What Is MuleHunter.AI? RBI Bets On Artificial Intelligence To Stop Mule Bank Accounts, Digital Frauds

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Last Updated:December 06, 2024, 14:33 IST

AI tool MuleHunter.AI is an advanced AI/ML-based solution designed to improve identification of suspected mule accounts

RBIH showcased the model and its use-cases at the Global Fintech Fest in August. (Representative image)

In its ongoing efforts to combat and prevent digital frauds, the Reserve Bank of India has introduced an innovative AI/ML-based model, MuleHunter.AI. Developed by the Reserve Bank Innovation Hub, this solution is designed to help banks efficiently address the growing issue of mule bank accounts and significantly reduce digital fraud.

A mule bank account refers to a bank account that is used by criminals to facilitate money laundering or the illegal movement of funds. These accounts are typically set up by individuals who may either be unaware they are participating in illegal activities or are coerced or tricked into opening and using the accounts.

Announcing the latest monetary policy decision on December 6, Governor Shaktikanta Das emphasised that the RBI is intensifying efforts to tackle mule accounts. He highlighted that the newly introduced AI-based solution will be crucial in helping banks eliminate these accounts and curb digital fraud.

Project Overview & Background

Online Financial Frauds: A Growing Concern

Data from the National Crime Records Bureau (NCRB) reveals that online financial frauds accounted for 67.8% of all cybercrime complaints received in the second quarter of 2022. This highlights the increasing prevalence of financial crimes in the digital space, posing significant challenges for authorities and financial institutions alike.

The Challenge of Money Mule Accounts

A major hurdle in combating financial fraud is the use of money mule accounts. These accounts are employed by criminals to launder illicit funds. They are often set up by individuals who are either unknowingly recruited through promises of easy money or coerced into participating in these illegal activities. The interconnected nature of these accounts makes it difficult to track and recover the funds, exacerbating the problem.

Current Detection Methods: Limitations

To address this issue, the RBIH has been consulting with banks to assess existing methods for identifying and reporting money mule accounts. However, the current rule-based systems for detecting such accounts are far from perfect. These systems tend to generate a high number of false positives, resulting in longer detection times and leaving many mule accounts undetected.

AI/ML-based Solution: A More Effective Approach

In response to these challenges, RBIH developed the AI tool MuleHunter.AI, which is an advanced AI/ML-based solution designed to improve the identification of suspected mule accounts. Unlike traditional rule-based systems, machine learning algorithms can analyse large datasets of transaction and account details, offering more accurate and faster detection. This approach has proven to be significantly more effective in uncovering mule accounts, thereby enhancing the security of financial systems and enabling quicker responses to financial fraud.