A user-centered explainable artificial intelligence approach for financial fraud detection

Ying Zhou, Haoran Li, Zhi Xiao and Jing Qiu

Finance Research Letters, 2023, vol. 58, issue PA

Abstract: This paper aims to produce user-centered explanations for financial fraud detection models based on Explainable artificial intelligence (XAI) methods. By combining an ensemble predictive model with an explainable framework based on Shapley values, we develop a financial fraud detection approach that is accurate and explainable at the same time. Our results show that the explainable framework can meet the requirements of different external stakeholders by producing local and global explanations. Local explanations can help understand why a specific prediction is identified as fraud, and global explanations reveal the overall logic of the whole ensemble model.

Keywords: Financial fraud detection; Explainable artificial intelligence; SHAP (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:58:y:2023:i:pa:s1544612323006815

DOI: 10.1016/j.frl.2023.104309

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