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As AI capabilities evolve, financial institutions face pressure to balance innovation with security, trust, and regulatory compliance. From fraud prevention to customer experience, deterministic AI applications continue to form the backbone of financial services—even as new technologies like generative and agentic AI emerge. In this episode, JoAnn Stonier, Data and AI Fellow at Mastercard, joins us to share how Mastercard is navigating these dynamics. She explains how AI-driven analytics reduce false positives in fraud detection, why "agent-ish" AI marks an important transition toward more autonomous systems, and how responsible governance ensures privacy and security remain at the forefront. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!
By Daniel Faggella4.4
162162 ratings
As AI capabilities evolve, financial institutions face pressure to balance innovation with security, trust, and regulatory compliance. From fraud prevention to customer experience, deterministic AI applications continue to form the backbone of financial services—even as new technologies like generative and agentic AI emerge. In this episode, JoAnn Stonier, Data and AI Fellow at Mastercard, joins us to share how Mastercard is navigating these dynamics. She explains how AI-driven analytics reduce false positives in fraud detection, why "agent-ish" AI marks an important transition toward more autonomous systems, and how responsible governance ensures privacy and security remain at the forefront. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

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