Invoice Processing Using Robotic Process Automation

Authors

  • Sagar Sahu  Computer Engineering, Datta Meghe College of Engineering, Airoli, Navi Mumbai, Maharashtra, India
  • Sania Salwekar  Computer Engineering, Datta Meghe College of Engineering, Airoli, Navi Mumbai, Maharashtra, India
  • Atharva Pandit  Computer Engineering, Datta Meghe College of Engineering, Airoli, Navi Mumbai, Maharashtra, India
  • Manoj Patil  Computer Engineering, Datta Meghe College of Engineering, Airoli, Navi Mumbai, Maharashtra, India

DOI:

https://doi.org//10.32628/CSEIT2062106

Keywords:

DataBot, Optical Character Recognition, Robotic Process Automation

Abstract

This paper describes our recent effort to develop a automative application to transform invoice processing in Finance operations. As a prime example of the technology’s potential for driving efficiency, Robotic Process Automation (RPA) can be applied to a number of finance and accounting operations, invoice processing. RPA DataBot can automate data input, error reconciliation, and some of the decision-making required by finance staff when processing invoices. At the same time, automation is able to limit errors in such processes and reduce the need for manual exception handling. UiPath’s RPA DataBot are able to constantly monitor a dedicated folder where invoices are saved by employees (or other DataBot) in PDF format. Once robots detect the presence of an invoice in the folder, they begin to extract information from the document. Using intelligent Optical Character Recognition (OCR) and natural language processing capabilities, DataBot are able to read out the information that is visible on the invoice. After robots extract the key information from each invoice, they use their credentials to open the company’s database or enterprise resource planning system, if not already open. The robots then start processing the invoices one-by-one by transferring over the relevant invoice information. During this whole process, the DataBot are also running background activities such as monitoring the dedicated invoice folder or its email address, performing basic checks to see if the company’s database is open, and verifying whether vendor information (e.g. VAT number) on the invoice matches what is already in the database.

References

  1. Ying Li, Muthu Muthiah, Arindam Routh and Chitra Dorai, ”Cognitive Computing in Action to Enhance Invoice Processing with Customized Language Translation”, 2017, IEEE International Conference on Cognitive Computing (ICCC), IBM.
  2. Hatem Hamza, Yolande Belaid and Abdel Belaid, “A Case-Based Reasoning Approach on Unknown Class Invoice Processing”,2007, IEEE International Conference on Image Processing, France.
  3. T. A. Bayer, H. U. Mogg-Schneider and Daimler-Benz, ”A Generic System For Processing Invoices”,1997, Fourth International Conference on Document Analysis and Recognition, Germany.
  4. Enes Aslan, Ethem Unver, Tugrul Karakaya and Yusuf Sinan Akgul,”An optimization approach for invoice image analysis”,2015, Signal Processing and Communications Application Conference,Turkey

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Published

2020-04-30

Issue

Section

Research Articles

How to Cite

[1]
Sagar Sahu, Sania Salwekar, Atharva Pandit, Manoj Patil, " Invoice Processing Using Robotic Process Automation, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 2, pp.216-223, March-April-2020. Available at doi : https://doi.org/10.32628/CSEIT2062106