Reserve Bank of India Deputy Governor Rohit Jain has issued a stark warning about the emerging systemic risks posed by financial institutions' increasing reliance on a concentrated number of common technology providers, including cloud and AI services, which could lead to widespread disruption.
Key Points
- Financial institutions' growing dependence on common technology providers (cloud, AI) creates systemic risk, as disruption at one could affect many.
- RBI Deputy Governor Rohit Jain identified 'speed, concentration and opacity' as three key risks amplified by technology in finance.
- Automated systems' speed requires resilience beyond individual error prevention, focusing on early detection and containment.
- Accountability in financial decision-making cannot be diluted by advanced AI models, as institutions cannot outsource consequences.
- Regulatory policy should focus on outcomes and accountability, not prescribing specific technological choices, while evolving with new risks like quantum computing.
Financial institutions' growing reliance on common technology providers could create a new source of systemic risk, with a disruption at one provider potentially spreading across multiple institutions, Reserve Bank of India (RBI) Deputy Governor Rohit Jain said on Wednesday.
"Financial institutions may increasingly depend on a relatively small number of cloud providers, technology vendors and (artificial intelligence) model providers, often using overlapping datasets and similar technological infrastructure," Jain said at the Global Fintech Fest 2026, adding, the concern isn't simply the failure of one institution, but the possibility that a common dependency could transmit disruption or error across many institutions at the same time.
Understanding the Key Risks
Jain identified "speed, concentration and opacity" as three key risks as technology becomes more deeply embedded in finance.
"None of these risks is entirely new, but technology can amplify them and allow their effects to travel through the financial system in ways that are faster, wider and sometimes harder to detect," he said.
About speed, Jain said automated systems can act much faster than humans can respond, requiring financial institutions to build resilience that goes beyond preventing individual errors.
Institutions must be able to detect problems early, contain their effects and intervene before a small mistake becomes a much larger one, he said.
The growing sophistication of AI models also cannot dilute accountability in financial decision-making, Jain said.
"Advanced models can identify relationships and arrive at decisions in ways that may be difficult to explain.
"Greater sophistication, however, cannot mean weaker accountability."
"An institution may outsource the computation, but it cannot outsource the consequence," Jain said.
The underlying risks of finance remain unchanged despite technological advances, he said.
"Borrowers can still default, liquidity can still disappear, leverage can still magnify losses, and operational failures can still disrupt financial services."
Technology's Impact on Financial Risks
Technology doesn't eliminate those risks, but can significantly alter their speed, scale and transmission, the RBI's deputy governor noted, adding, rapidly evolving technology also creates a regulatory challenge, with authorities risking acting either too early or too late.
"Regulate too early, and we risk writing detailed rules for a technology we do not yet fully understand, or for an architecture that may change before the rules take effect," Jain said.
"Regulate too late, and the technology may already be deeply embedded before its risks are fully understood and addressed."
Policy should focus on outcomes and accountability rather than prescribe every technological choice, he suggested.
"The obligation to treat customers fairly does not change because an algorithm influences the decision.
"Similarly, responsibility for managing risk does not disappear because a model or technology is supplied by a third party," Jain explained.
Regulatory expectations should also be proportional to the consequences of a particular technology use, he said.
"A tool used to summarise an internal document cannot be treated in the same way as a system that autonomously approves credit or executes financial transactions," Jain said.
The greater the consequences of a technology's use, the stronger the expectations should be around governance, validation, oversight and intervention, he further said.
Future Risks and Regulatory Evolution
The central bank's deputy governor also flagged quantum computing as a future risk to the financial system, particularly because of its implications for existing cryptographic systems.
"Preparing in advance reflects a broader principle: We should not wait for a future vulnerability to become a present crisis before responding."
The RBI's supervisory capabilities will also need to evolve alongside the technology used by financial institutions, Jain said.
He cited DAKSH and PRAVAAH as examples of technology being used to improve supervisory and regulatory processes.
He also pointed to the Digital Payments Intelligence Platform (DPIP), which recognises that payment fraud increasingly cuts across institutional boundaries and requires network-level intelligence and near-real-time information sharing.
The policy objective should be to allow useful innovation while ensuring risks remain contained, Jain said.
"Good policy should give innovation room to grow, while ensuring that accountability and resilience grow with it."
Ultimately, technology should be judged by the outcomes it delivers to financial consumers rather than by its sophistication, he added.
