RBI is leveraging AI to crack down on ‘mule bank accounts’
Context:
The Reserve Bank of India (RBI) is leveraging artificial intelligence (AI) to combat the growing issue of “mule” bank accounts, used by criminals for laundering illicit money.
About RBI’s Initiative:
- The RBI’s innovation subsidiary, the Reserve Bank Innovation Hub (RBIH), has developed MuleHunter.AI, an advanced AI-powered model to detect and address this problem effectively.
- The model has shown promising results in a pilot with two large public sector banks, and banks have been encouraged to collaborate with RBIH to enhance its capabilities.
What Are Mule Bank Accounts?:
- Mule accounts are bank accounts co-opted by criminals to facilitate illegal activities such as money laundering. These accounts are often purchased from individuals, typically those from lower-income groups or with limited technical knowledge.
- The term “money mule” refers to individuals unknowingly used by criminals to move stolen or illicit funds. When these cases are discovered, the account holders often face scrutiny while the actual perpetrators evade detection.
Magnitude of the Problem in India:
Mule accounts are central to most financial frauds in India. Recently, the government froze 4.5 lakh such accounts involved in laundering proceeds of cybercrimes. Key statistics include:
- 40,000 accounts detected in the State Bank of India (SBI).
- 10,000 in Punjab National Bank.
- 7,000 in Canara Bank.
- 6,000 in Kotak Mahindra Bank.
- 5,000 in Airtel Payments Bank.
Measures by RBI and the Government:
The RBI has been actively addressing the issue by issuing guidelines to strengthen cybersecurity and fraud prevention in banks. The MuleHunter.AI system is a cornerstone of these efforts, enabling efficient identification of mule accounts. Additionally, the RBI has launched a “Zero Financial Frauds” hackathon to encourage innovative solutions targeting mule accounts.
Government initiatives have included:
- Regular meetings with stakeholders like the Indian Cybercrime Coordination Centre (I4C), NABARD, and banks to discuss strategies against digital fraud.
- Encouraging banks to adopt AI/ML tools for real-time mule account detection.
- Training bank staff on fraud prevention.
- Exploring restrictions on suspicious withdrawals, such as limits on dormant accounts that suddenly see significant activity.
The Department of Financial Services has emphasized adopting cutting-edge technology, fostering inter-bank collaboration, and using solutions like MuleHunter to bolster fraud detection.
