Brands
Discover
Events
Newsletter
More

Follow Us

twitterfacebookinstagramyoutube
ADVERTISEMENT
Advertise with us

India's FIU launches AI-infused system to combat money laundering, terrorism financing

The new system 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.

India's FIU launches AI-infused system to combat money laundering, terrorism financing

Sunday May 05, 2024 , 3 min Read

India's Financial Intelligence Unit (FIU) has operationalised an advanced 2.0 version of its information technology system, armed with artificial intelligence and machine learning 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 organisations 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 has been accessed by PTI which 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.

"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," the report said.

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 analyse textual inputs like 'grounds of suspicion'.

The FINnet 2.0 is aimed to provide sophistication in FIU's "analytical and data processing capacity" and it comprises of three sub-systems.

While 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 like the Income-tax department, ED, CBI, DRI and snooping organisations like the IB, military intelligence and the NTRO among others.

FINCore, the most important vertical of this technology setup, uses artificial intelligence and machine learning to generate summaries and sharing suspicious transaction reports with various law enforcement agencies based on risk profile, it said.

This third sub-system uses information from external databases like the Central Board of Direct Taxes (CBDT), Ministry of Corporate Affairs, National Payments Corporation of India (NPCI), Central Registry of Securitisation Asset Reconstruction and Security Interest (CERSAI), Central Depository Services Ltd. (CDSL) and National Securities Depository Limited (NSDL) to draw a "holistic picture of the entity in question and helps in more effective resolution and identification of the entity".

The report stated that as the FIU deals with "sensitive" financial data, confidentiality and data security were important component of the upgraded IT system.

"Various measures are put in place to ensure security of data, including strong, end-to-end encryption, automatic blocking of logins after a set number of unsuccessful login attempts, controlled access to content stored on the portal, logging of security incidents, identity management solution capable of managing security rights and privileges by individuals," it said.


Edited by Affirunisa Kankudti