MuleHunter is an AI/ML-based model from the Reserve Bank of India (RBI). AI for combating mule accounts that are used for money laundering or else. These accounts allow criminals to launder money from cybercrimes. Banks will provide data to the model to help it better identify patterns of fraud.’
Launched by the Reserve Bank Innovation Hub, the new program is working with two public sector banks on pilot programs.
In FY22, 8,752 bank frauds amounting to Rs 9,298.4 crore were reported, but in FY24, they more than tripled to hit 32,363, amounting to Rs 2,714.64 crore, according to data from Minister of State (MoS) Finance, Pankaj Chaudhary, in response to a query in the Lok Sabha. These are frauds in commercial banks and AIFIs with amounts involved of Rs 1 lakh and above in each case.
Examples include mule accounts and mule bank accounts, bank accounts used by criminals for money laundering (and bermuang), set up by a naive person by promise of quick and easy money or duress. Hindered trace and recoverability: Due to the extremely interlinked nature, this transfer of funds is hard to trace and recover.
According to the National Crime Records Bureau (NCRB), online financial frauds make up 67.8 percent of all complaints of cybercrime, showing a clear technology gap that AI-based fraud-prevention solutions can address. The cases of mule accounts have streamed in, and money mules made up an incredible 53% of the overall fraud threats to the financial institutions in 2023. Although the state and various authorities are working against this, cybercriminals keep finding new ways to bypass the law and go after money laundering.
As this challenge continues to grow, the Reserve Bank of India Innovation Hub (RBIH) has developed a cutting-edge AI/ML model called MuleHunter AI, aimed at assisting banks and financial institutions in identifying and combating mule accounts.
Unlike traditional systems that frequently create false alarms, MuleHunter. ai uses machine learning to quickly and accurately identify suspicious accounts by monitoring illicit fund flows. By catching fraud early and improving the efficiency with which banks perform their cyber risk audits. It becomes one of the key solutions to enhance the strength of the financial backbone of the country. Early results indicate it greatly improves identification rates, a huge advance in the battle against financial crime.
“RBIH has developed an in-house AI/ML-based solution that is more effective than a rule-based system at detecting suspected mule accounts. By analyzing datasets containing both transaction and account detail, advanced ML algorithms can identify mule accounts much more accurately and faster than traditional, rule-based systems could. Such a data-led machine learning-based approach has led to the detection of a larger number of mule accounts in a bank’s ecosystem,” RBI said in a statement.
The system analyzed 19 unique patterns of mule account activity in collaboration with numerous banks. A trial project for two large public sector banks has been giving encouraging results.
“Initiatives like MuleHunter. Thus, we see how AITM showcases AI’s capabilities for combating threats, such as fraud detection and prevention (including cases like mule accounts). “If implemented, these measures can pave the path for a future-ready financial ecosystem that is secure, inclusive, and technology-driven by encouraging the collaboration of regulators, banks, and fintechs,” said Rajesh Mirjankar, Co-Founder, MD, and CEO of KiyaAi.
It has also been organizing a hackathon to promote innovation in fraud detection. Banks can use their systems, but if they want to paste everything, it is MuleHunter. AI will always protect your currency and bring the immediately needed infrastructure to smaller banks to identify fraud effectively and ensure customer trust in the financial system at large.
RBI has also requested banks to partner with its MuleHunter initiative. AI is used to identify mule accounts that are used for committing financial fraud.
“Banks should partner with RBIH to optimize MuleHunter. AI initiative to tackle the problem of the use of mule bank accounts for perpetrating financial frauds,” RBI Governor said on Friday.
The RBI has also been taking several steps in consultation with banks and other stakeholders to prevent and mitigate digital fraud in the financial sector, he mentioned.
This includes RBI guidelines on strengthening cybersecurity and cyber fraud prevention and transaction monitoring for regulated entities.
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