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June 4, 2026International Journal of Financial StudiesOpen Access

Financial Fraud Detection Based on an Explainable Multi-Layer Framework

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Authors

HXHui XiaYHYilong HuangSFShanshan Fang

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Overview

Randomized trial evaluates a multi-layer framework for financial fraud detection, suggesting enhanced interpretability and effectiveness.

Key Points

  • The research aims to develop an effective framework for detecting financial fraud through advanced feature extraction and classification methods.
  • Proposed a multi-layer architecture model integrating business, internal control, and strategic features.
  • Utilized multi-layer neural networks for feature extraction and developed classification capabilities.
  • Incorporated explainable artificial intelligence techniques to enhance interpretability of the model.
  • The framework demonstrated competitive discriminatory ability in identifying financial fraud.
  • It achieved low-false-alarm fraud warnings under the multi-layer feature setting.
  • Provided interpretable insights catering to various stakeholders' needs.

Cite This Study

Xia et al. (2026) studied this question.

synapsesocial.com/papers/6a2117dfd499ed480b170b05https://doi.org/10.3390/ijfs14060146
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