New Delhi: The central bank’s innovation arm is in talks with ten public and private banks to further the adoption of its artificial intelligence (AI)-powered tool to detect rising cases of financial fraud through widely prevalent “mule accounts”, a top executive said.
The Reserve Bank Innovation Hub’s (RBIH’s) platform, termed Mulehunter.Ai, has already been deployed by two large public sector banks, according to RBIH chief executive Rajesh Bansal. The trademarked platform was developed after identifying a total of nineteen patterns based on insights from multiple banks, he said.
A mule account refers to a bank account that is used to receive and transfer funds acquired by illegal means.
Typical patterns of misuse range from sudden transactions in a dormant account to multiple credits in an account followed by one large debit.
RBIH conducted stakeholder consultations with ten banks to understand the traditional approach adopted by lenders in such cases. It found that most banks still use a rule-based system to identify suspected mule accounts, after which verification is done manually, which leads to significant loss of time.
Bansal noted that early results -after the deployment of the AI-powered tool-have been “encouraging in terms of far better accuracy and cutting down the time taken”.
“If the percentage of accuracy of the manual system was x, this is 3x. If the time taken was y, this is o.1y,” he told ET.
In August, while addressing delegates at the Global FinTech Festival in Mumbai, PM Narendra Modi had urged regulators to take bigger steps to prevent cyber frauds and further digital literacy. “My expectation from regulators is that they need to do more to prevent cyber frauds and take more steps to improve digital literacy. Cyber frauds should not be allowed to impede the progress of the fintech and startup industries.”
Tech Adoption in Banking
RBIH’s AI platform is meant to hasten the detection of fraudulent accounts. Pointing out that “there are multiple channels through which frauds occur, and they are no longer small sums and can be to the tune of Rs 1 crore these days”, Bansal said they realised that “the best way would be to look at where the money eventually goes–to mule accounts”.
To be sure, the RBIH model will require continuous training and upgrade to ensure it can distinguish between mule and genuine business transactions.
The aim of the Mulehunter.ai initiative is to accelerate technology adoption in the banking sector.
Earlier this year, RBI governor Shaktikanta Das urged public and private sector banks to step up efforts against mule accounts and intensify customer awareness initiatives, among other measures, to curb digital frauds.
India lost approximately Rs 11,333 crore to cyber fraud in just the first nine months of 2024, according to data from the Indian Cyber Crime Coordination Centre (I4C) under the home ministry.
ET had reported on November 14 that banks are using AI to fight the growing menace of mule accounts, deploying AI tools to track suspicious patterns like dormant accounts receiving large credits or multiple accounts showing identical recurring transactions simultaneously.
Financial technology companies such as Bureau, Clari5 and Datasutram are helping banks deploy AI-based fraud detection systems that can detect issues like mule accounts.
Bansal said that if banks start using AI tools, it can gradually help address the issue.
