The war between the various financial sectors and money laundering has led financial institutions to set up technologically intelligent weapons. Thus, these institutions aim to use sophisticated analytical technologies such as machine learning to combat various financial crimes effectively. Furthermore, financial institutions are confronted with criminals and regulators who are imposing increasingly severe sanctions for offenses. Branches, which fear supervisor sanctions and damage to their reputation, are more dedicated than ever in their efforts to combat money laundering and the financing of terrorism (AML \/ CFT).The compliance teams who are under all this pressure from regulators believe that \u201cmachine learning\u201d is the miracle solution for the AML. Sanction Scanner would like to point out that machine learning is not new as a concept, but recent is its use in combating money laundering. Its usefulness is particularly important for reducing the number of false positives (false alerts) that are generated through traditional AML devices.Also, the areas of AML \/ CFT that are likely to be covered by these new technologies are very numerous, in particular:Customer knowledge (KYC), which involves due diligence and adequate customer profiles, such as verifying the origin of fundsMonitoring of transactions, which includes investigations of alerts.Thus, new technologies will play a potentially huge role in the field of AML \/ CFT, but they cannot entirely replace human judgment, which remains very important in these processes. Therefore, the aim will be to enrich the existing AML \/ CFT devices with the various technologies of artificial intelligence (AI).In this paper, we will focus on the uses of AI technologies in the field of AML \/ CFT. In the second part, we will present the challenges that must be met by KYC \/ AML software publishers as well as financial institutions to upgrade traditional AML \/ FT systems.All regulators talk about\u2026<\/p>","protected":false},"excerpt":{"rendered":"
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