As of December 10, 2025, 23 banks have implemented the Reserve Bank of India’s (RBI) MuleHunter.AI initiative, according to an RTI response that MediaNama received from the central bank.
Furthermore, India’s central bank said that it cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI because the RBI holds the information in a fiduciary capacity with banks, and that disclosure could harm competitive interests under the RTI Act, 2005.
Moreover, the RBI stated that it does not have information on formal coordination with law enforcement agencies like the Indian Cyber Crime Coordination Centre (I4C) specifically for MuleHunter.AI, nor does it hold details of internal circulars, guidelines, or advisories sent to banks or payment aggregators about the initiative.
For context, MuleHunter.AI is an artificial intelligence-driven (AI-driven) model developed by the Reserve Bank Innovation Hub (RBIH) to help banks detect and curb mule accounts, which fraudsters use to funnel, launder, or transfer proceeds of financial fraud.
Earlier in August 2025, the RBI’s Chief General Manager (CGM) Suvendu Pati said that at least 15 banks had already implemented MuleHunter.AI. These banks include the likes of Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, and AU Small Finance Bank. At the same event, Pati added that Federal Bank was in advanced stages of going live.
Meanwhile, RBI Governor Sanjay Malhotra noted in November 2025 that nearly 20 banks had adopted the system, again without a published list of names.
What is MuleHunter?
The RBIH announced MuleHunter.AI in December 2024 as a new AI-based tool focused on identifying mule accounts used in financial fraud. Fraudsters exploit mule accounts to transfer illicit funds through otherwise legitimate banking systems, which makes transactions difficult to trace and recover, and leaves financial institutions as well as customers vulnerable to losses.
Traditional fraud detection systems rely on static, rule-based models that flag accounts based on fixed criteria. However, these systems often generate high false positives and require lengthy manual checks, slowing responses and leaving many fraudulent accounts undetected for longer periods. Moreover, rigid rule sets cannot adapt swiftly to evolving criminal behaviour.
However, MuleHunter.AI analyses transaction and account activity patterns across banks to identify accounts likely used as “mules” in financial fraud, rather than relying on fixed, static rules. It was developed by studying 19 distinct behaviours associated with mule accounts, enabling more accurate and faster detection of suspicious accounts.
AI In Fintech And Banking
AI is increasingly shaping the Indian financial sector, with fraud detection emerging as a primary application alongside customer service and risk management. At MediaNama’s “AI in Fintech” panel in April 2025,
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