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AI in Banking Needs Explainability to Reach its Potential
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AI in Banking Needs Explainability to Reach its Potential

AI in Banking Needs Explainability to Reach its Potential

Peter Renton·
FintechNews Roundup
·May. 10, 2019·1 min read

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.

  • Peter Renton
    Peter Renton

    Peter Renton cofounded Fintech Nexus as the world’s largest digital media company focused on fintech before it was acquired by Command. 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.

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