RBI asks banks to collaborate with MuleHunter.AI to find mule accounts

The RBI on Friday asked banks to collaborate with its initiative MuleHunter.AI to weed out mule accounts which are used to commit financial fraud.

A mule account is a bank account used by criminals to launder illicit funds, often set up by unsuspecting individuals lured by promises of easy money or coerced into participation. The transfer of funds through these highly interconnected accounts makes it difficult to trace and recover the funds.

"Use of money mule accounts is a common method adopted by fraudsters to channel proceeds of frauds," Reserve Bank of India (RBI) Governor Shaktikanta Das said.

Unveiling the December 2024 monetary policy, he said the RBI 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, piloted by Reserve Bank Innovation Hub (RBIH), a subsidiary of Reserve Bank.

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," the Governor said.

He also said the RBI has been taking various measures in coordination with banks and other stakeholders to prevent and mitigate digital fraud in the financial sector.

These include RBI guidelines for regulated entities to strengthen cybersecurity, cyber fraud prevention and transaction monitoring.

Further, the Governor announced to constitute a committee to develop a Framework for Responsible and Ethical Enablement of AI (FREE-AI) in the financial sector.

The financial sector landscape, he said, is witnessing paradigm shifts with the advent of frontier technologies. Technologies like Artificial Intelligence (AI)/ Machine Learning (ML), tokenisation, Cloud Computing hold transformative potential for the financial sector as they can handle enormous volumes of data, automate complex processes, enhance decision-making, and bring in unprecedented efficiencies.

While the benefits are many, the attendant risks like algorithmic bias, explainability of decisions, and data privacy, are also high, he said.

To harness the benefits, it is critical to address the attendant risks early in the adoption cycle, Das added.

The committee, Das said, will comprise experts from diverse fields and shall recommend a robust, comprehensive, and adaptable AI framework for the financial sector. The details of the committee will be notified separately.