AI and ML Enhances the Anti-Money Laundering Solutions
The issue of money laundering is a critical and rising concern worldwide and is violating the financial services system in many countries. United Nations estimated that between 2 and 5 percent of global GDP or $1.6 to $4 trillion is laundered every year globally. Thus, it is imperative for countries and financial institutions to have Anti-Money Laundering systems in place to combat these malpractices.
An effective Anti-Money Laundering (AML) system sets up rules, regulations, and procedures to prevent the disguising of illegal sources of large funds generated by criminal activities such as corruption, tax evasion, drug peddling, human trafficking etc. The laundered money is usually processed through various legitimate banking channels in rapid succession in order to hide the original source of information.
Many financial institutions use AML tools that are mostly based on rule engines where alerts are generated against a transaction whenever it violates any of the pre-defined rules. Alerts raised by such a tool then go through rigorous investigation to decide if the transaction should be prevented and/or reported to the authorities. Recent developments in technology and innovation have enabled AI & ML technologies to be leveraged in the AML space to contribute to the effectiveness of the traditional AML tools as well as prevent such crimes on time.
ABG has a dedicated team of professionals working in the fields of AML, AI & ML and provides services in the following spaces:
AI & ML technologies in tandem with the traditional AML tools have proved to be of great benefit for financial institutions to provide effective solutions. These have enabled system integrators with useful and time effective technologies in order to fast-track their investigations and effectively detect any suspicious activity. Many financial institutions are adopting these new solutions to stay ahead of their competitors and to efficiently prevent any mishaps while complying with the regulations and being cost-effective at the same time.
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