AI in Banking Needs Explainability to Reach its Potential

In an American Banker op-ed the author acknowledges the amazing potential of AI; it has been said that it could provide banks with over $1 trillion in cost savings by 2030; the challenge for banks will be to keep AI from becoming a black box; the current regulations, including model risk management, are designed for static models, not models that can learn and improve over time; many organizations such as Google, Microsoft and DARPA are working to make AI explainable but first there should be “accountable AI” which calls for human accountability for those developing the AI models. Source.

About the Author

  • Peter Renton

    Peter Renton is the chairman and co-founder of LendIt Fintech, the world’s first and largest digital media and events company focused on fintech. Peter has been writing about fintech since 2010 and he is the author and creator of the Fintech One-on-One Podcast, the first and longest-running fintech interview series. Peter has been interviewed by the Wall Street Journal, Bloomberg, The New York Times, CNBC, CNN, Fortune, NPR, Fox Business News, the Financial Times, and dozens of other publications.

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