Responsible and Trust Centric AI Governance for India’s Capital Markets
India’s capital markets are undergoing a historic transformation. With over 160 million investors, nearly USD 4 trillion in market capitalization, the world’s fifth‑largest equity market, 99% electronic transactions, and the largest derivatives volumes globally, the scale, speed, and complexity of Indian markets have reached unprecedented levels. India now operates one of the most technologically advanced market ecosystems in the world. It is truly representative of ‘India Shining’.
Participation is expanding, digital infrastructure is deepening, and the pace of innovation is accelerating. Artificial intelligence is increasingly embedded in how markets function: supporting regulatory oversight, strengthening compliance, enhancing risk management, and enabling scale with resilience.
As AI adoption becomes focal point, an important question comes to the fore: How do we ensure AI strengthens trust in India’s markets rather than undermining it?
The answer lies in building responsible, trust‑centric AI governance that aligns innovation with the public interest, investor confidence, and systemic stability.
Trust Is the Bedrock of Market Growth
Capital markets thrive on trust – trust that rules are applied consistently, risks are understood, and participants operate on a level playing field. In India, this trust has been carefully built over decades through robust regulation, institutional maturity, and an unwavering commitment to market integrity.
AI has the potential to reinforce this foundation. Applied responsibly, it can help regulators and institutions detect misconduct earlier, respond to emerging risks faster, and manage complexity at scale.
However, trust cannot be automated. It must be deliberately designed as a non-negotiable tenet into AI systems through thoughtful and sound governance, transparency, and accountability. Without these safeguards, AI risks becoming a source of opacity rather than confidence.
AI in Capital Markets: Opportunity and Responsibility
Across India’s capital market ecosystem, AI is already supporting critical functions such as:
- Market surveillance and anomaly detection
- Anti–money laundering and fraud prevention
- Regulatory reporting and supervisory analytics
- Risk, margin, and liquidity management
These use-cases directly affect investor protection and systemic stability. As a result, AI governance in capital markets is not just a technology consideration, it is a policy, regulatory, and societal concern.
Key questions demand attention:
- Can AI‑driven alerts, risk scores, and compliance decisions be clearly explained, audited, and challenged by regulators and market participants?
- Do AI systems deliver fair and unbiased outcomes across investors, issuers, and intermediaries – without distorting access, liquidity, or market behavior?
- Do regulated entities remain fully accountable for decisions influenced by AI, particularly in areas such as market abuse detection, client classification, and risk management?
- Are emerging systemic risks – such as correlated model behavior, algorithmic feedback loops, or AI‑driven market stress – properly understood, tested, and managed?
Addressing these questions is essential to sustaining confidence in an increasingly AI‑enabled market environment.
Principles for Trust‑Centric AI Governance
Trust‑centric AI is becoming essential to sustaining market confidence, regulatory credibility, and long‑term stability. A responsible approach to AI in India’s capital markets should be anchored in a few practical principles:
- Human Accountability at the Core
AI must remain a tool that supports, not substitutes human judgment. Whether in market surveillance, AML monitoring, or risk management, ownership of AI‑assisted decisions must rest clearly with SEBI‑regulated entities and market infrastructure institutions.
Accountability must be unambiguous. Decisions influenced by AI should be reviewable, challengeable, and correctable; thus preserving both investor confidence and regulatory credibility.
- Transparency and Explainability
Effective supervision requires that regulators, exchanges, and intermediaries can understand how AI systems generate alerts, scores, or recommendations.
Explainability is critical for auditability, regulatory review, and enforcement; especially where AI influences market access, trading restrictions, or compliance actions. Transparency strengthens trust without constraining innovation.
- Fairness and Inclusion
India’s markets serve a highly diverse investor base across regions, income levels, and varying degrees of digital literacy. AI models trained on historical data can unintentionally reflect structural biases.
Continuous testing, representative data practices, and strong governance oversight are therefore essential to ensure AI supports fair, inclusive, and non‑discriminatory participation in capital markets.
- Resilience and Market Stability
As AI adoption scales across exchanges, intermediaries, and clearing systems, the use of similar models and data sources can introduce new forms of systemic risk.
Governance frameworks must address model concentration, stress testing under volatile conditions, and robust human override and fallback mechanisms. In a high‑volume, high‑velocity market like India’s, AI resilience is inseparable from financial stability.
Strengthening Institutional Capacity
Responsible AI adoption is as much about people and institutions as it is about technology. India’s regulators and market institutions have demonstrated a strong ability to adapt to change. Building upon this strength will be critical.
Key Priorities include:
- Enhancing supervisory capabilities to assess and monitor AI systems
- Establishing clear, outcome‑based guidance on model governance
- Encouraging structured collaboration between regulators, market participants, and technology providers
Shared learning and regulatory clarity can enable innovation while maintaining high standards of market conduct.
Aligning with India’s Responsible AI Vision
India’s broader digital and AI ambitions emphasize trust, inclusion, and national resilience. Capital markets offer a powerful platform to demonstrate how these values can be operationalized in complex, high‑impact systems.
Trust‑centric AI governance supports:
- Investor confidence and participation
- Alignment with global regulatory expectations
- Long‑term market competitiveness and stability
Most importantly, it reinforces the credibility of market institutions in the eyes of citizens.
Looking Ahead: Designing Trust into the Future
AI will continue to evolve, but the principles that underpin strong markets remain constant. Trust, transparency, and accountability are not constraints on innovation, they are enablers of sustainable growth.
For India’s capital markets, the objective should not be rapid AI adoption alone, but responsible adoption that strengthens the system. By embedding trust‑centric governance into AI from the outset, India can set a global benchmark for how technology serves markets and the public interest, at scale.
The decisions we make today will shape investor confidence and market resilience for years to come. Getting AI governance right is not merely a technological imperative; it is a collective responsibility.
WrittenBy Sheenam Ohrie, Managing Director, Broadridge India
