In most cases, money launderers hide their actions through a series of steps that make it look like money that came from illegal or unethical sources are earned legitimately. Most of the major banks across the globe are shifting from rule-based software systems to artificial intelligence based systems which are more robust and intelligent to the anti-money laundering patterns. Recently developed Anti-Financial Crime Solutions which uses unsupervised learning techniques to understand customer behaviour which is further used to drive intelligence gathering, investigations and possible SAR filings

For instance as example Cloudular Network Tasks. Military Intelligence professionals that 'task network', have occasionally determined (and eliminated) 'valued' targets by integrating OSINT and HACKING with HUMINT and AI into a 'Cloudular Network'.

Not linear but cloudular, which means one asset will lead to others quickly and efficiently as we pull the various threads of information allowing clients to move in many directions at the same time or follow one specific aspect if required.

• determine terrorist groups logistics chains and supporters in order to identify nodes and support cells.
• identify the security and financial practices and people that terrorist groups applies to visitors to their battle grounds such as journalists, businessmen and recruits
• determine terrorist’s travel profiles, travel operations and patterns of travel to the US, Europe, North Africa, Asia and the Middle East
• provide electronic footprint on any and all aspects of the particular groups/individuals in Syria, Iraq, Iran, Afghanistan, Libya and elsewhere as available
• develop additional assets to meet requirements as tasked

Five sorts of financing or funding terrorism groups can be searched by AI-FININT program, namely:

1. Kidnapping for ransom (cash based transfers), extortion (cash based transfers), drug- and human trafficking and smuggling
2. ID theft, credit card fraud, falsifications, trade based money laundering (e.g. export and or used assets)
3. Private donations and fundraising
4. Misuse charitable organisations

State sponsorship

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