AML Advisory

Financial Intelligence Unit arms itself with AI & ML tools for AML

India’s Financial Intelligence Unit has introduced a groundbreaking upgrade to its information technology system named FINnet 2.0. This new system incorporates AI & ML tools for AML, significantly enhancing the nation’s capabilities in detecting, analyzing and preventing money laundering and terrorist financing. This cutting-edge technology highlights the vital role of innovation in strengthening financial intelligence and ensuring national security.

Journey to FINnet 2.0: Developing Financial Intelligence Unit

The Registered Financial Intelligence Unit in India has integrated artificial intelligence and machine learning tools to combat money laundering and terrorist financing. The upgrade was necessitated by the increasing volume of suspicious transaction reports from banks and financial institutions, which the FIU analyzes and disseminates to investigations and intelligence agencies, according to a 2022-23 fiscal report.

The FIU was established in 2004 under the Prevention of Money Laundering Act; it plays a crucial role in India’s fight against money laundering and terrorism financing. The recently accessed report outlines the development of the Financial Intelligence Network (FINnet) 2.0, designed to adapt to the evolving regulatory environment and technological framework. This overhaul aims to improve financial intelligence collection, processing and dissemination.

FINnet 2.0 leverages emerging technologies for enhanced analytical capabilities, data quality, compliance monitoring and security tools, strengthening FIU-India’s anti-money laundering and terrorism financing efforts. The system generates risk scores for individuals, businesses, reports, networks, and cases, prioritizing high-risk cases for immediate action using risk analytics.

Evolution of FINGate, FINCore and FINex in FINnet 2.0

FINnet 2.0 enhances FIU’s analytical and data processing capacity with three sub-systems: FINGate, FINCore and FINex. FINGate collects information from banks, financial institutions, and intermediaries. FINCore, the most crucial vertical, performs analytics and generates summaries of suspicious transactions; FINex disseminates financial intelligence reports to investigate agencies like the Income tax department, ED, CBI, Directorate of Revenue Intelligence, Intelligence Bureau, military intelligence and NTRO.

FINCore uses external databases, including the Central Board of Direct Taxes (CBDT), Ministry of Corporate Affairs (MCA), National Payments Corporation of India (NPCI), Central Registry of Securitization Asset Reconstruction and Security Interest, Central Depository Services Limited, and National Securities Depository Limited, to create a comprehensive profile of entities that aids in effective resolution and identification.

Essential Feature of FINnet 2.0

The essential features of FINnet 2.0 are stated below:

1. Artificial Intelligence and Machine Learning Integration

FINnet 2.0 utilizes AI and ML for advanced data analysis and predictive modelling. These tools help identify trends, patterns, and indicators of illicit activities, enhancing the FIU’s ability to detect and prioritize high-risk cases and entities.

2. Risk Scoring

The system generates risk scores for individuals, businesses, reports, networks, and cases, enabling the identification of high-risk cases for immediate actions and streamlining the investigative process.

3. National Language Processing & Text Mining

The system uses NLP and text mining to analyze textual inputs such as grounds of suspicion. This capability improves the depth and accuracy of analyses, making it easier to interpret and act on complex financial data.

FINnet 2.0 Secures Sensitive Data to Ensure Confidentiality & Security

With the sensitive nature of financial data managed by the FIU using AI & ML tools for AML, FINnet 2.0 integrates robust security measures to ensure data confidentiality and security. These measures include:

1. End-to-End Encryption

Ensure data security during both transmission and storage, thereby preventing unauthorized access.

2. Access Control

Ensures controlled access to portal content and automatically blocks logins after multiple unsuccessful attempts to safeguard the system.

3. Monitoring

It involves continuous logging of security incidents and an identity management solution that manages security rights and privileges, which form critical components of the system’s security infrastructure.

Which Entities Report to FIU-IND?

Entities reported to FIU-IND include businesses or professions designated under Section 2 Clause (wa) of the PMLA. These entities encompass banking companies, financial institutions, intermediaries and individuals engaged in specified professions.

The reporting entities must comply with KYC regulations established by the RBI. Consequently, FIU-IND KYC registration is mandatory for smooth transactions. Similarly, FIU registration for NBFCs is obligatory for the seamless operations of NBFC banking activities.

What are the Strategic Impacts and Future Directions for FINnet for FIUs?

The launch of FINnet 2.0 marks a major milestone in India’s financial intelligence and crime prevention efforts. Utilizing AL and ML, the FIU can process vast amounts of data more efficiently, detect complex patterns indicating illicit activities and deliver actionable intelligence to authorities. This technological advancement boosts FIU’s capabilities and sets global standards for integrating advanced technologies into financial intelligence systems.

How did Collaborative Efforts Shape FINnet 2.0?

The development and implementation of FINnet 2.0 was achieved through collaboration with experts in data analytics, IT and financial crime investigations. The Financial Intelligence Units ensured that the system could manage the increasing volume of Suspicious Transaction Reports while effectively identifying and interpreting intricate patterns indicative of illegal activities.  


India’s Financial Intelligence Unit, equipped with the advanced FINnet 2.0 system, uses AL and ML to combat money laundering and terrorist financing. This forward-thinking approach emphasizes the crucial role of technological advances in enhancing financial security and compliance. By adopting these methods, the FIU is setting a new standard for detecting and preventing financial crimes, underscoring technology’s importance in maintaining national and global financial security.


  1. How does FINnet 2.0 enhance India’s FIU capabilities?

    FinNET 2.0 is an upgraded system that integrates AI & ML tools for AML and terrorism financing to enhance data processing, risk assessment, and security measures and strengthen financial intelligence efforts.

  2. In what ways is AI utilized in AML?

    AI in AML enhances risk management efforts by effectively detecting and reporting money laundering operations. It integrates regulatory practices and complies with laws to ensure integrity within the financial system.

  3. What role does ML play in AML?

    Machine learning and artificial intelligence play important roles in the domain of AML analytics and compliance. These technologies enable identity verification or proper KYC by analysing diverse data points. 

  4. Who establishes the FIU to enhance AML?

    The Government of India established the FIU-IND through an official memorandum dated 18th November 2004, and it also serves as the central agency.

  5. What are the security measures in place to protect sensitive financial data?

    FINnet 2.0 employs end-to-end encryption, access controls and continuous monitoring to ensure data confidentiality and prevent unauthorized access to sensitive financial information.

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