AI race of money laundering prevention against money laundering
Artificial intelligence is playing an increasingly important role in money laundering prevention, as it can help identify suspicious activity in financial transactions at an early stage and provide more effective anti-money laundering and counter-terrorist financing measures. At the same time, however, every AML expert is aware that money launderers are also increasingly exploiting AI technologies to conceal their illicit activities.
The very methods that can be used to optimize anti-money laundering on the one hand are often countered by activities that encourage money laundering.
A few examples:
- Pattern Recognition:
AI can analyze large volumes of transaction data and identify patterns or anomalies that indicate possible money laundering. By continuously monitoring a very high number of transactions, AI can identify suspicious activity faster and more accurately than previous software solutions.
Unfortunately, however, money launderers can also use AI to adapt their transaction patterns to make them appear less suspicious. By using AI to create patterns that resemble normal business activity, they may attempt to circumvent the pattern recognition algorithm. Alternatively, AI can be used to generate random patterns to bypass the attention of transaction monitoring systems.
- Behavior Analysis:
AI systems can analyze customer and transaction behavior over time and distinguish normal behavior from deviant behavior. Deviations that could indicate money laundering or other criminal activity can thus be detected more quickly.
Unfortunately, money launderers can leverage AI by analyzing legitimate transaction patterns and imitate them better than without AI.
- Identification method:
AI systems can help automate the verification of customer identities and documents, such as passports or ID cards. This speeds up the KYC process and reduces manual workloads.
However, AI is equally used in the creation of fake identification documents and is already being used, particularly in video legitimation.
- Text and language analysis:
AI can also analyze text and speech to identify potentially suspicious information in communications. This can be helpful in detecting indications of money laundering schemes in emails, chats, or other forms of communication.
However, AI can also be used to create realistic audio or video fakes in which a person appears to say or do things that they never actually said or did (deepfakes). Deepfakes, in particular, can facilitate identity theft.
The list could be continued.
The use of AI by money launderers will be very successful if money laundering defendants do not take advantage of the development of AI to the same extent and rise to the challenge. Advances in money laundering prevention technologies go hand in hand with advancements in money laundering detection technologies. However, they require a willingness to invest heavily in these technologies.
