Four Ways to Reach AML Compliance through Artificial Intelligence(AI)

The wonders AI has been able to achieve so far in every field have the world thinking twice about its potential. Business processes have had breakthroughs with AI technology integrated into them. Some scientists predict that by 2030, the AI tech will have saved over 1 trillion dollars for the banking industry. This is mainly due to the increasing compliance and regulatory costs for the banking sector. Thus automated AML solutions for banks have become somewhat of a necessity. Some of the automated AI based processes involve fraud detection programs, anomaly detection programs, transaction monitoring systems and risk analytic software.

To decide what the perfect fit for your company is you need to evaluate your use cases in detail. After identifying your AML requirements for an AI system you need to work with experts in the field or engage an outsourced AI based AML provider to implement an effective compliance program. Some steps businesses should take to achieve AML compliance through AI include;

Anomaly Detection

An anomaly detection system is used by organisations to detect anomalies in large sums of data. Large amounts of transactional data that comes in through the banks’ servers can be difficult to sift through by traditional rule-based monitoring systems. An anomaly detection system operated through AI and machine learning can detect multiple types of anomalies at the same time thus issuing reports to the management, who are then able to take further action on the matter.

Transaction Monitoring Systems

Modern transaction monitoring systems employ machine learning protocols. Outdated rule-based monitoring system’s had low efficiency and a high number of false positives. With machine learning integrated into such systems, the monitoring process can be made more efficient and fast. It can detect actual fraudulent behaviour instead of just flagging any potentially suspicious activity. More to that, it can generate risk reports for the management to monitor any fraudulent behaviour and take a timely action over it.

Robotic Process Automation

Manual reviewing procedures are long and exhaustive. Most importantly they tend to have a high potential for error. Through Robotic Process Automation (RPA) financial institutes can increase both the efficiency as well as the accuracy of the reviewing process. The time it takes for human labour to review each and every alert is reduced by APA, thereby improving the whole process and allowing for better compliance with AML regulations.

AML Screening

Many KYC/AML companies are now providing AML checks through an automated process, wherein their AI-based software scan’s an individual’s name through every watch list issued by global regulators. If they are flagged by the system, the company/bank is issued a warning about their vulnerable status. Thus allowing them to decide whether or not to take them on as a client.

Technologies like AI and machine learning are providing simple yet efficient AML solutions for banks thus enabling them to improve their compliance process. They have managed to increase the efficiency and accuracy of the process and have also effectively reduced the time for implementing compliance regulations.

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