Optical Character Recognition

9 Key Advantages of OCR-Based Data Entry

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9 Key Advantages of OCR-Based Data Entry

Although manual data entry is the backbone of many businesses out there, the process is plagued with inefficiencies such as slow collaboration, reduced productivity, security risks, a lengthy turnaround time, and human errors, among many others. 

OCR-based data entry introduces automation into the workflow, increases staff productivity with end-to-end digitization without manual input, and lowers operational costs while reducing the processing time from weeks and days to 30-60 seconds. 

Let’s dive deeper and understand the benefits of OCR data entry in document processing. 

What is OCR-based data entry?

Optical Character Recognition (OCR) software extracts texts and numerical data from scanned files, physical documents, and images, and converts them into machine-readable and editable formats. With a slight modification, the process can be fully automated. thus reducing the need for a data entry task force.

OCR-based data entry is widely used in paper-dominated industries like banking, lending, insurance, healthcare, and real estate, among many others. The system is ideal for handling documents such as ACORD forms, bank statements, medical records, invoices, and other contracts. 

Advantages of OCR-based data entry

Along with automation, OCR-powered data entry offers a host of benefits, such as:

1. Increased efficiency and time savings

OCR software improves business efficiency by delivering well-structured and formatted data. Along with eliminating the need for manual labor to sort paper documents, it saves time and effort, leading to efficient data entry. 

The optical character recognition software archives and stores extracted data that can be easily retrieved. Employees save time that would otherwise go in manually searching for these documents. The result is that time spent on data extraction and retrieval can be redirected toward core business activities. 

2. Enhanced accuracy and data quality

Automated data entry using optical character recognition extracts data with more than 99% accuracy. Alongside addressing issues like data loss and inaccurate or outdated data, it processes and extracts data in real-time from the documents. 

The absence of human intervention reduces the likelihood of erroneous data entries, resulting in more precise and reliable data quality. 

The pre-processing techniques of OCR also improve the quality of the documents. Here are the pre-processing steps. 

A) Binarization 

Converts the scanned images into black and white, making it easier to read and extract texts in this mode. 

B) Rescaling

Resizes the image dimensions to 200-600 DPI to ensure that the OCR extractions yield the best results. 

C) Denoising

Removes unnecessary noise, such as blemishes or marks. 

D) Skew Correction

Corrects the document alignment by slightly rotating the scanned document in the desired direction. 

3. Cost savings and resource optimization

Incorporating an OCR data entry service into your business is a cost-effective solution, as it eliminates the need to hire additional professionals for data extraction and entry. Data validation, extraction, and processing are automated and can be done at scale 24/7 without manual intervention. 

The system reduces expenses for shipping, printing, and copying manual documents. By digitizing documents, it allows for the reclamation of office space that would otherwise be occupied by bulky paper files. 

An added benefit is that OCR systems store the data securely in the cloud, saving on costly data recovery processes. 

4. Versatility and compatibility

The automated data entry process is highly versatile as it can convert handwritten forms, printed texts, scanned files, and images into formats like-

  • .DOC 
  • .DOCX 
  • .XLS 
  • .XLSX 
  • .TXT 
  • searchable .JPEG 
  • .PNG 
  • .TIFF

By integrating with third-party systems such as Zapier, Google Sheets, Salesforce, Stripe, and Xero, to name a few, the system allows the data to go downstream for further processing. 

5. Scalability in handling large volumes

Needless to say, OCR-based data entry is highly scalable. The document processing bandwidth can be steadily increased as your company grows. Eventually, it can process thousands of documents, validate data across hundreds of data points, and prepare them for data entry within a few minutes.

Docsumo’s high straight-through processing (STP) rate of 95% enables companies to process documents and prepare them for data entry within 30-60 seconds, irrespective of the volume. Being powered by machine learning (ML) algorithms, the efficiency and accuracy rate steadily increase as the volume of documents increases due to their adaptive nature. 

In the case of a lower volume of documents to be processed, the plan can be downsized. 

6. Data validation and verification

Unlike manual entry, the data extracted through optical character recognition technology instantly undergoes validation against business rules and available databases. Verification processes, such as data matching with existing public records, are carried out to ensure accuracy. Any inaccuracy or mismatch is flagged for manual check. 

For instance, when an automated OCR system is extracting data from invoices, the extracted information, like the final payment tally, order number, quantity, and dates, is matched with those present in the purchase orders (PO) and goods received notes (GRN) for validation. 

In cases of verification, the system compares the available data in the public database to authenticate the identity of a person applying for a loan or opening a bank account. 

7. Data analytics and insights

Advanced OCR platforms for document processing and data validation offer analytics features to analyze the extracted data and generate insightful reports. These reports are used by C-suite personnel, finance, and accounting teams to make strategic and financial decisions. 

For example, a finance company can use OCR software to digitize loan approvals and analyze lending patterns, helping them identify popular loan instruments and plan marketing strategies accordingly. 

Similarly, an insurance company can use OCR technology to extract data from claim forms and analyze trends in claim types, leading to improved risk assessment and fraud detection.

8. Compliance and security

End-to-end data encryption ensures the extracted information is safe from malware attacks, cybercriminals, and brute-force hacking. Most data-based OCR platforms are compatible with regulations including GDPR, HIPAA, and SOC-2. 

Docsumo’s OCR-based data entry is compliant with the strictest privacy laws of the European Union as well as the US. And, HIPAA compliance makes them eligible to offer OCR services to healthcare companies.

9. Disaster recovery

Storing data digitally in secure servers or distributed systems enhances data maintenance and protection. In times of sudden urgency or natural disasters, the digitized data can be swiftly retrieved, ensuring seamless business continuity even under challenging circumstances. 

This safeguard against data loss allows businesses to operate without interruptions, minimizing potential disruptions and safeguarding critical information.


To sum it up, implementing OCR-based data entry- 

  • Increases overall productivity of the workforce 
  • Increases accuracy along with the quality of the extracted data
  • Reduces costs and increases ROI
  • Integrates with existing business software either using smart APIs or native integrations
  • Offers flexible scalability options 
  • Ensures compliance with GDPR and SOC-2 regulations
  • Provides backup data storage in case of unforeseen mishaps. 

If these 9 reasons weren’t compelling enough, here’s a 14-day free trial of Docsumo’s  Intelligent OCR system to convince you. 

Suggested Case Study
Automating Portfolio Management for Westland Real Estate Group
The portfolio includes 14,000 units across all divisions across Los Angeles County, Orange County, and Inland Empire.
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Pankaj Tripathi
Written by
Pankaj Tripathi

Helping enterprises capture data for analytics and decisioning

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