In a bid to address the financial fraud at different levels, the Reserve Bank of India introduced MuleHunter.ai, which is an innovative artificial intelligence-based model. This technology specialises in detecting and flagging mule accounts, which are often exploited for money laundering activities.
The term “Money Mule” refers to individuals who are unknowingly manipulated by scammers to launder stolen funds through their bank accounts. These individuals are often recruited by criminals to transfer unlawfully obtained money across various bank accounts.
The tool has undergone successful pilot testing at two public sector banks. Online financial frauds make up 67.8% of cybercrime complaints, as reported by the National Crime Records Bureau (NCRB), underscoring the urgent demand for AI-powered fraud prevention solutions.
A significant challenge in tackling financial fraud is the abuse of mule accounts, which play a vital role in facilitating illicit financial activities. Tools such as MuleHunter.AI are indispensable for protecting the financial system and mitigating the risks associated with cybercrime.
The RBI said: “AI solutions to identify mule bank accounts MuleHunter.AI The Reserve Bank has been taking various measures in coordination with banks and other stakeholders to prevent and mitigate digital frauds in the financial sector. These include RBI guidelines to regulated entities for strengthening cybersecurity, cyber fraud prevention and transaction monitoring. Use of money mule accounts is a common method adopted by fraudsters to channel proceeds of frauds.”
It added that the central bank is currently running a hackathon on the theme “Zero Financial Frauds” which includes a specific problem statement on mule accounts, to encourage development of innovative solutions to contain the use of mule accounts. Another initiative in this direction is the AI / ML based model called MuleHunter.AI, being piloted by Reserve Bank Innovation Hub (RBIH), a subsidiary of Reserve Bank. This model enables detection of mule bank accounts in an efficient manner.
This model enables detection of mule bank accounts in an efficient manner. A pilot with two large public sector banks has yielded encouraging results. Banks are encouraged to collaborate with RBIH to further develop the MuleHunter.AI initiative to deal with the issue of mule bank accounts being used for committing financial frauds.
How will it work?
The collaboration between the Reserve Bank Innovation Hub and financial institutions focused on assessing mule account identification and reporting methods. Traditional rule-based detection systems frequently produce inaccurate alerts and slow processing times, resulting in numerous undetected mule accounts.
Through a thorough analysis of 19 specific mule account behaviors in collaboration with banks, the Reserve Bank Innovation Hub created MuleHunter.AI to address these deficiencies. Initial findings demonstrate notable enhancements in detection effectiveness and precision.
The utilisation of AI/ML in this solution outperforms conventional rule-based systems through the utilisation of machine learning algorithms. It analyzes transaction data and account information to accurately and rapidly predict mule accounts. By concentrating on discerning the movement of illegal funds into mule accounts, this platform enhances banks’ ability to identify fraudulent activities within their systems effectively.
“Introduction of Mulehunter.ai marks a landmark step in India’s digital lending and fintech ecosystem. The cutting-edge initiative promises to better enable the industry to combat frauds and protect consumers by detecting and mitigating the risk related to fraudulent activities like mule accounts. It would therefore form a very strong mechanism to create trust and credibility – an important pillar of success in any digital financial platform. Furthermore, a comprehensive framework of the responsible and ethical enablement of AI is equally crucial. AI needs to be innovative yet transparent, fair, and accountable,” said Yashoraj Tyagi, CEO, CASHe.
“Initiatives like MuleHunter.AITM demonstrate how AI can effectively address challenges like fraud detection and prevention, including use cases like mule accounts. By encouraging collaboration between regulators, banks, and fintechs, these steps lay the groundwork for a more secure, inclusive, and tech-driven financial ecosystem,” said Rajesh Mirjankar Co-Founder MD and CEO of KiyaAi.