Artificial Intelligence ('AI') is rapidly reshaping the financial sector, powering everything from automated credit assessments and fraud detection to personalized customer experiences and algorithmic trading. For India's vibrant fintech ecosystem, AI promises unprecedented efficiency and scale. While these innovations create opportunities for faster and more efficient services, they also raise important challenges. Questions of accountability for third party AI models, risks of bias in training data, lack of transparency in decision making and vulnerabilities around consumer protection and data security have become increasingly pertinent. Regulators worldwide are grappling with ideas to foster innovation without compromising financial stability and consumer trust.
This article highlights the significance of the Framework for Responsible and Ethical Enablement of Artificial Intelligence ('Report'), key recommendations of the Report, state of AI adoption and challenges, it's impact on sectors such as Micro, Small and Medium Enterprises ('MSMEs') and Regulatory Technology ('RegTechs'), it's treatment of outsourcing challenges in AI adoption and how the framework aligns with global regulatory approaches.
Background
In a move set to shape the future of AI in finance, the Reserve Bank of India on 13 August 2025, released the report of it's Committee, chaired by Professor Pushpak Bhattacharya of IIT Bombay, on the Framework for Responsible and Ethical Enablement of Artificial Intelligence ('FREE- AI'). The Report lays down a comprehensive roadmap for embedding AI into India's financial sector.
The RBI on 6 December 2024 via Statement on
Developmental and Regulatory Policies constituted a committee of
experts from diverse fields to develop FREE-AI which aimed to
recommend a robust, comprehensive and adaptable AI framework for
the financial sector.
It undertook extensive surveys and consultations with regulators,
financial institutions and technology experts before finalizing its
recommendations.
The report envisions a future where AI enhances financial inclusion through multilingual, multimodal tools and drives efficiency across operations, fraud detection, compliance and more. It strikes a delicate balance ensuring AI's benefits, such as broader credit access and improved service delivery, are harnessed without undermining fairness, transparency or systemic stability.
Core principles: The '7 Sutras'
At the heart of the report lie the seven sutras or guiding principles designed to anchor AI adoption in the financial sector:
1. Trust is the Foundation
2. People First
3. Innovation over Restraint
4. Fairness and Equity
5. Accountability
6. Understandable by Design
7. Safety, Resilience and Sustainability
These principles transcend mere slogans, forming the ethical backbone of the subsequent 26 actionable recommendations grouped across six strategic pillars.
Strategic pillars and key recommendations
The committee's recommendations are organized around six broad pillars, reflecting both the opportunities and risks of AI in finance. Three of these pillars focus on enabling innovation, while the other three are aimed at building safeguards.
Innovation focused pillars
On the innovation side, the report focuses on the following:
* Infrastructure: The Report proposes the creation of a digital public infrastructure and financial sector specific data platforms, including integration with initiatives like AI Kosh, to support trustworthy Indian AI model development.
* Policy: The Report calls for enabling adaptive policies, including the establishment of an AI innovation sandbox for safe experimentation along with homegrown AI models and a dedicated development fund for India specific solutions.
* Capacity: The Report also urges capacity building within regulated entities and regulatory bodies, particularly at the board and C-suite levels, to ensure AI literacy and readiness.
Risk mitigation pillars
On the risk mitigation side, the report focuses on the following:
* Governance: The Report recommends board approved AI policies within financial institutions and the issuance of a consolidated RBI issued AI guidance document for uniform standards.
* Protection: The Report further recommends that consumers be informed when engaging with AI systems, accompanied by enhanced cybersecurity, consumer protection and AI specific audit mechanisms.
* Assurance: The Report proposes robust AI audit frameworks, expanded product approval processes and augmented business continuity plans that account for AI model performance degradation.
Notably, to ensure continued oversight, the committee has recommended integration of AI tools with UPI and other digital public platforms, as well as forming a multi stakeholder committee under the RBI to monitor AI evolution and emerging risks proactively.
AI and Outsourcing
The growing reliance on third party AI services by financial institutions raises another important regulatory challenge, particularly around accountability and governance. A key question is whether use of third-party AI services amounts to outsourcing and who should monitor the use of sensitive data for model training and decision making. Training AI on local institutional datasets risks embedding bias, while training on large, shared datasets raises privacy concerns. To address this, the Report proposes that the RBI makes available anonymous common datasets for training. Importantly, the principle that boards and senior management remain ultimately accountable for third party activities also applies to AI. Financial Institutions are therefore expected to validate third party models as rigorously as their own, with contracts requiring disclosures on important aspects. The Report builds on RBI Guidelines on Managing Risks and Code of Conduct in Outsourcing of Financial Services by banks ('RBI's Outsourcing Guidelines'), clarifying that use of third-party AI models within an institution's own systems is not outsourcing per se, but when services are outsourced and those providers use AI, this falls squarely within outsourcing norms. The Report notes that outsourcing agreements at present does not explicitly cover the AI- specific governance, risk mitigation, accountability and data confidentiality and thus, recommends AI specific enhancements in outsourcing agreements, covering these aspects, including algorithmic bias and use of AI by third-party vendors and their subcontractors.
The Report has set an encouraging while cautious regulatory tone with it's call for a 'tolerant supervisory stance', allowing for first time AI errors from institutions provided sufficient safety measures are in place, underscoring RBI's intent to promote innovation without complacency.
Comments
The FREE-AI report is more than a policy document; it is a strategic blueprint for balancing innovation with responsibility in India's financial sector.
The Report is also expected to influence several ongoing digital initiatives. The proposed framework complements the Fintech Association for Consumer Empowerment (FACE) Code of Conduct for RegTechs, aligning industry self-regulation with RBI's ethical AI principles and making integration with regulated entities smoother. The Report also interacts with the existing RBI sandbox framework. The committee's proposal for an AI Innovation Sandbox differs from RBI's existing financial sector sandbox. While the latter allows live testing with real users under controlled conditions and limited regulatory relaxations, the proposed sandbox would act as a safe experimentation environment for AI solutions without offering such relaxations. However, AI applications can still be admitted into regular regulatory sandbox.
Further, for MSMEs, the Report could also strengthen both Open Network for Digital Commerce (ONDC) and Open Credit Enablement Network (OCEN) by enabling more reliable digital marketplace tools and fairer AI driven credit assessments. This has the potential to improve access to finance and visibility for small businesses, while the report's emphasis on transparency and accountability helps guard against risks of bias and misuse.
The framework also reflects the global momentum towards responsible AI governance, its emphasis on accountability, transparency and risk management is consistent with the OECD's recommendations on AI in finance in it's report titled 'Regulatory Approaches to Artificial Intelligence in Finance' and it resonates with the Bank of England's analysis on 'Financial Stability in Focus: Artificial intelligence in the financial system' which underscores the need for resilient governance and systemic oversight. In doing so, the report not only strengthens India's regulatory position but also places it in line with international best practices, reinforcing trust in the use of AI across the financial ecosystem.
In conclusion, by combining enabling infrastructure, clear governance mandates and forward-looking regulatory tone, the RBI has set the stage for AI adoption that is not only technologically advanced but also ethical, inclusive and resilient. The coming phase will test the sector's ability to face steep resource and capability barriers. If implemented in both letter and spirit, FREE-AI could position India as a global leader in building a financial ecosystem where cutting edge AI thrives without eroding public trust.
The Report of the committee can be accessed here.
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