The AI Revolution in Indian Finance
Artificial Intelligence is rapidly reshaping India's financial sector, moving from experimental phases to core business operations. Banks, fintech firms, and investment houses are leveraging AI and Machine Learning (ML) for a wide array of functions.
These include customer onboarding, credit scoring, fraud detection, algorithmic trading, and portfolio analysis. This technological shift promises greater efficiency, cost reduction, and the potential to offer financial services to previously underserved communities. Public sector banks like SBI and Canara Bank are making significant investments in AI to enhance decision-making and improve customer engagement. The economic potential is vast, with projections suggesting AI could add nearly USD 500-600 billion to India's GDP by 2035, a significant portion of which would come from the financial services sector.
Identifying the Core Risks
Despite the benefits, the unchecked use of AI poses significant risks. A primary concern is algorithmic bias. If AI models are trained on biased historical data, they can perpetuate and even amplify discrimination, potentially leading to unfair exclusion from credit and other financial products. Another major issue is the 'black box' problem, where the decision-making process of a complex AI is opaque, making it difficult to understand or challenge its outputs. This lack of explainability is a serious concern for both consumers and regulators. Furthermore, the rapid adoption of AI introduces new security vulnerabilities, including the potential for creating deepfake content or fake financial statements to manipulate markets, as well as risks of data drift and adversarial attacks. As Chief Economic Adviser V. Anantha Nageswaran recently warned, the temptation for productivity gains should not come at the expense of safety and security.
The Regulatory Response: SEBI and RBI Step In
Indian regulators are moving from a watchful stance to active governance. The Securities and Exchange Board of India (SEBI) has already made significant moves. In February 2025, it introduced Regulation 16C, which makes any SEBI-regulated entity fully responsible for the integrity and compliance of the AI tools it uses. Following this, SEBI issued a consultation paper proposing more detailed guidelines covering governance, investor protection, and disclosure for AI usage in securities markets. Similarly, the Reserve Bank of India (RBI) is actively shaping the landscape. After publishing an advisory framework for responsible AI in August 2025, the central bank is now discussing more comprehensive guidelines. In June 2026, the RBI released a draft 'Guidance on Regulatory Principles for Model Risk Management,' proposing a governance framework for all models used by banks and NBFCs, with specific enhancements for AI systems.
The Mandate for Human Oversight
A central theme in the regulatory debate is the non-negotiable role of human oversight. Both SEBI's proposals and the RBI's draft guidance emphasize that accountability must remain with humans and institutions. The RBI has explicitly called for mandatory human oversight for AI-driven decisions through 'human-in-the-loop' arrangements. This includes building in capabilities for humans to override AI decisions and even 'kill-switches' to deactivate systems if they behave unpredictably. The regulator also warns against 'automation bias,' where humans place excessive trust in automated outputs. For customer-facing systems, the RBI has proposed that firms must disclose when a customer is interacting with an AI and provide an option to switch to a human agent. This principle ensures that technology remains a tool to support human judgment, not replace it entirely, especially in critical financial decisions.
Balancing Innovation with Stability
The core challenge for India is to strike the right balance: fostering the innovation that AI brings while safeguarding financial stability and consumer trust. The current regulatory approach appears to favour targeted amendments to existing laws rather than a single, sweeping AI Act. This allows for a more flexible and adaptive regime. Financial institutions are now being pushed to integrate AI risk management directly into their board-level governance structures. They will be held accountable for all models they use, even those procured from third-party vendors, which will require independent validation and due diligence. The debate is not about whether to use AI, but how to deploy it responsibly. This means ensuring fairness, transparency, and accountability are built into the systems from the ground up, a move that requires collaboration between regulators, financial institutions, and technology providers.
