Artificial Intelligence, Machine Learning & Corporate Fraud

Jesper Sørensen ()

Chapter Chapter 34 in Shorting Fraud, 2025, pp 341-358 from Springer

Abstract: Abstract As seen previously in the book, to detect fraud, moving beyond traditional financial metrics, ratios, and statistical methods, one may use Artificial Intelligence and Machine Learning. This chapter is not a full and exhaustive overview of Artificial Intelligence and Machine Learning, but an introduction primer related to using it in a corporate fraud setting. The chapter touches upon AI concepts like expert systems, genetic algorithms, and fuzzy logic, but focuses primarily on ML due to its practical application in fraud detection. The chapter explores various ML models and algorithms. It emphasizes the importance of data preprocessing for ML models and discusses challenges like false positives, false negatives and model comprehension. The chapter also highlights the potential of natural language processing (NLP) in fraud detection.

Date: 2025
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DOI: 10.1007/978-3-031-81834-9_34

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