India’s central banking ecosystem is turning to artificial intelligence to tackle the growing threat of cyber-enabled financial fraud. A new tool developed under the Reserve Bank’s innovation arm is designed to detect and freeze mule accounts before stolen money disappears through complex banking networks.
RBI-Backed Innovation Hub Deploys AI Tool to Track Mule Accounts
India’s financial authorities are deploying a new artificial intelligence system aimed at disrupting the networks that enable large-scale cyber fraud. The tool, known as MuleHunter.AI, has been developed by the Reserve Bank Innovation Hub, an initiative supported by the Reserve Bank of India.
The system is designed to identify and shut down so-called mule bank accounts, which investigators say form the backbone of many digital fraud operations. According to officials, the technology is capable of detecting and blocking roughly 20,000 mule accounts every month, helping authorities disrupt the financial channels used by cybercriminals.
Digital fraud schemes frequently rely on networks of such accounts to move stolen money rapidly between multiple banks. Once funds are transferred through a chain of accounts, tracing the origin of the transaction becomes significantly more difficult for investigators. Authorities say the new AI-driven platform seeks to interrupt that process at an early stage, identifying suspicious accounts before the money can be fully dispersed through the system.
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The Role of Mule Accounts in Cyber Fraud Networks
Financial investigators say 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. Funds stolen from victims are transferred into one account and then quickly routed through multiple accounts across different banks.
The rapid movement of funds creates layers of transactions designed to obscure the trail. By the time investigators identify the first account, the money may already have been split and moved through several other accounts. Authorities say this pattern has made mule accounts particularly difficult to detect using traditional banking monitoring systems.
AI System Designed to Detect Suspicious Patterns
The MuleHunter.AI platform uses machine learning to analyze patterns in banking transactions and account activity. Officials say the system can detect unusual changes in account behavior, including transaction patterns that resemble those commonly used in fraud networks.
One of the key capabilities of the system is the ability to freeze suspicious transactions before funds are withdrawn. When the tool identifies a suspicious transaction chain, it can trigger alerts that allow banks to halt transfers and freeze the accounts involved. Investigators say the technology is also 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 system is already being deployed in around two dozen banking systems, according to officials familiar with the project.
Rising Scale of Mule Account Activity
Data from the Indian Cyber Crime Coordination Centre highlights the scale of the problem. According to the agency, 26.5 lakh layer-1 mule accounts had been identified by December 31, 2025. Authorities say cybercriminals have used these networks to siphon off nearly ₹20,000 crore, though about ₹8,189 crore has been recovered and returned to victims.
The concentration of mule accounts has been uneven across the country. Investigators say Haryana’s Nuh district recorded more than 1,000 mule accounts identified in 2025, while Jharkhand’s Jamtara district—long associated with cyber fraud—saw more than 350 such accounts detected during the same period.
Recognizing the growing scale of cyber-enabled financial crime, the Ministry of Home Affairs has directed all financial institutions to integrate with the MuleHunter platform by December 2026. Officials say the system is intended to create a coordinated national mechanism capable of identifying suspicious accounts across banks and financial institutions.
For investigators confronting increasingly sophisticated cybercrime networks, 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.
