Explainable & Responsible AI in Digital Banking Transformation

Posted February 13, 2023 | Industry | Amplify
xplainable AI
With AI systems now equaling or exceeding human performance, it’s increasingly important to understand the reasons a prediction is made. This is especially true in banking, where financial stability is at risk if the underlying mechanisms driving market-moving decisions are not well understood and where consumers must be protected from technology-related bias. Cigdem Gurgur explains the limitations and possibilities inherent in XAI and gives examples of AI’s potential to increase accuracy and fairness over the current statistical models guiding credit and lending decisions.
About The Author
Cigdem Gurgur
Cigdem Z. Gurgur is Associate Professor of Decision and System Sciences at Purdue University, and a member of Arthur D. Little’s AMP open consulting network. She is a data and management science expert with experience in optimization models under uncertainty and decision support systems development with algorithmic theory design. Dr. Gurgur’s work utilizes meta-analytics, computational models, and artificial intelligence (AI) techniques for… Read More
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