RBI 2022-23 report on the trends and progress
The 2022-23 report on the trends in, and progress of, banking in India, which was released on Wednesday by the RBI, studies the use of Artificial Intelligence in banks and how it has grown over time.
To assess the level of awareness and readiness for adopting AI in Indian banks, an analytical study was conducted on banks’ annual reports by the RBI staff between 2015-16 and 2021-22.
This study employed a textual analysis method by matching keywords specific to the domain and utilising 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.
Additionally, insights from Large Language Models such as ChatGPT and Bard were integrated into the analysis.
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.
Adoption of AI in the banking sector
AI tools are extensively adopted and heavily utilised in areas such as fraud detection, optimising information technology operations, and digital marketing.
The study argues that banks can improve efficiency and provide better customer experiences by leveraging these applications.
The use of ML techniques for real-time analysis of customer transactions enhances the estimation of default risks.
This bolsters their risk management strategies, the study suggests.
The study also 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.
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