From Tokenised Bonds to AI: SEBI’s Next Phase of Regulated Financial Innovation
From testing tokenised corporate bonds to exploring an artificial intelligence sandbox, SEBI’s technology agenda points towards a financial market where innovation must be matched by stronger governance, operational resilience and investor protection.
India’s financial markets are entering a phase in which the next set of reforms will be shaped as much by technology as by regulation. As digital infrastructure changes how securities are issued, held, traded and settled, the Securities and Exchange Board of India (SEBI) is exploring ways to accommodate innovation while maintaining the safeguards on which market confidence depends.
On October 15, SEBI Chairman Tuhin Kanta Pandey outlined the regulator’s priorities, including a review of listing regulations, stronger monitoring of funds raised through public issues, improvements to corporate bond market liquidity and the exploration of an artificial intelligence (AI) sandbox. The proposed sandbox would provide a controlled environment in which applications could be tested, risks assessed and appropriate safeguards developed.
These plans follow the launch of SEBI’s Demat 2.0 pilot for tokenised corporate bonds in September. Together, the initiatives highlight a broader regulatory question: how can emerging technologies be incorporated into financial markets without weakening the standards of transparency, accountability and investor protection?
Demat 2.0: Testing Tokenisation Within the Securities Framework
SEBI’s Demat 2.0 initiative provides a practical example of how the regulator is approaching technological innovation. Launched on September 10, 2026, in collaboration with the Reserve Bank of India (RBI), the pilot explores the use of distributed ledger technology (DLT) to represent corporate bonds as digital tokens and bring securities transactions closer to their settlement processes.
In conventional securities infrastructure, ownership records, transaction processing and fund settlement can involve multiple systems and intermediaries. Tokenisation can enable ownership and transfer records to be maintained on a shared digital ledger, potentially reducing reconciliation requirements and allowing certain processes to be automated.
Under Demat 2.0, the underlying corporate bond retains its existing legal character and investor rights. The technology changes the way the security is recorded and transferred, rather than turning the bond into an entirely different investment product.
The pilot combines tokenised securities with settlement through the RBI’s central bank digital currency infrastructure and the use of smart contracts for specified processes. Its broader objective is to assess whether closer integration between securities and payments can improve settlement efficiency and reduce operational friction.
The initiative has already moved beyond the conceptual stage. By September 2026, three issuers — REC, Larsen & Toubro and IIFL — had issued tokenised corporate bonds aggregating ₹1,025 crore under the pilot. The subsequent phase is intended to facilitate secondary-market trading of tokenised corporate bonds, including retail participation.
However, the longer-term significance of tokenisation will depend on more than the ability to represent securities digitally. Its practical value will be determined by how effectively the infrastructure supports reliable ownership records, secure transfers, operational continuity and the protection of investor rights.
What an AI Sandbox Could Mean for Financial Markets
While Demat 2.0 tests a specific application of distributed ledger technology, the proposed AI sandbox could provide a broader framework for examining how artificial intelligence can be used in financial markets.
An AI sandbox is generally a controlled testing environment in which developers and regulated institutions can evaluate applications under defined conditions before deploying them more widely. Depending on its eventual design, such an environment could help assess the reliability of AI systems, identify potential risks and determine what safeguards are necessary for their use in regulated activities.
In financial markets, potential applications range from fraud detection and surveillance to compliance monitoring, risk analysis and the identification of unusual trading patterns. AI tools could help process large volumes of data and flag activity that warrants closer examination by compliance teams or market supervisors.
For a regulator, controlled testing can offer a way to understand both the capabilities and limitations of these systems before their adoption becomes more widespread. It can also help identify where human review, audit trails, data controls and clearly assigned responsibility are necessary.
The distinction between testing an application and authorising its unrestricted deployment remains important. The details of SEBI’s proposed sandbox, including its eligibility criteria, scope and operating conditions, have yet to be established publicly. Its eventual impact will therefore depend on the framework the regulator develops.
The proposal also sits within a wider shift towards technology-enabled financial supervision. As market participants adopt more sophisticated systems, regulators need the capacity to assess how those systems operate, where they may fail and whether their use introduces risks that conventional oversight mechanisms may struggle to identify.
Innovation Must Be Matched by Accountability
Tokenisation and AI address different aspects of financial market infrastructure, yet both raise a common set of regulatory questions.
For tokenised securities, these include the integrity of ownership records, the security of digital infrastructure, the treatment of operational failures and the ability to resolve disputes. Interoperability between systems will also matter as digital securities move across platforms and involve multiple institutions.
AI introduces a different set of concerns. Models may produce inaccurate outputs, reflect biases in their underlying data or make decisions that are difficult to explain. Dependence on external technology providers can add further risks relating to cybersecurity, data access, business continuity and the ability of regulated institutions to maintain oversight.
These issues become particularly significant when technology is embedded in activities that affect trading, settlement or investor outcomes. An automated process may improve speed, yet a failure can also spread quickly if the controls around it are inadequate.
A controlled testing framework can help identify such weaknesses before wider deployment. However, testing alone cannot replace ongoing monitoring, clear accountability and appropriate risk management.
For regulated entities, the central requirement will remain the ability to demonstrate that their systems operate within applicable regulatory obligations. The use of an external vendor, an automated model or a distributed ledger does not remove responsibility for compliance and market integrity.
The Wider Market Context: Access, Liquidity and Investor Protection
SEBI’s technology initiatives form part of a broader reform agenda aimed at making India’s capital markets more efficient and accessible.
At the October 15 event, Pandey noted that India’s market capitalisation had risen nearly fivefold over the preceding decade to ₹472 lakh crore. The country had more than 15 crore unique investors, while mutual fund assets had reached ₹83 lakh crore.
As participation expands, the regulator faces the task of ensuring that market infrastructure and oversight evolve alongside the scale and complexity of activity. Simplifying compliance, strengthening disclosure requirements and improving liquidity in corporate bonds are part of that effort.
Tokenisation could contribute to this objective if it makes certain processes more efficient and supports more integrated market infrastructure. An AI sandbox could similarly help the regulator and market participants understand how emerging tools can be used responsibly.
Neither initiative, however, guarantees greater liquidity, wider participation or lower costs. Those outcomes will depend on implementation, market adoption, the quality of safeguards and the ability of institutions to operate the systems reliably.
Investor awareness remains another important consideration. According to SEBI’s Investor Survey 2025, only 36 per cent of investors had moderate to high knowledge of securities markets. Easier digital access must therefore be accompanied by clear disclosures and investor education that help individuals understand the products they use and the risks they assume.
From Experimentation to Market Readiness
SEBI’s emerging technology agenda reflects a measured approach to financial innovation. Rather than viewing technology solely as a means of accelerating transactions, the regulator is examining how new systems can function within an established framework of investor rights, market integrity and institutional accountability.
Demat 2.0 offers a live testing ground for tokenised securities, while the proposed AI sandbox could provide a structured way to evaluate a wider range of applications. Both initiatives will need to demonstrate their value under real operating conditions and within clearly defined safeguards.
The next phase of regulated financial innovation will ultimately be judged by whether it can deliver meaningful improvements to market infrastructure without introducing risks that undermine confidence. Technology may expand what financial markets can do. The quality of regulation, governance and implementation will determine how reliably those capabilities translate into practical outcomes.