Fuzzy C-Means for Fraud Detection in Large Transaction Data Sets

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1 Citeringar (Scopus)

Sammanfattning

Large, multinational corporations typically have to process hundreds and thousands of vendor invoices every day coming from hundreds or thousands of vendors in different currencies from many countries. This has forced the adoption of simple and fast rules of thumb to accept and pay invoices below a chosen value cutoff without further scrutiny. This has invited fraud, which is hard to detect and react to, as the transaction data sets are very large. Fuzzy C-means has turned out to be effective to identify and sort out transactions, which are similar to typical fraud cases.

OriginalspråkOdefinierat/okänt
Titel på gästpublikation2018 IEEE International Conference on Fuzzy Systems (FUZZ)
FörlagThe Institute of Electrical and Electronics Engineers
Sidor
ISBN (tryckt)978-1-5090-6020-7
DOI
StatusPublicerad - 2018
MoE-publikationstypA4 Artikel i en konferenspublikation
Evenemang2018 IEEE International Conference on Fuzzy Systems (FUZZ) - 2018 IEEE International Conference on Fuzzy Systems (FUZZ)
Varaktighet: 8 jul 201813 jul 2018

Konferens

Konferens2018 IEEE International Conference on Fuzzy Systems (FUZZ)
Period08/07/1813/07/18

Nyckelord

  • Analytics
  • Fraud detection
  • Fuzzy C-Means

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