The current system to combat money laundering encounters a number of difficulties. With the digital revolution, Artificial Intelligence could play a major role.

The United Nations Office on Drugs and Crime (UNODC) has declared that money laundering would represent 2 to 5% of global GDP every year, in other words 1.6 to 4 billion dollars. And yet, the financial sector has no shortage of devices to detect and alert to the criminal activities it encounters.

Banks need to improve the way they handle their alerts in order to better target money laundering activities, which would save time and money.

According to the Autonomous Research Institute, the banking sector is expected to save $1 trillion by 2030 through the use of Artificial Intelligence technology. Indeed, the integration of AI in data filtering steps, in monitoring customers in the KYC process, transactions or prioritizing alerts allows analysts to have more time to focus on important cases and improve the quality of

AI is increasing the effectiveness of the fight against money laundering, but only 35% of banks use it. To date, the authorities have been reluctant to use AI because of explainability. Moreover, despite cognitive search, the quality of the data used and processed is difficult to verify. There is a problem of confidentiality and data protection.

Finally, in order to be able to process these large quantities of data, financial institutions need to have strong processing and storage capacities.