validation platform that operations teams use to catch and correct data that’s extracted from documents.
"I think the tool is great because it's an out of the box solution where you can give a business admin, or someone that's knowledgeable enough from a tech perspective and a business perspective, to really drive and make the changes and really own the administration of the tool."
