Study on Artificial Intelligence (AI) in Indian Banking Sector with Special Reference to Punjab National Bank

by Sudipta Saha Roy
Assistant Professor in Commerce, Serampore College, Serampore, India

10.46679/978819573220304

Roy, S. S.(2023). Study on Artificial Intelligence (AI) in Indian Banking Sector with Special Reference to Punjab National Bank. In P.K. Paul, S. Sharma, E. Roy Krishnan (Eds.), Advances in Business Informatics empowered by AI & Intelligent Systems (pp 48-72). CSMFL Publications. https://dx.doi.org/10.46679/978819573220304

Abstract

The meaning of intelligence is the capacity to absorb and learn from experience which can be used as a tool to handle problems and fit into a new situation (Jhangiani et al., 2014). Artificial Intelligence (AI) is the technology that tries to copy logical functions which are prepared by human beings (D’Monte, 2018). In the past two decades, India’s digital banking sector has grown rapidly. The growing number of internet banking, mobile banking and payment app users, are the main catalysts behind the growth of digital banking. The rising demand for online banking has created opportunities for the implementation of AI in the Indian banking sector (Vijai, 2018). The main objectives of the present study are: (i) to discuss the concept of Artificial Intelligence (AI), (ii) to study the implication of AI in the Banking sector and (iii) to state the different aspects of AI in Indian Banking sector with special reference to Punjab National Bank (PNB). AI has played an important role in determining fraudulent accounts and reducing the gross NPA of Banks. The banking operations of PNB had been paralyzed in February 2018 due to fraud carried out by Nirav Modi and Mehul Choksi. After this incident, PNB introduced an AI-enabled audit system to eliminate the loopholes in their banking operations. The Gross NPA of PNB and the total number of frauds reported have decreased by 11.47% and 39% respectively, in the financial year 2021-2022 in comparison to the last year. The present study reveals that day by day, banks are adopting AI for personalized customer services and reducing errors in banking operations. Furthermore, AI can handle NPA Management through Big Data Analytics, which will help in strengthening the balance sheets of banks.

Keywords: Artificial Intelligence (AI), Banking Sector, Punjab National bank (PNB), Non-Performing Assets (NPA), Fraud

This work is a part of: Advances in Business Informatics empowered by AI & Intelligent Systems (Eds. P.K. Paul, Sushil Sharma, Edward Roy Krishnan)

© CSMFL Publications & its authors.

References

  1. AI in Banking, A Primer, Published By: Institute for Development and Research in Banking Technology(IDRBT), 2022, 7-31 https://www.idrbt.ac.in/wpcontent/uploads/2022/07/EAIML_Aug0103_2022.pdf
  2. Bandopadhyay, T., (2018), The Anatomy of PNB fraud. Retrieved May 25, 2019 https://www.livemint.com
  3. Baruah, A., (2018), Ai Application in the Top 4 Indian Banks, Tech Emergence; Retrieved www.techemergence.com/ai-applications-in-the-top-4-indian- banks/
  4. Chaudhary, S., & Singh, S., (2012), Impact of Reforms on the Asset Quality in Indian Banking, International Journal of Multidisciplinary Researches, Vol.2, issue. 1, January 2012, ISSN 22315780, 13-31 http://zenithresearch.org.in
  5. D’Monte, L., (2018), NSE bets big on AI, Block chain to mitigate algo-trading risks, (LiveMint, Retrieved from https://www.livemint.com
  6. Hamid, E., N., Ahmad, N., and Sanaz, P., (2012)Credit Assessment of Bank Customers by a Fuzzy Expert System Based on Rules Extracted from Association Rules, International Journal of Machine learning and Computing, Vol. 2, No. 5, October 2012, 19-26 http://www.ijmlc.org
  7. Jhangiani, R., Tarry, H., & Stangor, C. (2014). Principles of social psychology (1st international H5P edition). BCcampus OpenEd, [Vancouver], 19-21, ISBN9781774200155, 1774200155 https://opentextbc.ca/socialpsychology/
  8. Kumar, K. Suresh, Aishwaryalakshi, S. & Akalya, A. (2020), Impact and Challenges of Artificial Intelligence in Banking, Journal of Information and Computational Science, ISSN: 1548-7741, vol. 10, Issue 2-2020, 1101-1109. https://joics.org/VOL-10-ISSUE-2-2020/
  9. Messai, A.S. & Jouini, F. (2013), “Micro and Macro Determinants of Non-Performing Loans”, International Journal of Economics and Financial Issues, Vol.3, No.4, 852-860. https://www.researchgate.net/publication/286345094_Micro_and_Macro_Determinants_of_Non-performing_Loans
  10. Dass, R. (2012), Data Mining in Banking and Finance: A Note for Bankers, accessed on March 2012. http://iimahd.ernet.in/publications/data/Note%20on%20Data%20Mining%20%26%20BI%20in%20Banking%20S
  11. Rao, G., K., & Kumar, R., (2011) Framework to Integrate business intelligence and Knowledge management in banking industry, Review of Business and Technology Research, ISSN: 1941-9406 Vol. 4, No. 1, July 2011, 1-14. https://www.researchgate.net/publication/51961950_Framework_to_Integrate_Business_Intelligence_and_Knowledge_Management_inBanking_Industry
  12. Sabharwal, M. (2014), The use of Artificial Intelligence (AI) based technological applications by Indian Banks, International Journal of Artificial Intelligence and Agent Technology, Vol. 2, issue 1, 1-5, https://www.academia.edu/26053536/_The_use_of_Artificial_Intelligence_AI_based_technological_applications_by_Indian_Banks_
  13. Saraswat, D., & Srivastava, R. (2018). Non-Performing Assets in Public Sector and Private. Journal of Banking and Insurance Law, 1 (I), 4, 1-8, https://lawjournals.celnet.in/index.php/jbil/article/view/114
  14. Sengupta, R. & Harshvardhan. (2017), Non-performing assets in Indian banks: This time it is different, Indira Gandhi Institute of Development Research, Mumbai, WP-2017-019. 1-21, http://www.igidr.ac.in/pdf/publication/WP-2017-019.pdf
  15. Singh, A. (2013), Performance of Non-Performing Assets (PAS) in Indian commercial banks, International Journal of Marketing, Financial Services & Management Research, ISSN 2277-3622, Vol. 2, No. 9, September (2013), 86-94. https://www.scirp.org/(S(i43dyn45teexjx455qlt3d2q))/reference/referencespapers.aspx?referenceid=1859862
  16. Srivastava. S., & Chauhan, P., (2018), Institutional Factors influencing Non-Performing Assets (NPA) in Indian Banking Sector and use of Artificial Intelligence as a remedial tool, Indore Management Journal, Vol. 10, Issue 1, January-June 2018,46-56 https://www.iimidr.ac.in
  17. Vijai, C., (2018), Artificial Intelligence in Indian Banking Sector: Challenges and Opportunities, International Journal of Advanced Research (IJAR), ISSN No. 2320-5407,6 Jul. 2018, 1581-1587. https://doi.org/10.21474/IJAR01/8987

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