Rise of AI chatbots in India’s Banking Sector

GS Paper III

News Excerpt:

The Reserve Bank of India (RBI) has released a report on Trends and Progress of Banking in India 2022-23 that studies the use of Artificial Intelligence (AI) in banks and how it has grown over time.

More details on the report:

  • An analytical study was conducted on banks’ annual reports by the RBI staff between 2015-16 and 2021-22 to assess the level of awareness and readiness for adopting AI in Indian banks.
  • This study employed a textual analysis method by matching keywords specific to the domain and utilizing named entity recognition techniques.
  •  It leveraged widely recognised AI and Machine Learning (ML) dictionaries and glossaries from sources such as Google Vertex AI, Google Developers, IBM, NHS AI Lab, and the Council of Europe.
  • Insights from Large Language Models such as ChatGPT and Bard were integrated into the analysis.

Chatbots take center stage:

  •  In FY17, only 5 banks had opted for this facility. This incrementally grew in the following years. Now, 26 banks have this facility.
  • Over 78.8% of the banks have adopted this facility — i.e., 26 out of the 33 scheduled commercial banks analysed.
  •  11 out of 12 public sector banks (PSBs) had some form of chatbot and virtual assistant by using AI and ML technologies, by the end of June 2023. On the other hand, only 15 out of 21 private sector banks (PVBs) had them.
  • The share of PVBs with chatbots was significantly higher than the share of PSBs in FY17. However, the situation reversed in the following years, with the trend of large-scale mergers among the PSBs appearing to have influenced the adoption of chatbots, as merged entities often adopt the technology from their acquiring banks.
  •  According to the RBI study, non-banking financial corporations have also started introducing chatbots for customer services.

AI's multifaceted impact:

  • The analysis using a word cloud indicates a significant emphasis by banks on automation.
  • This trend likely stems from the goal of improving efficiency and enhancing capabilities in the detection of fraud and other forms of predictive analytics, the RBI study suggests.
  • It is also notable that there is an awareness or potential for adopting emerging technologies such as Robotic Process Automation, the Internet of Things, and Natural Language Processing.
  • A key application of AI in various service sectors is the use of chatbots, which are capable of engaging in conversations with human users in natural languages, either via text or voice.

Risks and challenges:

  • The study ends with a cautionary note. AI in finance might heighten existing risks and introduce new ones, such as consumer protection concerns.
  • The opaque functioning of AI models complicates compliance with laws, regulations, and internal controls in financial firms.
  • These models could trigger market shocks and amplify systemic risks, particularly in terms of procyclicality, the study warns.

Conclusion:

Improved client experiences and increased efficiency are anticipated from the banking sector's rapid adoption of AI in India. Although possible risks should be considered carefully, the sector is well-positioned for future development and innovation due to the favorable influence on operations, risk management, and customer service.

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