In this episode, guest host Marika Torsdotter sits down with AI and financial crime compliance expert Aneta Klosek to cut through the noise around AI and reveal what most compliance professionals are still missing.While the industry fixates on large language models like ChatGPT, Aneta argues there's a whole ecosystem of AI algorithms quietly powering or failing to power the fight against financial crime. The conversation breaks down three concrete use cases:* Gradient Boosting — the workhorse inside most transaction monitoring systems, learning from historical patterns to prioritize alerts and reduce false positives far beyond what static rule-based systems can achieve.* K-Means Clustering — an unsupervised learning technique that segments customers by behavior, not just category. A $50,000 transfer that looks normal for a corporate treasury cluster is a massive red flag for a retail student cluster. Context is everything.* Word Embeddings — the technology that bridges unstructured text and risk intelligence. From recognizing that "Muhammad Al-Hassan" and "M. Al-Hassan" are the same person, to understanding that "cleared of fraud" and "charged with fraud" carry opposite risk signals this model brings semantic intelligence to name screening and adverse media.Aneta closes with a hard truth: the biggest gap in the industry isn't technology it's the skill gap between technical teams and compliance officers, and the dangerous tendency to treat AI as a pilot project rather than a core business strategy. Meanwhile, criminals face none of those constraints.Bottom line: Stop treating AI as a side project. Start with your data. Build from clarity, not hype.