Around the world, financial institutions are increasingly faced with a changing and threatening environment. Complex challenges in this post-covid period: increased digitization of services, the growing complexity of fraud and cybercrime, increasing amounts of data and above all increased regulatory pressure. This increases the pressure on financial institutions to implement effective AML compliance systems.

In their day-to-day risk assessment operations, Anti-Money Laundering (AML) analysts spend much of their time dedicated to routine and repetitive tasks. According to a study published by the research firm “Celent” (Source: Ray, Arin. 2018. …

When it comes to financial crime today, it appears to us as a kind of self evident after investigation that the most promising analytics tools are undoubtedly artificial intelligence. Machine intelligence constitutes a better alternative to analyst jobs because the use of Artificial Intelligence (AI) and in particular Natural Language…

1- The effectiveness of AI-based solutions in preventing and detecting new advanced fraud patterns. The traditional methods and solutions to fight against money laundering based on algorithms and basic rules, are ineffective and obsolete in the face of new fraud schemes which appear to be increasingly sophisticated. Artificial intelligence-based solutions are…