The Role Of OCR Technology In Robotic Process Automation Robotics & Automation News


(MENAFN- Robotics & automation News) The Role of OCR technology in Robotic Process Automation

Businesses need to handle vast amounts of data in their daily operations. This data is used in conjunction with process automation systems.

In order to streamline business operations, OCR (optical character recognition) software is used together with robotic process automation (RPA).

This synergy is transforming how companies extract, process, and utilize information from various documents and sources.

Understanding OCR Technology

OCR Technology is a game-changer in the world of data extraction. OCR software is used to electronically extract data from different types of documents.

This can include extracting data from an ID or passport using an ID scan , or electronically extracting data from a PDF file or an image. OCR software makes it possible to digitize and edit documents and locked files.

Modern OCR solutions offer a range of features that make them indispensable in today's business environment. These include multi-language support, the ability to handle various font types and styles, and even the capability to recognize handwritten text.

Advanced OCR systems can also maintain the original document's layout, ensuring that the extracted data retains its context and structure.

OCR Integration with RPA

Data-intensive processes that require repetitive tasks can be automated through the combined use of OCR and Robotic Automation Processes. RPA bots, which are designed to mimic human actions in digital systems, can leverage OCR technology to“read” and interpret information from various sources.

This combined use is effective in situations where data needs to be extracted from documents which are unstructured or incomplete.

Some common use cases where OCR and RPA shine together include:

  • Invoice processing and accounts payable automation
  • Customer onboarding and KYC (Know Your Customer) processes
  • Claims processing in insurance
  • Data entry and validation in healthcare
  • Form processing in government agencies

By automating these tasks, organizations can significantly reduce the time and resources required for data handling, while also minimizing errors associated with manual data entry.

Benefits of OCR in RPA

The benefits of combining OCR and RPA are profound for businesses. It drastically improves efficiency as a manual and repetitive task can be done without supervision or without adding additional employees to the task.

OCR-enabled RPA bots can process documents at a much faster rate than human workers, with a higher degree of accuracy. This speed and precision lead to quicker turnaround times for tasks and reduced errors in data processing.

The combination of OCR and RPA also results in significant cost savings for businesses. Savings are made on additional employees who would otherwise have to be compensated for doing a manual and repetitive task. This also increases productivity as employees can be allocated to other tasks.

Challenges and Limitations of Automating OCR

While the benefits of integrating OCR with RPA are substantial, it's important to be aware of potential challenges. One of the primary issues is the accuracy of OCR in dealing with poor-quality documents or complex layouts.

Handwritten text, unusual fonts, or documents with intricate designs can sometimes pose difficulties for OCR systems, leading to errors in data extraction.

Another challenge businesses face is the implementation of the OCR-RPA system. Upfront costs can be high, and maintenance may need to be performed on the system. Businesses would also need to provide training to employees who manage these systems, in order to ensure their correct use.

Future Prospects of OCR

By making use of emerging technology such as machine learning and artificial intelligence , businesses can ensure that the accuracy and automation of their system is robust and perfected.

For instance, there are emerging OCR systems designed specifically for medical records or financial documents, which can understand and extract industry-specific terminology and data structures more effectively.

Main image by Eric Prouzet on Unsplash

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