The financial industry demands precision, speed, and trust—making it an ideal environment for applied AI. In this session, we’ll explore how AI and automation are transforming risk management, compliance, and operational workflows across the financial sector.
Drawing from hands-on experience in leading cloud migration and enterprise automation at a global financial institution, I’ll share how AI was embedded into critical data pipelines to enable real-time fraud detection, support AML/KYC compliance, and reduce operational overhead. We’ll examine how PySpark-based automation frameworks and machine learning models enhanced the monitoring of suspicious activity, streamlined data validation, and supported regulatory adherence without compromising performance.
This session also highlights the importance of data observability and quality in financial environments. We’ll discuss strategies for maintaining trust in AI outcomes through robust data reconciliation, cross-system integrity checks, and proactive anomaly detection.