AI, blockchain, analytics transforming finance, banking in India

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The fast-paced technological advancements in India, especially in fields like artificial intelligence (AI), blockchain, and data analytics, have opened up new possibilities to transform traditional financial services and processes, India’s Economic Survey 2024-2025 pointed out.

AI and large language models (LLMs) have improved customer service with interactive chatbots and tailored experiences, while blockchain provides secure, transparent, and efficient transactions. Additionally, shifting consumer behavior and expectations—fueled by digital natives and growing demand for personalized, seamless, and convenient financial solutions—are pushing established firms and newcomers to innovate in order to stay competitive.

India’s Economic Survey, which examines national trends and aids in determining resource allocation, was presented by India’s Finance Minister Nirmala Sitharaman in Parliament on January 31. It was published one day prior to the announcement of India’s Union Budget, an annual financial report outlining the government’s planned spending, expected revenue, and expenditure for the upcoming fiscal year.

“Now the world is in the artificial intelligence (AI)-powered digital age, driven by decreasing data storage and processing costs, greater accessibility, and connectivity. These innovations can lead to higher automation and often enhance human decision-making speed and accuracy when correctly managed to mitigate risks,” the Economic Survey said.

“The use cases of AI and Machine Learning (ML) applications by banks in India range across areas such as credit underwriting, regulatory capital planning, liquidity management, fraud detection and prevention, risk assessment and management, portfolio optimisation, pricing models, and chatbots,” the survey added.

In November last year, the Reserve Bank of India (RBI) acknowledged an increased mention of artificial intelligence (AI)-related technologies in the annual reports of public sector banks, a space once more actively explored by private sector banks. In its October bulletin, the central bank’s report pointed out that “enthusiasm” for AI technologies among public-sector banks in India is now largely on par with private-sector banks, particularly in recent years.

For instance, Bank of Baroda, one of India’s prominent public sector banks, has introduced a generative artificial intelligence (AI)-powered virtual relationship manager (VRM) to enhance the digital customer service experience. The VRM acts like a relationship manager, advising clients about investments and available financial services.

This innovative VRM is a first in the local banking sector and aims to assist customers by providing real-time information about the bank’s products and services. It also helps identify customer needs for specific banking services and can assist with basic tasks like obtaining account statements, requesting chequebooks, applying for debit cards, and issuing interest certificates.

‘A few risks’

The Economic Survey stated that, along with the benefits, using AI in the banking system entails a few risks.

The black-box nature of AI systems can make it challenging to evaluate their reliability or challenge their decisions. This lack of transparency raises concerns about trust and complicates the validation of fairness and accuracy of AI decisions, making it difficult to audit or understand the algorithms that underpin these decisions.

Accountability issues arise when it’s hard to trace decisions to their origin or assign responsibility. Other risks include human resource concerns, such as insufficient human oversight, over-dependence on AI, and the erosion of human expertise.

Cybersecurity threats, malicious activities like synthetic identity fraud, rogue trading, and market manipulation are also major concerns. System risks are significant issues, such as the inability to intervene or manage market correlations.

“Establishing robust AI governance is the first and crucial step in addressing the challenges that come with the implementation of AI systems. Without an appropriate governance framework, AI systems may operate without clear guidelines or oversight, leading to potential abuse or misuse of technology,” the Economic Survey pointed out.

“As vulnerabilities could evolve with the pace of innovation and degree of AI integration in financial services, regulatory and supervisory effectiveness may take a backseat if financial regulators’ AI-related skills and knowledge do not keep pace with developments in this space,” the Survey added.

So far, the RBI has created a regulatory sandbox focusing on innovative technology products and services.

The RBI recently announced the establishment of a committee to create a Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) in the financial sector.

The RBI’s initiative comes as generative AI (GenAI) is projected to add $359-438 billion to India’s gross domestic product (GDP) by 2029-2030, highlighting the need for ethical and responsible use of the technology to support the country’s financial sector and economic growth.

The RBI has also introduced an artificial intelligence/machine learning (AI/ML)-based model, MuleHunter.AI, developed by the Reserve Bank Innovation Hub (RBIH), to tackle digital fraud. The AI model is also expected to help banks deal with the issue of mule bank accounts, a typical tactic fraudsters use to funnel the proceeds of their fraudulent activities.

In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.

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