Fraud Detection in Supply Chain with Machine Learning

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

Research output: Contribution to journalArticlepeer-review

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Abstract

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
JournalIFAC-PapersOnLine
Volume55
Issue number10
DOIs
Publication statusPublished - 26 Oct 2022

Keywords

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

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