Robotic Process Automation for Anti-money Laundering

It has mandatory by RBI to comply with the Bank Secrecy Act and should implement Anti-Money Laundering (AML) rules. The purpose of the AML rules are to help detect and report suspicious activities including the predicate offenses to money laundering such as securities fraud, market manipulation, etc. The latest technologies like Robotic Process Automation (RPA), machine learning, analytics and report generation for their AML compliance programs will help realize the efficiency and productivity gains and effectively reduce the cost of compliance.

More focus for financial organizations now is improving risk profiling and beginning to use AI to meet that problem while at the same time they are trying to optimize in order to close more and more fraud investigations to find out suspicious activities.

Advance technologies include analytics report, anomaly detection, network risk intelligence and machine learning which covers regulator investigation and internal risk management for the organizations. The activity which can perform in AML is AML compliance, AML transaction monitoring, trade surveillance, anti-fraud case management and operational risk, Investigation, Due Diligence, entity matching, suspicious activity detection tuning, etc.

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