By Deepak Chand Thakur, CEO and Co-Founder and NPST
India’s digital payments are growing at a remarkable pace. In September 2026, UPI processed 24.07 billion transactions worth ₹29.37 lakh crore, up 23% in volume and 18% in value from a year earlier. Daily volumes crossed 800 million for the first time. Digital payments are now part of everyday life across the country.
For banks, scale on this level brings a matching responsibility. As payments become faster and more complex, compliance can no longer remain a periodic activity. Risks might happen at any time, and reviewing them weeks or months later is not enough. ‘RegTech has a central role here: it helps banks monitor risk continuously, automate routine compliance work, and respond faster to regulatory change.
Regulators are already asking for continuous oversight
The regulatory direction for banks is clear, and it has moved quickly over the past few months.
RBI’s Fraud Risk Management Directions for commercial banks, issued in July 2026, expect Early Warning Signal systems to monitor transactions in real time or with minimal lag, with particular attention to money-mule accounts. They also reinforce red-flagging of accounts and timely reporting of payment fraud to the Central Payments Fraud Information Registry and through Fraud Monitoring Returns. That only works if detection is continuous.
For banks in merchant acquiring, NPCI’s framework already makes the acquirer accountable for the merchants it onboards, including correct categorisation. The common thread is that regulators want evidence that controls are working every day.
Making compliance a continuous process
Traditional compliance has mostly been based on cycles. Data is collected, reviewed, and reported at set intervals. But risks do not always follow the same timetable. A suspicious transaction, unusual customer behaviour, or a regulatory change can emerge between two review cycles. By the time it is identified, the opportunity to act early may already be gone.
This gap is especially visible in merchant acquiring. A merchant that passes KYC and KYB checks at onboarding can change later: its website, ownership, product mix or transaction patterns may drift well away from its approved category. Under a periodic model, that drift often comes to light only through chargebacks, customer complaints or a regulatory query, after the bank’s exposure has already built up. The same applies on the account side, where a dormant or newly opened account can be turned into a mule account within days.
Technology can close this gap by watching for risk as it emerges instead of waiting for the next cycle. AI and machine learning models can track account, merchant and transaction behaviour, flag anomalies, and support risk-based decisions in near real time. As volumes grow, compliance checks become hard for banks to scale and slow down their response to new threats.
Embedding compliance into everyday operations
The real value of RegTech is not just automation. It is about integrating compliance into the systems where business already happens. This allows compliance checks to become part of day-to-day operations rather than a separate process.
Automated KYC and KYB checks can verify information at onboarding and revalidate it over time.
Continuous transaction monitoring can flag unusual patterns such as velocity spikes, rising chargebacks or structured payments without waiting for an end-of-day review. Regulatory intelligence tools can use natural language processing to track new RBI and NPCI circulars and map them to internal controls. The result is less repetitive work, and compliance teams can spend their time on exceptions, judgement calls and emerging risks.
The same approach can improve regulatory reporting. Instead of rushing to collect and consolidate information before a deadline, banks can build API-driven data flows that validate information as it moves through the system. This can make reporting faster while improving traceability and audit readiness.
The foundation matters as much as the intelligence
However, simply adding AI to existing compliance processes will not solve the problem. Enterprise-ready RegTech for banks needs four foundations.
Connected data. In most banks, compliance data sits across onboarding, fraud, AML, core banking and reporting systems, which creates gaps and inconsistencies. Bringing these sources gives a much fuller picture of risk.
Intelligent analytics. Modern systems have to go beyond rule matching. They need to understand patterns, behaviour and relationships across accounts, merchants and transactions, and keep learning as fraud tactics change.
Seamless integration. API-first design lets compliance controls sit inside existing workflows, alongside the bank’s core banking, payment switches and enterprise fraud risk management systems, rather than adding another tool for staff to operate. These platforms should strengthen what banks have already built, not replace it.
Strong governance. AI-driven compliance has to be explainable and auditable, with appropriate human oversight. Technology has made detection and analysis far more efficient, but accountability still sits with the bank and its board. Every flagged decision needs a clear rationale a regulator can follow. As the Digital Personal Data Protection (DPDP) framework phases in, continuous monitoring will also need to be designed around consent, data minimisation and security from the start.
Building trust alongside scale
India’s digital payments journey has shown how technology can bring speed and convenience to financial services. The next phase will be about ensuring that this growth is supported by equally strong systems for security, risk management and compliance.
RegTech can support this shift by helping banks respond to risks earlier, adapt to regulatory changes faster and give compliance teams better visibility into emerging risks.
In the end, the goal isn’t to add more compliance processes. It is to build compliance into the way banks operate, so that growth and trust move forward together.