- Introduction
Allocation of India’s Union Budget from last financial year for the Digital India Initiative has doubled to around USD 480 million, roughly translating to INR 3703 cr, for the dedicated growth of technology.[1] Additionally, India is believed to have the highest number of digital banking users across the world as of 2022, making us one of the most diverse customer base with a knack for inclusive financial growth.[2] With the ever-growing population, of which the majority is included in the formal banking sector, the country has a rapidly growing digital banking customer base with various advanced services and fintech products. The advent of Digital India has brought Artificial intelligence and its promotion to the public and private sectors.
This burgeoning population also underscores the need for labour-intensive processes rather than technology implementation. Replacing extant labour-intensive work with AI-based technology across all sectors can bring significant macro and micro losses. Therefore, it must be understood that AI is not about replacing human expertise but rather augmenting it, especially in financial and technological sectors such as banking in a country like India.
The World Economic Forum, in its annual meeting this year, deliberated on how Artificial Intelligence (“AI”) will drive an inclusive financial sector.[3] It emphasised that delegating routine tasks to AI will let financial experts focus on building a more innovative and focused approach to finance.
- Regulatory Landscape
From being an academic curiosity to integrating AI into almost every sector globally, the extensive use speaks for itself. The banking sector proved to be a pioneer in implementing and adopting all emerging technology use cases in India and worldwide. AI applications were predicted to aid the banking industry and save on potential costs worth USD 447 billion by the end of this year.[4]
The regulatory bodies in India for the banking sector are the Reserve Bank of India (“RBI”), the Securities Exchange Board of India (“SEBI”), and the Insurance Regulatory and Development Authority of India (“IRDAI”) overseeing the banking system, securities market, and insurance-reinsurance sector, respectively. These bodies have considered a regulatory sandbox approach while using emerging technologies such as AI and blockchain.
In 2018, the Niti Aayog was appointed by the Government of India (“GOI”) to lead laws governing AI and its ethical implications.[5] However, the pace at which policies should be ruled out seems to lag behind. Meanwhile, implementers have self-governed and self-regulated a framework to avoid non-compliance with the law and use emerging tech to their business advantage.
The Aayog recommended that the GOI facilitate work promoting research and application of AI and ensure the setting up of agencies or centres for developmental work. The 2021 report of the Niti Aayog laid down the need for self-governance with specific legal provisions for AI-based decision-making processes. Similarly, the Ministry of Commerce and Industry recommended establishing a nodal agency, data banks, and other policies to coordinate AI-related activities in India.
- AI Basics
AI is a branch of computer science that is powered by algorithms. Machine learning (“ML”) algorithms and data fed into AI enable the system to learn and evolve from its original programming. There are broadly three types of AI -
● Artificial narrow intelligence (“ANI”) - a narrow range of abilities;
● Artificial general intelligence (“AGI”) - on par with human capabilities;
● Artificial superintelligence (“ASI”) - more capable than a human.
Feeding data sets any of the above machine learning models to data is called training. The criteria for successful training is the ability to predict desired or previously unseen outcomes. Therefore, it also means that if any such model has been fed differentiated data, the system tends to hallucinate and process undesirable or unimaginable results.
- AI-enabled Segments
Generative AI, a part of ANI, can provide banks with an advanced banking landscape and simultaneously meet expanded risk management and compliance demands.
Banks leverage AI on the front end to ease customer identification and authentication through live chatbots and AI assistants, strengthen customer relationships, and provide preliminary insights. Such operations falling in front-end or middle-office applications are an area where there is an opportunity to save costs.
Any banking system operates through three main channels: the front office for conversational banking, the middle office for anti-fraud, and the back office for basic underwriting. AI-enabled middle-office banks use AI technology to detect and prevent payment fraud and improve processes for anti-money laundering (AML) and know-your-customer (KYC) regulatory checks. Moreover, ‘conversational payments’ on the UPI are expected to use an AI-powered system to add an extra layer of security. When launched, this will be a game changer in the payments landscape.
The State Bank of India (“SBI”) undertook one successful AI experiment, wherein it deployed AI, ML, and business analytics to expand its product offerings and improve customer satisfaction. The bank will deploy a NextGen Data Warehouse and Data Lake and explore new partnerships with fintechs and NBFCs for co-lending. It has also been announced[6] that the next version of the SBI YONO app will prioritise customer-centric design, hyper-personalized experiences, and innovative product offerings through AI/ML.
- Challenges
Among the roaring integrations with AI, one must not lose sight of the ethical dimension. Of particular interest is the integration with the banking sector, which is a highly regulated industry and, therefore, requires transparency, data security, accountability, and unbiased decision-making. Emerging technologies use AI to extract actionable insights and quantifiable predictions to aid the banking system in account opening/ closing, default, fraud, and customer departure. This would also mean that the AI has a huge repository of data.
AI penetration in the banking industry and its associated growth hinge on data literacy and the availability of AI talent, as there is no one fix-formula to integrate AI into any sector, let alone banking. The right mix of AI literacy and data availability will curate the kind of AI-assisted or even completely AI-driven processes. The financial sector possesses an advantage in embracing the surge of AI, and due to the differences in digital literacy levels and connectivity infrastructure, fintech banking has been adopted largely in urban areas.[7] This factor has also somewhere contributed to the reinforcement of Big Tech domination. Further, using AI and privately held big data by the urban tech giants to cater to customers with financial services can disrupt competition in the financial markets.
- Need for Regulations
Banking is especially apt for the use of machine learning techniques due to the abundance of both structured and unstructured data and the necessity for a thorough analysis to support its guidelines and policies. Integrating machine learning with fundamental banking fields like economics, statistics, and econometrics positions central banks to lead in AI advancements. The Bank of International Settlements, via their Monetary and Economic Department, published a paper on Generative artificial intelligence and cyber security in central banking.[8] It was found that the increasing sophistication and frequency of cyber threats and the advent of AI tools introduce novel risks and challenges to the security framework of regulatory and supervisory authorities.
The report of the RBI’s Working Group on FinTech and Digital Banking categorises fintech innovations into payments, clearing and settlement; deposits, lending and capital raising; market provisioning; investment management; and data analytics and risk management.[9] The constant need for AI regulations is due to their unpredictable nature, which may jeopardise human beings' natural rights. The working group suggested that AI has the potential to transform data analytics and customer experience in banking. It elaborated on how this digital transformation and innovation in banking, financial services, and insurance (BFSI) will revolve around three major aspects - Blockchain, AI, and the Internet of Things. With the onset of interconnected devices riding on self-learning and evolving AI and BlockChain keeping track of each and every transaction, banking will no longer be just apps, websites or physical branches.
Indian policymakers play key roles in delivering guardrails to the regulatory framework. Some features of AI and Banking integration are much debated, such as fairness, transparency, accuracy, consistency, data privacy, explainability, accountability, robustness, monitoring, updating, and the imperative of human oversight. The adoption of AI by banking regulators and institutions would have to keep a close eye on machine learning as AI systems to develop biases, which would negatively impact the quality of the results.[10]
Development and deployment of AI models need close human supervision commensurate with the risks that could materialise from financial institutions employing the technology. A comprehensive regulatory framework is needed to outline governance in this emerging market, as fractured regulation can also create loopholes. The regulation of AI must be based on cross-sectoral, clear premises that the government articulates through policy. India requires a policy that mandates AI operations to undertake continuous iterative risk assessments and requires them to use only error-free data sets for training.
[1] Uncovering the ground truth: AI in Indian financial services - https://www.pwc.in/assets/pdfs/research-insights/2022/ai-adoption-in-indian-financial-services-and-related-challenges.pdf
[2] Here are 4 ways AI is streamlining banking in India, World Economic Forum, December 2023 - https://www.weforum.org/agenda/2023/12/how-ai-can-streamline-indian-banking/
[3] How Artificial General Intelligence will drive an inclusive financial sector in Latin America, Jan 2024 -https://www.weforum.org/agenda/2024/01/ai-is-driving-the-evolution-of-a-more-inclusive-financial-sector-in-latin-america-here-is-how/
[4] The impact of artificial intelligence in the banking sector & how AI is being used in 2020, Business Insider, Dec 2019 -
[5] National Strategy for Artificial Intelligence, Niti Aayog, June 2018 - https://www.niti.gov.in/sites/default/files/2023-03/National-Strategy-for-Artificial-Intelligence.pdf
[6] SBI to use AI/ML to improve customer experience and operations, Tech Circle, June 2023 - https://www.techcircle.in/2023/06/06/sbi-to-use-ai-ml-to-improve-customer-experience-and-operations
[7] EY, “The Battle for the Indian Consumer”, October 2017 - https://www.ey.com/Publication/vwLUAssets/ey-the-battle-for-the-indian-consumer/$File/ey-the-battle-for-the-indian-consumer.pdf
[8] BIS Papers No 145, Generative artificial intelligence and cyber security in central banking, by Iñaki Aldasoro, Sebastian Doerr, Leonardo Gambacorta, Sukhvir Notra, Tommaso Oliviero and David Whyte, May 2024 - https://www.bis.org/publ/bppdf/bispap145.htm
[9] RBI “Report of the Working Group on Fintech and Digital Banking”, November, 2017 -
https://rbidocs.rbi.org.in/rdocs/PublicationReport/Pdfs/WGFR68AA1890D7334D8F8F72CC2399A27F4A.PDF
[10] AI Tames the Complexity of Regulation in Financial Services, Infosys - https://www.infosys.com/insights/ai-automation/documents/ai-tames-complexity.pdf