The current anti-money-laundering system faces a number of difficulties. With the digital revolution, Artificial Intelligence could play a big role.

The United Nations Office on Drugs and Crime (UNODC) has stated that money laundering will account for 2 to 5 percent of global GDP each year, or $1.6 billion to $4 billion. And yet, the financial sector has no shortage of mechanisms to detect and alert on the criminal activities it encounters.

Banks need to evolve the processing of 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 the steps of data filtering, at the level of customer monitoring in the KYC process, transactions or the prioritization of alerts allows analysts more time to focus on important cases and improve the quality of their work.

AI increases the effectiveness of the fight against money laundering, but only 35% of banks use it. To this day, authorities are reluctant to AI because of explainability. In addition, 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 amounts of data, financial institutions need to have high processing and storage capacities.