In India, money moves in a blink. With UPI transactions hitting record-breaking billions every month, if your security team takes 30 minutes to look at an alert, they aren’t just late, they’ve already lost. By the time an analyst even notices something is wrong, a “mule account” network has already funneled stolen money through five different layers and is out of reach.

Traditional Security Operations Centers (SOCs) are too slow to meet the needs of the Indian financial market. The shift to an AI SOC, one that thinks, prioritizes, and acts autonomously, will soon be a necessity. We need a system that thinks as fast as the payment rails it’s supposed to protect.

Why 30 Minutes is the New Forever

Legacy cybersecurity was built on a “detect and remediate” philosophy. An alert triggers, a human analyst investigates, a ticket is raised, and a port is closed. This process, even when optimized, takes roughly 20 to 30 minutes. The old cycle, detect, alert, investigate, and act, takes at least 20 minutes on a good day. In the UPI world, 20 minutes is a lifetime.

When a “first-time high-value transfer” happens at 3:00 AM, a standard SOC treats it as a log entry to check in the morning. Meanwhile, attackers use automated scripts to drain accounts faster than any human can react. This creates “trapped capital”, money that is technically yours but is as good as gone because your defense is reactive. If you’re waiting for a human to click “approve” on a security block, the money is already in a different state, under a different name.

Staying Under the Radar Using Micro-Splitting

Attackers have figured out how to stay under your radar. Instead of trying to steal ₹1 lakh in one go (which would trigger alarms), they use bots to split the theft into 50 tiny ₹2,000 transfers. This is called micro-splitting.

To your system, this looks like normal daily life, like buying groceries or paying for a cab. These “rapid fund-out patterns” are designed to beat static rules.

Specific challenges for current SOCs:

• SOCs are drowning in “noise,” struggling to reduce false positives, and are unable to distinguish between a legitimate high-frequency user and a micro-splitting script using behavioural analytics.
• Most fraud detection systems rely on static rules (e.g., “Flag if > ₹1 Lakh”). Attackers know these rules better than junior analysts do. Machine learning-based anomaly detection changes this, spotting unusual patterns in transaction behavior that static rules will never catch.
• The lack of data provenance across different banking modules means the SOC sees the “log” but doesn’t see the “intent.” Without SIEM-driven correlation and threat intelligence feeds, context is always missing.

To catch a micro-splitter, you don’t need a faster human; you need an architectural shift toward automated threat detection that understands context.

Moving Beyond Endpoint Security Toward Agentic Defense

For CXOs at Indian financial institutions, the current mandate is to integrate MDR directly with NPCI’s real-time rails. It is no longer enough to secure the laptop or the server. The threat is in the logic of the transaction itself. This requires a shift from signature-based detection to behavioral analytics and network analysis powered by UEBA, continuously profiling normal vs. abnormal user and system activity to flag deviations the moment they occur.

Modern defense requires moving beyond simple “if-then” scripts. The objective is to utilize automated AI agents that possess the “agency” to reason through the context of a transaction. When a system identifies 200 small-value transfers hitting a newly created “mule account” (accounts often opened with forged credentials), it shouldn’t wait for a human. It needs to calculate the probability of a mule account network in real time using predictive analytics and immediately execute a “soft-freeze” on the outgoing UPI handle.

This is where NuSummit Cybersecurity’s AI SOC provides a critical advantage. Rather than treating security as a silo, CogniX MDR in the AI SOC platform leverages AI-powered agents specifically designed to reduce L1 threat analysis time through automated incident prioritization, ranking alerts by severity so analysts focus only on what matters. For a CISO, it’s a way to ensure that the immutable ledger is protected before a transaction is finalized

Meeting NPCI Guidelines Without the Headache

The NPCI is pushing banks toward real-time monitoring. CogniX MDR helps you stay ahead of these guidelines by automating the detection of “first-time” interactions and atypical transfer values,  combining threat hunting with predictive defense to identify attack vectors before they are exploited.

Because CogniX MDR uses SOAR (Security Orchestration, Automation, and Response), it can automate the entire containment process. If a mule account is detected, the playbook can automatically deactivate the user account and contain the threat. XDR capabilities extend this protection across endpoints, the network, and the cloud layers simultaneously. This moves your Mean Time to Detect (MTTD) and Respond (MTTR) from hours down to seconds.

Strategy Over Hype

Cybersecurity isn’t just a cost; it’s what keeps your customers trusting you. A single viral story about a “15-second loss” can do more damage to a bank’s reputation than the actual theft.

By using a platform like CogniX MDR, you’re turning security into a business advantage. Deploying an AI SOC means you’re telling your customers, and your board, that you can handle the velocity of modern payments without blinking.

The CogniX MDR advantage

• Cuts threat detection effort by up to 80% and response time to under 3 minutes.
• Already handles ingestion for large organizations, like a leading Indian e-commerce leader, processing 4TB of logs daily.
• Aligned with the MITRE ATT&CK framework to ensure you aren’t just guessing, but hunting based on real-world attacker techniques.

The Bottom Line

UPI isn’t slowing down. By the end of 2026, we expect transaction volumes to double again. If your defense still relies on manual checks and “brittle” rules, you’re leaving the door open for 15 seconds every time someone hits “Pay.”