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In this eye-opening interview, Chandrakant Maheshwari, Lead Model Validator at Flagstaff Bank, warns that model risk is no longer a siloed technical concern—it’s becoming a business-critical function tied directly to customer rights and regulatory exposure.
He points to GDPR as a pivotal force reshaping model validation by making transparency a legal requirement. Banks must now ensure models can explain their decisions clearly, particularly when it comes to rejecting or approving customers. This pressure will only intensify as the EU’s 2024 AI Act rolls out and U.S. state-level laws begin to catch up.
Maheshwari stresses the urgent need for stronger “three lines of defense” within model risk management, including live dashboards that track customer approvals, capital measures, and early warning indicators. Without this infrastructure, institutions risk falling behind in both compliance and business readiness.
He also highlights a major shift on the horizon—from software-as-a-service to autonomous AI agents. This transformation demands aggressive upskilling across all levels of an institution, from first-line users to auditors. Those who delay will expose themselves to competitive and regulatory disadvantages.
Throughout, he cites frameworks like SR 11-7 as global templates and praises GDPR for setting the tone on data transparency. Conferences like these, he concludes, are essential for knowledge-sharing and for keeping pace with a rapidly evolving risk landscape.
Chandrakant Maheshwari is a seasoned expert in Financial Risk Management with over 20 years of experience specializing in Model Risk Management Financial Crimes and AML Compliance. He is a thought leader in integrating AI technologies into risk management frameworks. Chandrakant is an advocate for using Generative AI to enhance model validation and risk assessment processes driving innovation while maintaining robust regulatory compliance. A published author and frequent speaker at industry conferences he is passionate about mentoring the next generation of risk professionals and advancing the practical applications of AI in finance.
