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AI Won’t Save You … But It Might Spot Trouble Before You Do
At Risk Americas 2025, Riten Dixit of the Federal Home Loan Bank of Cincinnati laid out a clear-eyed vision for how AI and machine learning can enhance—not replace—risk modeling. His message? In volatile markets, AI’s real value is early detection and better thinking, not technical perfection.
Jul 08, 2025
Riten Dixit, VP, Risk, FHLB
Tags:
AI and Technology (including Fintech)
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The views and opinions expressed in this content are those of the thought leader as an individual and are not attributed to CeFPro or any other organization
- AI and ML are being used to augment, not replace, traditional risk models
- Riten Dixit
emphasized AI’s strength in identifying early signals in complex markets
- Traditional
models fail to capture structural shifts like today’s mortgage market anomalies
- During the
2023 banking crisis, AI spotted risks before they appeared in financials
- Validation
of AI models should focus on decision usefulness, not just accuracy
- Dixit
developed a clustering tool using NLP and learning algorithms for identifying
bank vulnerabilities
- AI enhances
pattern recognition in fragmented and fast-changing risk landscapes
- Future
modelers must act as architects, using diverse tools to build decision-ready
frameworks
- Emphasis was
placed on communication and transparency with AI model users
- The real
value lies in models that improve thinking, not in achieving technical
perfection
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