RBI Introduces AI-Powered Surveillance for Mule Accounts to Combat Cyber Fraud

Post Views: 6

India’s Central Bank Leverages AI to Combat Cyber-Enabled Financial Fraud

India’s central bank is leveraging artificial intelligence to combat the growing threat of cyber-enabled financial fraud, with a new tool designed to detect and freeze mule accounts before illicit funds disappear through complex banking networks.

The Reserve Bank Innovation Hub’s Solution

The Reserve Bank Innovation Hub, an initiative backed by the Reserve Bank of India, has developed a system called MuleHunter.AI to identify and shut down these accounts. Investigators say mule accounts form the backbone of many digital fraud operations, frequently used in networks that enable large-scale cybercrime.

The technology is capable of detecting and blocking approximately 20,000 mule accounts monthly, helping authorities disrupt the financial channels used by cybercriminals. Digital fraud schemes often rely on these accounts to move stolen money rapidly between multiple banks, making it challenging for investigators to trace the origin of the transaction.

How Mule Accounts are Used in Online Scams

Mule accounts are central to many online scams, including digital arrest frauds, phishing attacks, and e-commerce scams. These accounts are often opened using forged documents or through individuals who allow their bank accounts to be used in exchange for commissions. Once operational, mule accounts are typically used for a short period, with funds stolen from victims transferred into one account and then quickly routed through multiple accounts across different banks.

The MuleHunter.AI Platform

The MuleHunter.AI platform uses machine learning to analyze patterns in banking transactions and account activity, detecting unusual changes in account behavior and transaction patterns that resemble those commonly used in fraud networks. The system can freeze suspicious transactions before funds are withdrawn, triggering alerts that allow banks to halt transfers and freeze the accounts involved.

The technology is designed to identify connections between accounts that appear unrelated but share common transaction patterns. Unlike traditional fraud detection systems that often identify fraud only after the incident occurs, the AI tool aims to intervene earlier in the process by detecting signals within the transaction flow.

The Scale of the Problem

Data from the Indian Cyber Crime Coordination Centre highlights the scale of the problem, with 26.5 lakh layer-1 mule accounts identified by December 31, 2025. Cybercriminals have used these networks to siphon off nearly ₹20,000 crore, with about ₹8,189 crore recovered and returned to victims. The concentration of mule accounts has been uneven across the country, with Haryana’s Nuh district recording over 1,000 mule accounts identified in 2025, while Jharkhand’s Jamtara district saw over 350 such accounts detected during the same period.

National Mechanism to Combat Mule Accounts

The Ministry of Home Affairs has directed all financial institutions to integrate with the MuleHunter platform by December 2026, aiming to create a coordinated national mechanism capable of identifying suspicious accounts across banks and financial institutions. The technology represents an attempt to shift the battle upstream, targeting the financial infrastructure that enables fraud before stolen money can vanish into the banking system.