Robotic Process Automation (RPA) involves the use of technology where software robots can emulate humans. This allows systems to do the work that humans do like data entry, validation, etc. In the competitive world of finance, RPA can be very helpful in improving operational efficiency and reducing costs.

Bahaa Abdul Hussein highlights key issues related to the use of RPA in the financial and banking sector are discussed below.

RPA is not necessarily a game changer 

While there is no doubt that RPA offers automation benefits, it does have limitations. There is still manual work involved as in data extraction and processing of documents. This puts pressure on businesses as they still need to use manual work to ensure processes happen smoothly.

IPA can fill the gap 

IPA or Intelligent Process Automation ensures the drawbacks of RPA are addressed. It makes use of Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) to accomplish what RPA cannot. Particularly, in the field of document processing RPA still requires human intervention.

This is where Intelligent Document Processing (IDP) can help. This platform can ensure total automation thereby freeing employees from these tasks, so they could focus on core tasks. The use of Optical Character Recognition (OCR) allows the system to read documents and decipher text and images.

The finance and banking sector can enjoy powerful benefits with IDP. The following explains how the financial sector can benefit from IDP.

  • IDP allows finance and banking organizations to capture data effortlessly from any kind of document, including digital forms. It thus does away with the requirement of manual effort.
  • The use of OCR can help the system categorize documents automatically.
  • Since manual processing is done away with, transactions can happen faster. This improves speed and efficiency.
  • Automation ensures greater accuracy and allows transactions to be authorized precisely.
  • The system can read customer emails and extract data from it. This can be used to process customer requests and send it to the right team to handle.
  • The intelligent processing allows the organization to quickly recognize cross-selling and upselling opportunities. This allows finance and banking businesses to improve revenue.

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