In a compelling conversation with Edwin from the Center for Financial Professionals, Chandrakant Maheshwari, Lead Model Validator at Flagstar Bank, sheds light on the complexities and evolving challenges in financial crime risk modeling. With the ever-changing nature of financial crimes, particularly in anti-money laundering (AML) and fraud detection, Chandrakant emphasizes that staying ahead requires not just vigilance but continuous innovation.

Chandrakant points out that financial crime models must evolve constantly to stay effective. "Models that were relevant five years ago are no longer applicable today," he notes, citing the explosion of transactional data and the sophistication of threats as key drivers. In particular, he highlights how fraud and AML models differ not just in the data they process, but in the fundamental philosophy of their design—fraud models are about defending customers from external threats, while AML models are about monitoring customers’ behavior to detect illicit activity.

The interview dives deep into behavioral indicators that distinguish these two domains. Fraudsters act fast and erratically—large, unusual transactions or sudden location shifts often trigger red flags. On the other hand, money launderers operate with patience and subtlety, blending illicit funds into normal activity over time to stay under the radar. This makes AML validation far more nuanced and long-term in nature.

When asked how financial institutions can improve their validation processes, Chandrakant stresses the importance of ongoing education. Training, he believes, is a shared responsibility. “It’s not just about the organization providing resources. Professionals must take initiative—through online platforms, free courses, or peer learning—to keep their skills sharp.”

Chandrakant also advocates for active participation in industry events. These gatherings serve as more than just knowledge exchanges—they validate shared challenges and offer actionable insights. “You may not find a 100% solution, but you'll leave knowing how to solve 20% more of the problem,” he reflects.

This conversation reinforces the idea that in the face of increasing model complexity and regulatory expectations, collaboration, continual learning, and technological adoption are non-negotiable. Chandrakant's insights serve as a powerful reminder that financial crime risk management isn’t just about compliance—it’s about foresight, adaptability, and strategic thinking.