Money laundering is the process of making large amounts of money generated by criminal activities as if it appears to have come from a legitimate source. Anti Money Laundering is a complex issue for financial institutions. AML compliance is mandatory and there are sanctions such as fines for non-compliance institutions. AML compliance processes have been costly and complex for large companies and banks. The large amount and complex of data, and AML regulations cause time loss and increased costs.
Despite the precaution taken, financial crimes are increasing. Financial institutions need more sophisticated tools to minimize the increased risks. The new technology discovered for this need is artificial intelligence. New technologies that continually learn, collect new information and regulate processes can be developed with machine-learning-based artificial intelligence. It is expected to overcome the ever-increasing data density problem in AML. It can help find inconsistent customer transactions and suspicious transactions. AI can detect relationships that are too complex to be understood by rule-based monitoring or the human eye.
Even if the regulators support artificial intelligence, they are concerned what can happen in the application part. They have not taken advantage of AI because of concerns with the “black box”. It is difficult to understand its transparency and what it does and why, because its inner workings are not fully understood. Regulators require a compliance officer to better interpret the outputs.
The Effects Of Artificial Intelligence In The Anti-Money Laundering
Continuously monitor customer activities. By learning normal customer behavior, he can easily notice unusual behavior and transaction. It can even find the differences that can be unnoticed by human eye.
- It can reduce the cost of AML compliance audit.
- It can reduce the number of false-positive alerts.
- It can provide to find money laundering methods that are too complex to be understood by human eye.
AI is still a developing technology and it is unknown what will be happened and how will be used, by the banking and financial services sector. As a result, financial institutions are turning to new technological solutions with increasing cyber and financial crimes.