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Rise of AI in Indian banking: insights into adoption trends and financial health

The adoption of Artificial Intelligence within the banking sector is gaining significant momentum, particularly among private banks, as highlighted by recent observations from Reserve Bank of India (RBI) staff members. Their findings indicate that factors such as asset size and the Capital Risk-Weighted Assets Ratio (CRAR) are influential in the rate at which banks adopt AI technologies.

According to RBI officials Shobhit Goel, Dirghau K. Raut, Madhuresh Kumar, and Manu Sharma, the size and financial health of a bank positively correlate with its focus on AI, reflecting the impact of economies of scale and the availability of investment necessary for technological advancement. Their study, titled “How Indian Banks are Adopting Artificial Intelligence?”, published in the RBI’s latest monthly bulletin, revealed that larger banks tend to have a greater propensity for AI adoption. This trend is evident from the positive and statistically significant relationship between AI scores and the asset sizes of banks.

The study aligns with the resource-based theory, which posits that organizations with more substantial resources are more likely to invest in innovation and advanced technologies like AI. Additionally, survey results support the notion that banks with larger asset sizes demonstrate a higher adoption rate of AI. Larger banks, facing challenges in coordination across various verticals, are likely to realise greater net gains from integrating such technologies and data systems, thereby increasing their motivation to adopt AI solutions. Conversely, the authors suggest that smaller banks may encounter challenges in adopting these technologies due to higher fixed costs and a lack of economies of scale.

The Role of CRAR in AI Adoption

The study also examines the significance of CRAR, which serves as a proxy for a bank’s capital adequacy and reflects its financial health. The findings indicate a positive relationship between CRAR and AI scores, suggesting that well-capitalised banks are better positioned to assume investment risks in new technologies. These banks benefit from adequate capital buffers and the confidence required to pursue AI solutions.

Increasing Emphasis on AI in Banking Reports

An analysis of annual reports from Indian banks spanning the period from 2015-16 to 2022-23 demonstrates a marked increase in the use of AI-related terminology. The RBI study noted that the frequency of such keywords in the annual reports of private sector banks surged nearly six-fold in the 2022-23 reports compared to those from 2015-16. Public sector banks (PSBs) have also shown a significant increase, with mentions of AI technologies more than tripling during the same period.

The officials found that in some public sector banks, interest toward AI technologies has improved to the same levels of private sector banks, mainly in the past several years. The application of text-mining techniques to their analysis raised some interesting findings, one of which is that most of the banks are focusing on automation. This can be because of harmonious efforts by these banks for efficiency gain and minimizing human intervention in banking process.

Main Areas of Thrust under AI Adoption

Data analytics is a prime focus area, and it has immense implications for fraud detection and predictive analytics. Though cloud-based and big data technologies remain in the center ring, ever more people come to see the opportunities available with newer AI and ML technologies. RPA, IoT, and NLP are gradually gaining more popularity among banks at least in the past few years.

In other words, a gradual embracing of AI technology in the Indian banking industry signals a greater leap into modernisation and improvement. The results of this RBI study reveal that the driving factors behind this include asset size and financial health; thereby pointing to a more all-encompassing trend of improved efficiency, security, and customer servicing in the banking sector.