RBI Policy
Introduces MuleHunter.ai to identify mule accounts
This story was originally published at 14:39 IST on 6 December 2024
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--RBI Das: Mule-hunter.AI introduced by RBI to identify mule accounts
--RBI Sankar: MuleHunter.AI to be trained to identify frauds in fincl sector
MUMBAI – The Reserve Bank of India introduced MuleHunter.ai, an advanced artificial intelligence and machine learning model developed by Reserve Bank Innovation Hub in Bengaluru, to tackle the growing menace of mule bank accounts and digital fraud, Governor Shaktikanta Das said in his monetary policy statement detailed Friday.
First introduced during the Global Fintech Fest in August, MuleHunter.ai represents a shift in the way financial institutions can identify suspicious activities. Unlike conventional fraud detection systems that rely on predefined rules, MuleHunter.ai continuously learns from data, enabling it to adapt and evolve in response to increasingly fraudulent methods. Additionally, by improving detection capabilities, MuleHunter.ai will enhance the traceability of illicit funds and strengthen the financial system's defences against online financial crimes.
Mule accounts are typically used to launder the proceeds of crime, with fraudsters recruiting unsuspecting individuals to act as "mules" by using their bank accounts to receive or transfer illicit funds. These accounts, which often operate under false identities or third-party names, are commonly linked to money laundering, tax evasion, and other financial crimes. The difficulty in detecting these accounts stems from the fact that they are often opened by legitimate individuals who unwittingly assist in illegal activities, making detection challenging during the onboarding process.
Moreover, mule accounts violate several laws, including the Prevention of Money Laundering Act, and are in direct contravention of RBI and Securities and Exchange Board of India guidelines. To address this challenge, MuleHunter.ai aims to leverage AI and ML technologies, which can identify mule accounts more effectively than traditional rule-based detection systems. This AI-driven model could enable banks to detect fraudulent accounts swiftly and with greater accuracy, ultimately safeguarding the integrity of the financial system.
The RBI has been working closely with the Indian Cyber Crime Control Centre, under the Ministry of Home Affairs, and other regulatory agencies to combat the rise of cybercrime. According to the National Crime Records Bureau, online financial frauds accounted for 67.8% of all cybercrime complaints in the second quarter of 2025. Between 2020 and 2022, cyber fraud cases surged by 31%, with over 150,000 cases registered in 2022 alone.
At a press conference after the Monetary Policy Committee outcome, Deputy Governor T. Rabi Sankar provided clarity on the MuleHunter initiative. He said MuleHunter is an infrastructure-level platform being developed by the central bank, and it would integrate data from all banks and payment system operators. Its AI engine would be trained on the comprehensive dataset to more effectively detect fraud within the financial system, he said.
Highlighting the growing concerns around fraud, Sankar said, "The number of frauds are increasing...the amount involved in fraud are increasing, although the number of frauds per transaction is coming down over the years. But the number is increasing fast enough for us to be concerned about it."
He emphasised that each entity remains free to continue using its own fraud prevention systems and is encouraged to innovate based on its own expertise and AI capabilities. The purpose of MuleHunter, he explained, is to provide an infrastructure-level solution that can be used by all players, particularly smaller banks or institutions that may not have the resources to develop such sophisticated systems. Even for larger institutions, it would serve as an additional tool that can complement and enhance their existing fraud detection framework, Sankar said. End
Reported by Sachi Pandey
Edited by Namrata Rao and Avishek Dutta
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