OCR stands for Optical Character Recognition, which is a technology that helps convert texts from images and other sources into text that is machine-readable. Today, contract managers use OCR technology to capture crucial information from legacy contracts, which otherwise takes hours or even days.
Wondering how it is done? Read this blog for complete information on using OCR for contract management—its process, benefits, and challenges. Know how using OCR can improve your CLM processes for efficiency and precision.
What is OCR in contract management?
OCR-based contract management refers to using optical character recognition (OCR) technology to extract and tag key contract data from paper, digital image files, JPG, and PDF agreements.
OCR-based contract technology helps get data insights from agreements generally not scannable or searchable by machines. This helps contract managers gain insights from the scanned text of legacy contracts without spending time analyzing each contract manually for this information.
Advanced OCR contract management tools have an in-built OCR engine that works with other technologies like artificial intelligence (AI) for complete automation in contract analysis. Natural language processing (NLP) and data extraction technology can extract information and auto-populate it into an actual record in the software.
Now that you know what contract OCR is, let’s see how it is beneficial for an organization.
5 reasons why you should use OCR to manage your contracts
Here are 5 noteworthy reasons for implementing OCR contract management software for your agreement management processes:
1. Auto-extracts contract metadata
Extracting contract data from legacy contracts is tedious, especially when you have piles of contracts.
OCR engines help avoid manual data entry by auto-identifying key contract terms from legacy agreements. AI then extracts these terms, enabling contract managers to gain insights from these agreements.
2. Helps identify and tag important fields
Optimal contract searchability and scannability are important for locating the right contracts and clauses. Contract managers often use tagging features in CLM tools to create bookmarks for essential agreement clauses—spending time and resources in the process.
Integrating OCR technology in your contract management process can help auto-identify and tag important clauses and terms in agreements. The OCR tech auto-identifies the most important clauses and tags them. This way, you can easily locate data within contracts with ease.
3. Promotes a single source of truth
More and more organizations are moving their agreements to central contract repositories. This means moving the contracts from storage locations like mail, drive folders, CRMs, and ERPs to a central digital storage location. However, what about paper documents, PDFs, and images?
With OCR technology, you can maintain a single source of truth and move all types of contracts to a single repository. OCR converts contracts in non-supported contract formats to ones that your digital contract repository software can understand and analyze—thus concentrating contracts to one source.
4. Sets reminders for obligation tracking
Wondering how many payments are due this quarter from your legacy contracts? Tracking contract dates and obligations is important for effective contract management. However, with legacy contracts, sales, procurement, HR, and finance teams lack visibility and tracking.
With all contract data being automatically identified, analyzed, and extracted, you can switch on auto-alerts for key obligations and dates. The OCR technology works in sync with AI contract tracking software like HyperStart CLM to generate reminders for key dates, leaving nothing to chance.
5. Get better results, faster
Manual data extraction processes are mundane and prone to human errors. When analyzing, extracting, and tagging thousands of contracts manually, there are high chances of human errors and negligence. This increases business risk, decreases productivity, and may even increase contract management costs.
OCR helps get better results in contract management with significantly less effort. You can automate the most complex of CLM tasks with OCR and AI technologies which are reliable for accuracy and precision. This makes contract processing easier and contract management more efficient and budget-friendly.
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Book a DemoThese are the benefits of using OCR technology for contract administration. However, while OCR, there are certain challenges and considerations while using OCR for managing contracts. Wondering what these challenges are? Keep reading to find out.
Common challenges in OCR-based contract management
OCR surely makes the contract management process frictionless and efficient. However, there are certain considerations to know about while using this technology. They are:
Chances of inaccurate results: Untrained or poorly trained OCR engines often generate inaccurate results. Your legal team may have to spend more time correcting this data.
Limited language support: Contracting OCR tech may not understand contracts in different languages or may use translators to interpret agreements.
Errors in unstandardized contracts: Unstandardized contracts have varying formats. This results in faulty data capture where OCR engines don’t understand dynamic layouts.
These are the challenges of using OCR in contract management. However, with advanced, well-trained, and refined contract management tools like HyperStart CLM, you can overcome these challenges. These tools offer accurate OCR extraction with multi-language support.
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Now that you know the challenges and considerations of OCR contract management, let’s take a look at how OCR tech can be used for contract management.
How OCR-led contract management works
This section lays down the process of using OCR technology to manage contracts.
1. Contract input
The first step to OCR conversion is to upload the contract documents on the OCR tool.
These documents can be in formats like images, handwritten agreements, PDFs, etc.
2. Preprocessing
Once the contract is imported and captured, the OCR tool preprocesses the file.
Preprocessing involves scanning for contracts only, eliminating duplicates, and gatekeeping unexecuted agreements.
Poor-quality contracts are adjusted for brightness, clarity, and sharpness, improving their quality.
Preprocessing helps achieve document quality that OCR engines easily understand and analyze.
3. Segmentation
The processed documents are clustered into smaller chunks for easy processing and better accuracy.
Contracts can be segmented based on smaller logical parts, thus making document processing faster for the OCR engine.
4. Character recognition
The OCR engine captures the text in the contract document through pattern recognition, feature recognition, or AI-powered OCR technology.
Pattern and feature recognition capture and match the contract’s data against available databases.
AI OCR uses machine learning technology to recognize and extract text from legal documents. HyperStart CLM uses this technology to extract contract data with 99% accuracy.
5. Text conversion and classification
The scanned and identified text is converted into machine-friendly formats for other tools to process.
Data from scanned contracts is classified based on similarity and tasks.
6. Post-processing
The extracted data can be stored, tracked, and analyzed.
The OCR engine also tags the extracted data with context to help contract managers find contracts based on classified data and text.
If you are using tools like HyperStart CLM, you can generate auto-reminders for extracted data like renewal dates, payments, and other obligations.
7. Review and verification
This step involves reviewing and correcting the extracted information to ensure accuracy.
High-stake data may be flagged for manual review, ensuring minimal risk exposure and maximum compliance.
OCR engines can automate data validation and verify contract information for accuracy, grammar, and spelling issues.
This is the process for using OCR for contract management. Now, what are the scenarios where OCR contract management is the right choice? Let’s discover some unique applications of this technology in the coming section.
3 Applications of OCR technology in contract management
The purpose and use of contract management OCR is to analyze and capture data from legacy contracts. However, there are multiple ways to use this technology. Let’s discover some use cases of contracting OCR.
- CLM migration and onboarding: Moving digital contracts from drives, email, and folders to CLM is easy. However, for physical contracts, you need OCR engines to convert legacy agreements to the digital format.
- Compliance monitoring: Contract OCR tools are excellent at understanding and tracking compliance. You can easily track compliance needs from years-old agreements.
- Renewal management: Wondering which contracts are due to be renewed this year? Get OCR engines to auto-tag and auto-track renewal dates—ensuring that you never miss another renewal again.
These are a few of many use cases in which OCR is the right technology for the contract management process. Now that you have all the information ready, all you need is a strong and reliable OCR contract management system.
Auto-extract contracts with 99% accuracy using HyperStart CLM
Leveraging OCR for contract management requires a strong and well-trained platform. HyperStart CLM provides AI-powered OCR contract management software to help you turn legacy contracts into insights with zero effort.
HyperStart CLM’s single-click import helps automate your contract data extraction process—giving you a fully prepared dashboard within 48 hours. Our OCR software auto-tags digital and scanned documents you organize based on renewal dates, liabilities, and other terms.
Still unsure? Book a demo with our team today to discover the unique applications of HyperStart’s OCR in your contract management processes.
Frequently asked questions
HyperStart CLM checks all these boxes and offers a 99% accurate AI and OCR tool to automate routine contract tasks. You can get a free 14-day trial of HyperStart CLM to know more.
