Context:
The Reserve Bank of India (RBI) is scaling up the deployment of its AI-driven MuleHunter platform across more banks to curb fraud involving mule accounts.
Key Highlights:
- MuleHunter Deployment:
- Already implemented by 5 banks: Canara Bank, PNB, BoI, BoB, and AU Small Finance Bank.
- Federal Bank to adopt it shortly.
- At least 15 more banks expected to onboard in the next 1–2 months.
- What is MuleHunter?
- Developed by RBI Innovation Hub.
- Uses AI/ML algorithms to detect mule accounts (fraudulent accounts used for money laundering or scams).
- Currently being provided to banks free of cost.
- Functionality & Efficiency:
- Detects 90% true positives, significantly better than traditional systems with 80% false positives.
- Identified 90 fraud patterns, such as frequent night-time transactions (esp. between 11 PM–1 AM).
- Used for both savings and current accounts.
- Implementation Requirements:
- Banks need infrastructure and data science teams for full adoption.
- Platform will learn and adapt better as more banks join.
- RBI’s Broader Strategy:
- AI Committee Report to be released soon.
- RBI is also evaluating threats from quantum computing to preempt future cyber risks.
Significance
- Enhances the cybersecurity framework for Indian banks.
- Aims to curb digital financial frauds more effectively.
- Supports real-time fraud prevention and inter-bank intelligence sharing.
