Fraud Detection in Supply Chain with Machine Learning

Mahdi Seify, Mehran Sepehri*, Amin Hosseinian-far, Aryana Darvish

*Corresponding author for this work

Research output: Contribution to JournalConference Article/Conference Proceedingspeer-review


A variety of fraud in Supply Chains may be detected either in physical parts or in cyber data. We use supervised machine learning to detect various fraud and misinformation in supply chains. The study is based on a car manufacturer concerned with increasing fraud, ranging from fraudulent invoices to inflated prices. Big data is provided for pattern recognition. A macro-level code is presented with actual algorithms developed in Python. The research is continuing, while the current work is presented with promising results.
Original languageEnglish
Pages (from-to)406-411
Number of pages6
Issue number10
Publication statusPublished - 26 Oct 2022
Event10th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2022 - La Cité des Congrès de Nantes 5, rue de Valmy BP 24102, 44041 Nantes Cedex 1, Nantes, France
Duration: 22 Jun 202224 Jun 2022

Bibliographical note

© 2023 The Authors


  • Machine Learning
  • Supply Chain
  • Fraud
  • Detection
  • pattern recognition


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