AI, ML tools to give more teeth to FIU

The FINnet 2.0 comprises 3 sub-systems. FINGate is meant for information collection from banks, financial institutions and intermediaries, FINCore is for analytics by FIU experts and FINex is used for disseminating financial intelligence reports to probe agencies and snooping organisations

New Delhi: India’s Financial Intelligence Unit (FIU) has operationalised an advanced 2.0 version of its information technology (IT) system, armed with artificial intelligence (AI) and machine learning (ML) tools, to check money laundering and terrorist financing crimes in the country’s economic channels. The upgrade of the technological backbone was required as the volume of data (suspicious transaction reports) flagged by banks and various other financial institutions to the FIU for analysis and further dissemination to investigative and intelligence organizations, has been increasing, a latest report for the 2022-23 fiscal said.

The agency was set up in 2004 to play a decisive role in India’s fight against the menace of money laundering and terrorism financing under the legal setup of the Prevention of Money Laundering Act (PMLA). The recently released report says that the Financial Intelligence Network (FINnet) 2.0 was envisaged as the country’s regulatory environment has been changing, technology landscape has been evolving and hence an overhaul of the existing FINnet 1.0 system was required to achieve an efficient system of collection, processing and dissemination of financial intelligence.

The report said: “FINnet 2.0 leverages emerging technologies for superior analytical competencies, data quality improvement, incisive compliance monitoring and cutting-edge security tools for strengthening anti-money laundering and combating the financing of terrorism capabilities of FIU-India and its reporting universe.”

It enables generation of risk scores for individuals, businesses, reports, networks and cases to be able to flag high risk cases, entities or reports for immediate action and it prioritises cases by using risk analytics, it said.

The 2.0 version has capabilities of “advanced analytics” by employing artificial intelligence and machine learning tools and a strategic analysis lab to stay abreast with the developments in anti-money laundering and emerging technologies, the report said. The new system also uses natural language processing (NLP) and text mining tools to analyze textual inputs like ‘grounds of suspicion’.