A Complete Guide to Automated OCR Data Capture

Accurate and reliable data extraction is critical to enhancing business operations. However, businesses relying on manual data entry face low productivity, increased errors and costs, and compliance issues.

For instance, the average office worker spends nearly 50% of their time updating and creating documents and 10% on manual data entry. Also, according to research, poor data quality can cost businesses nearly USD 12.9 million.

On the other hand, automated data extraction using Optical Character Recognition (OCR) transforms the data capture processes and improves efficiency. 

The benefits of automation OCR data capture are countless. It offers numerous business advantages, from increased accuracy rates, data-driven decisions, enhanced customer service, and reduced costs. 

This blog discusses OCR data capture in detail, including its benefits, drawbacks, use cases, and applications. We also explore how Docsumo can help businesses automate data capture.

What is OCR Data Capture? 

Optical Character Recognition (OCR) data capture is a technology that scans PDFs, images, and paper documents to convert data into editable and searchable texts. The software solution does this by recognizing different characters and comparing them with a trusted database of fonts to extract data. 

The extracted data is then ready for detailed analysis, integration, and storage. Several industries, retail, lending, banking, government, real estate, healthcare, insurance, and logistics, now widely employ OCR technology to automate data extraction tasks. 

How does OCR Data Capture Work?

OCR data capture systems follow a series of steps to extract data from documents accurately. And here's how an OCR solution automates data capture from documents: 

1. Image acquisition 

To begin the OCR data capture process, upload the relevant PDFs, documents, and scanned images into the OCR system. Some OCR systems enable automatic document ingestion through APIs, which intake documents from mail, DMS, and computers without manual intervention. 

2. Image preprocessing 

The OCR software solution then enhances the images in the documents to facilitate accurate data extraction. It performs a series of advanced preprocessing techniques to improve the document’s quality. 

Firstly, it corrects the skew to ensure the document is aligned correctly. Next, it reduces noises such as dust, smudges, digital artifacts, dots, boxes, and stray marks and adjusts optimal levels of contrast and density. 

This process helps the OCR recognize text from the background, reducing the chances of errors and inconsistencies. 

3. Character Recognition 

In this process, the OCR software analyzes the layout of the documents to locate text blocks, lines, complex tables, and paragraphs. It then employs pattern recognition and feature extraction algorithms to identify, isolate, and analyze characters. 

These algorithms break down each character into lines, angles, curves, and intersections to compare them against databases of fonts and identify the closest match. 

4. Output generation 

After identifying the characters, the OCR solution converts them into machine-encoded texts. This helps data operators easily integrate data into existing business software, perform analysis, and store information in databases.

5. Post-processing 

Once the output is generated, the OCR system arranges the characters into words, sentences, and phrases to preserve the formatting and layout. This step also employs robust validation rules to identify misspelled words and errors, analyze context, and correct inaccuracies. 

A Comparison of Manual Data Entry and OCR 

Traditional data capture is slow, tedious, and expensive. It's also prone to human error. Companies that benefit most from automation OCR technologies are those involved in payroll process and administrative tasks. 

They can reduce the number of forms they must complete and speed up their submission process.

1. Manual Data Entry and its challenges

Manual data entry enters information from a paper document or image file into a computer application. The manual process of sorting through and entering data can quickly become a bottleneck for companies trying to scale their operations.

There are many challenges associated with manual data entry, including:

• The challenge of reading specific texts due to poor handwriting or printing quality
• The Difficulty identifying important documents versus those that aren't so important
• The time it takes to manually enter all the necessary data into your computer's database
• The potential for human error when entering all this information by hand

Conversely, automated OCR data capture can identify, extract, and classify useful information from documents. Among other advantages of OCR over manual data entry, the most significant is speed. OCR is fast, accurate, and reliable for handling your data entry needs.

2. How is OCR better than manual data entry?

Automated OCR software is more convenient because it does not require user intervention. Compared with manual data entry, automatic OCR systems are more economical.

Automated OCR data entry can instantly turn your product information into computer-readable text that shopping carts and other online systems can use. OCR software reads the text directly from images of items and then converts it into usable information, allowing you to quickly and easily upload it.

Benefits of Automated OCR Data Capture 

Automation OCR (Optical Character Recognition) offers many benefits that can significantly improve efficiency, accuracy, and compliance. This technology has become an indispensable tool for organizations across various industries, from healthcare to finance and beyond. 

1. Faster turnaround time

Automated data extraction using OCR systems ensures faster turnaround time of data even while processing large volumes of documents. This helps to deliver services on time, improving customer satisfaction and retention. 

For instance, an insurance company processing hundreds of claims daily can extract name, age, phone number, policy details, and insurance amount in minutes. The company can then analyze the extracted data to ensure authenticity and swiftly initiate payments. 

2. Reduced human errors and increased accuracy

AI-based OCR solutions capture data with unmatched accuracy levels, greater than 90% for businesses across different industries. They use advanced validation rules to verify the extracted data and identify errors. 

The system also constantly learns and updates to maintain and improve this higher accuracy rate. 

3. Reduced operational costs

Adopting OCR technology into document processing workflows reduces significant costs in hiring labor for data extraction. Businesses can also prevent additional costs on expensive errors caused by manual data entry. Thus, in the long run, OCR technology offers a great ROI with all these cost savings. 

4. Enhanced efficiency and employee satisfaction 

OCR systems can work 24/7 without breaks or downtime, handling all repetitive data capture tasks and relieving employees. This lets employees leverage their skills to contribute to high-value tasks, improving employee satisfaction and retention. 

For instance, a business processing thousands of invoices per month can use OCR automation to extract data from invoices. This way, employees can concentrate on procurement strategies, vendor relationship management, and budgeting, improving business growth and expansion. 

5. Compliance and security

Most OCR data capture systems are GDPR, HIPAA, and SOC-2 compliant, helping businesses ensure compliance even with the strictest regulations. End-to-end data encryption, cloud storage, and access controls protect customer data against cybercriminals and malware attacks. 

For example, a healthcare organization storing patients’ personal and financial data can easily maintain HIPAA compliance with OCR systems. Moreover, advanced security features ensure that patient data is safe and secure. 

Schedule a free demo with Docsumo to learn how it can automate data capture according to your business needs. 

Drawbacks of Automated OCR Data Capture

OCR is imperfect; even the most basic text recognition software isn't infallible. For instance:

• OCR software does not support most fonts (and when it does, there are often significant issues). This means that text from any document with a font size of fewer than 12 points can likely have errors.
• Text from documents that use bold or italic font can be more challenging to convert. Also, paragraphs and line breaks may not be recognized by OCR programs and must, therefore, be manually added to the file.
• OCR software may fail to pick up certain characters in your document correctly if they are extremely large or small or not in a standard format.
• You must double-check all spellings of words and punctuation before submitting your documents.
• The text capture does not include images or tables, so these can be scanned separately.
• The finished scan is a single-column page, which means that presenting this information online or in other formats is limited.
• OCR doesn't recognize all formatting, so words may be written in all capitals, or some lines may be indented.
• If your documents are large (more than 5,000 characters) or have very complex formatting, it might not be cost-effective for you to use OCR. 

How Much Does OCR Data Capture Systems Cost? 

Here's a detailed breakdown of the costs involved in investing in an OCR data capture system: 

1. Front-end costs

Front-end costs for the OCR software for data entry system vary significantly according to the vendor. Some vendors might offer a “pay and forget” based pricing model for the OCR system, while others provide a flexible subscription or pay-as-you-go pricing method for businesses.

2. Software maintenance costs

Factors such as removing outdated functionalities, improving performance, software validation and testing, and fixing bugs determine the maintenance costs for the OCR software for data entry. This is a recurring cost that businesses need to pay to maintain the OCR solution's optimal functioning.

3. Training costs

This includes the training required for employees to leverage the OCR model and extract data. Some vendors provide training in-house, and some businesses outsource their training requirements to skilled professionals.

4. Additional cost

Besides these regular costs, businesses can expect costs for advanced features such as table extraction, handwriting recognition, and cloud processing functionalities. These costs can add up depending on the monthly document volume. 

Typical Use Cases of OCR Data Capture

Here are some industry-specific use cases and applications of OCR data capture systems: 

1. OCR in banking 

OCR technology in the banking industry overcomes many challenges and inefficiencies in day-to-day operations. These solutions streamline customer onboarding, compliance, loan application, accounting opening, and fraud detection processes with accurate and efficient data capture.

• Scans account opening forms and identity documents and extracts relevant data to onboard customers quickly and enable accurate documentation.
• Processes loan application forms and bank statements to capture borrower's identity details, income, and debt-to-income ratio
• Helps ensure KYC compliance by extracting borrower's name, address, and phone number and validating data with government and national databases
• Analyzes historical data and borrower's financial information to verify suspicious transactions and detect fraud

This way, OCR transforms banking processes and helps employees focus on strategic tasks such as loan underwriting, campaigns, marketing strategies, and compliance.

For instance, Grid Finance, a leading financial platform in Ireland, automated bank statement processing using Docsumo.Before implementing Docsumo, Grid Finance encountered challenges such as data entry errors and delayed loan approval due to manual data extraction.

Docsumo processed bank statements and payslips automatically for Grid Finance. 

The result?

• 93%+ touchless processing rate 
• 50+ manual hours saved every month 
• €5k/month reduction in processing costs

Take a look at the Grid Finance Case Study for more information

2. Accounts payable 

The accounts payable process is swamped with various documents, such as purchase orders, invoices, and purchase order requisitions. Utilizing OCR systems helps accountants automate data extraction tasks, save time, prevent errors, and enhance visibility into AP performance. 

Here is how OCR automates accounts payable processes: 

• Scans invoices, purchase orders, and requisitions to extract vendor name, vendor address, invoice number, PO number, and payment details
• Validates the extracted data with vendor databases and preset conditions to flag discrepancies and duplicates 
• Syncs the data into accounting software systems to avoid manual data entry errors and streamline payment processes

This automated OCR data capture process ensures faster invoice processing time, improves accuracy, and enhances relationships with vendors. 

3. Healthcare 

Leveraging OCR data capture in the healthcare industry processes significantly improves accuracy to ensure patient safety and improve diagnosis. OCR helps in the following ways:

• Digitizes medical histories, laboratory reports, doctor's notes, and patient forms and stores data in Electronic Health Records (EHR) 
• Processes healthcare insurance claims forms to extract accurate data and automate claims processing workflows 
• Extracts patient name, medication, and dosage from prescriptions to store data in a database accurately 

4. Commercial real estate 

The commercial real estate industry handles a variety of documents in various formats, templates, and layouts. OCR data extraction in the commercial real estate industry automatically adapts to different formats and captures required data to optimize operations:

• Processes lease agreements to capture lease renewal date, rent amount, tenant details, and security deposits and maximize occupancy rates 
• Extracts data from compliance reports and purchase and sale agreements to ensure compliance and avoid penalties
• Captures data from user manuals to facilitate real-time data analysis of equipment and streamline preventive maintenance processes

5. Government 

OCR in the government sector streamlines applications, digitizes public records and ensures compliance. It helps

• Digitize government records and convert them into editable text to ensure public transparency 
• Extract data from a wide range of application forms to deliver government services on time
• Ensure national and international compliance by maintaining accurate records of different documents 

These use cases and applications highlight the versatility of OCR systems, making them an indispensable tool for all industries. 

Is IDP a Better Alternative to OCR? 

While OCR may be adequate for an occasional task, IDP can manage high volumes of complex documents with greater efficiency and accuracy. Here are the reasons why IDP is a better alternative than OCR:

• Using IDP means you can extract structured data from unstructured documents with higher levels of accuracy than OCR alone.
• It's also very adaptable because it allows for extracting images, tables, and other types of data in many documents.
• IDP uses intelligent algorithms to extract the text from scanned images.
• It captures relevant information without errors and avoids missing any critical data.
• The high degree of automation involved enables faster processing times.
• IDP can analyze multiple document types without any pre-training or manual rule creation.
• IDP can be deployed across your entire business, regardless of industry or market sector. You can use it to extract data from customer service emails or purchase orders from suppliers in real-time.

Regarding accuracy, OCR software for data entry systems doesn't match what IDPs can do. Here is an overview of the comparison between OCR and IDP:

TABLE

How to Automate Data Capture with Docsumo?

Automated data capture is a core strategy for improving your conversion rates. If you're interested in automating your form processing, you'll want to take a look at Docsumo's software. 

It's a powerful tool that can help you leverage OCR (Optical Character Recognition) and Machine Learning (ML) technologies to automatically extract and process data from forms.

Automated form processing can save you hours of manual data entry, lower your costs, and more.

1. Upload Documents‍

You can upload documents that contain information about your customer profiles, like customer names and addresses.

2. Edit Fields‍

Remember to double-check all fields for accuracy to ensure accuracy in your data entry. For example, fix it if the parser classifies a data field incorrectly.

3. Validate Fields‍

If there are any errors in the information you capture on the form, fix them before moving on to the next step.

4. Review and Approval‍

Once you have captured every information on your form, it's time to review and approve it before moving on to the next step. This ensures that every last part of the information is accurate and there are no errors before uploading it.

5. Download CSV/Excel/JSON file formats‍

Docsumo lets you download the data in CSV/Excel/JSON formats for post-processing and analytics.

Streamline Data Processing Workflows with Docsumo's AI-based OCR Solution 

Embracing an OCR-based data capture system improves productivity and efficiency and gives businesses a competitive edge. You can serve clients better, reduce employees’ pressure to perform repetitive tasks, and increase the data accuracy rate. 

Docsumo, a powerful solution in the document processing industry, helps clients across different industries automate data capture tasks. The platform integrates OCR with AI technologies to support other languages, adapt to other formats, and ensure a 95%+ high accuracy rate. 

With Docsumo's pre-trained API models, you can extract data from any document without any ML model training. The system also supports effective customization to help you extract specific data and improve accuracy. 

Additionally, scale as your business grows and capture data from small batches to large volumes of documents without compromising processing speed. You can also integrate the system with existing business tools to automate data transfer and facilitate streamlined operations. 

Sign up for a 14-day free trial of Docsumo to leverage a 95% straight-through processing rate, customizable workflows, and seamless integrations.