Extraction from Income Verification Documents using OCR and IDP

Income verification documents are one of the most critical documents out there. In the case of manual data extraction from income verification documents costs hard work as well as lots of expenses. On working with advanced technology and systems, data extraction from a vital document can become a piece of cake. By using the system, the errors are meant to be minimized to almost zero percent. Digital data extraction could be a great option for low cost, less processing time, and uncompromised accuracy. However, data of income verification documents are meant to be extracted carefully to avoid financial complications. Extracting these data digitally will secure the contents and numerical records of an income verification certificate.

Receiving income verification documents is common for common people to big businesses. It is important to analyze and evaluate the data of these documents with care. Usage of modern data extraction tools like OCR and IDP have made the extraction process lucid and efficient. So, let’s discuss in this blog the question, how to data extraction from income verification documents using OCR and IDP. 

What are income verification documents?

Income verification documents are of mainly two types. A salaried person’s income verification data will be income documents, payslips, and employment verification. Mostly these documents are easy to extract. Data extraction Income verification documents of salaried individuals are less complex. This results in quick and efficient data extraction for salaried people. Whereas self-employed individual produces a complex and long income verification document. The document can comprise income tax return copies for the last two years, P&LA/Cs, balance sheets, computation of income statements, etc. In some cases, original sheets may need to be provided for income verification documents. For medium and big businesses business profiles are needed to evaluate a proper income verification document. Documents are needed to be evaluated and extracted with legitimate data extraction tool that supports modern digital ways like OCR and IDP. 

Automated Data Extraction from Income Verification Documents

The manual way of data extraction has become old and contemporary for the present digital world. It was a pretty hectic job to extract complicated data from income verification documents manually. Moreover, it used to take a lot of time to identify and extract the required data in less time. So, the best and most popular alternative for the job is automated data extraction from income verification documents. Automated data extraction makes the work more quick and efficient with the help of OCR and IDP. It can quickly extract images from pdfs and extract texts from pdfs. First of all, the tool will identify and analyze the collective required data that need to be extracted from the source. Data fields in an income verification certificate include gross salary, net salary, bank account, employer name, other credentials of the employer like addresses, employee name, employee address, employee contact number, address, salary periods, date of birth, total days, and hours worked, in/out service dates, hourly pay rate, issue date of documents and payslip, tax rate. There is a large pile of documents to extract in this whole field of income verification. Here machine learning and deep learning methods are applied to extract the data. OCR and IDP help to identify data locations and extract data values that are necessary for income verification.

How automated data extraction is made possible?

Physical and manual data have innumerable drawbacks and challenges. These drawbacks compelled people to introduce and innovate digital and automated data extraction from income verification documents processes. Modern technology has paved the way to understand and extract document layouts, required data present in the document. They are capable enough to extract valuable key information from the document in an automated way. With the help of automated data extraction software, extract images from pdfs and extract texts from pdfs has become a piece of cake. In recent years digital automated data is helping a lot of people and businesses in managing their data. Some new technologies like OCR and IDP are introducing easy ways to analyze and extract the exact data required from your income verification document. Moreover, with the advent of new systems like RPA, machine learning, AI technology we can provide people with a new field of automated data extraction. These innovations have way more potential to change your way of data management permanently. We help you in processing all your data from the Income Verification document using all these innovations and technology.

Drawbacks of automated income verification document extraction

Drawbacks are there in every system, no matter how perfect it looks. In the case of automated data extraction from income verification documents, people also face some serious challenges or drawbacks. Some basic drawbacks include scanning issues. Scanning images, charts, and text become a problem sometimes. Improper scanning is one of the common problems while extracting data through OCR.

OCR has a high accuracy rate for editable and searchable texts. But, sometimes it fails to deliver accuracy when texts are blurred or distorted. In that case, OCR shows inaccurate results after extracting. The authenticity of payslips, income verification documents are often not cleared in automated data extraction. Some documents can be fake and captured in low lighting conditions. Also, fraud in income certificates is difficult to detect by automated data extraction systems. It is unable to detect backgrounds of distorted or bent parts, identify edited or blurred text or number values. There are some algorithms and systems that help to detect these issues.

Another drawback of automated data extraction is it is not much efficient in key-value pair data extraction for income verification documents. Key-value extraction is effective for searching user-defined keys and their associated values. This form of extraction needs deep learning methods. Deep learning is also needed to understand income verification document IE. There are other drawbacks to using automated data extraction from income verification documents. With all modern technology and innovative features, automated data extraction sometimes fails to extract the desired data from income verification documents. This reduces the accuracy and work efficiency of the system. This can also affect businesses in many ways if unchecked. Due to easy and quick processing, there are chances to miss out on important data in a complex income verification document. All these drawbacks can be addressed and avoided by using new and effective software or tools.

How does the system run?

The entire system of data extraction from income verification documents runs automatically. Machine learning and deep learning play a major role in mobilizing the system of automated data extraction. New AI technology paves new ways to detect desired texts, values, data and extract them quickly. In these cases, RPA is the process that runs the system securely and comfortably. Robotic Process Automation or RPA is a process to automate data extraction using software robots that automate business operations that automate repetitive business operations. It boasts many business operations and reduces the cost of data extraction.

RPA speeds up the whole process and keeps the data secure. It works much better in transforming unstructured data to high-quality structured data. The data extraction system along with RPA is more effective when OCR comes along. Both RPA and OCR profoundly process these unstructured data and extract them automatically. AI methods help to run the automated data extraction system efficiently and fast. RPA uses software bots to detect and extract relevant data in the income verification document. The whole data extraction system becomes flexible with RPA as the robots can process multiple data formats. The extraction process system runs by a proper sequence with the help of RPA. It locates the data and identifies the relevant ones. Then, these data are prepared to process and transform through the system. All these data are extracted with better accuracy and quick speed.

The system also allows a combination of different data forms in the income verification document. Mainly the system enhances the business intelligence by running the whole system efficiently and easily. An automated data extraction system runs without any manual support to detect and process all the valuable data. RPA extractor automates the data extraction of income verification documents by selecting and processing the data with the help of OCR and IDP.

Tools used for data extraction from income verification documents      


Data extraction from income verification documents in OCR consists of both hardware and software ways. The hardware is used to capture the images and the software converts the images into document text. Mostly, it extract images from PDFs and also extract texts from pdfs. Also, there are some minor things in OCR that process the whole data manually. It works by digitalizing the data with a subsequent manual operation. It also works by identifying the required data and valuable numeric data from the income verification document. Besides, the OCR system works with a few quick and efficient features. It has some drawbacks like it fails to work with different templates, files types, and layouts. It also consists of human interventions to set template rules for different types of documents. OCR library can optimize and identify the data with the help of its AI model easily and efficiently.OCR or Optical Character Recognition is one of the basic tools for data extraction from income verification documents.


IDP or Intelligent Document Processing helps to automate data extraction from complicated and unstructured documents with manual and software-based techniques. In the case of data extraction from income verification certificates in IDP, the hardware process works by identifying and capturing the images or charts. The software process helps to extract the images or charts from pdf or extract valuable texts from PDFs. It is an upgraded and efficient version of OCR. OCR has several drawbacks and challenges. IDP or Intelligent Document Processing fills the missing spots where OCR technology lacks to execute. It can read, process, and extract different templates, files type, and layouts with ease. Both, IDP and OCR can extract data from several sources for income verification documents. IDP is .also excels in delivering high-quality and rectified data if passed through the pre-processing algorithms. In the case of Income Verification Processing collection and analyzing the valuable data is much important and needed human labor earlier. Instead, IDP mobilizes the entire data extraction process in an automated way.


Automated data extraction has benefitted lots of businesses in managing their data and extracting it with optimum efficiency. Seamless automation is one of the key benefits of automated data extraction. AI robots execute the whole process of extraction when users can relax back. Other key benefits are the ability to process a huge amount of data, hassle-free deployment. Overall automation of data extraction is the best way to extract valuable data from income verification documents.

It benefits users and businesses by delivering highly efficient, quick, and corrected data from the document. As both of the tools undergoes pre-processing methods that eventually increase the accuracy of the outputs. Pre-processing method requires a little bit of manual labor that works as a better effect in the case of efficiency. Today, the workflows of the companies are running high only due to the tools. Companies are capable of producing a quality of work to the clients. The productivity of the companies of the company is increasing gradually. Like manual data extraction, automated data extraction does not result in the reworking of tasks. Docextractor is the software that uses both of the tools and extracts data with quality outcomes. You must use and have a try at least once to experience the workflow of outcomes through Docextractor.

To conclude, data extraction may seem to be a hard job if done manually, but we, at Docextractor make the whole process much more efficient. Collecting and extracting your valuable data from your income verification certificate is no longer a matter to worry about. Docextractor provides you with new-age software with advanced OCR and IDP that delivers you your desired extracted data with almost 0% errors. Moreover, we value your time, and to fulfill that we identify and extract data from your income verification document quickly. These AI processes save you from the hurdle of extracting a huge amount of income verification data manually. Hope the above blog will help you out with the information and scopes regarding data extraction from income verification documents using OCR and IDP.



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