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

    Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

    1 Sitaatiot (Scopus)


    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.

    AlkuperäiskieliEi tiedossa
    Otsikko2018 IEEE International Conference on Fuzzy Systems (FUZZ)
    KustantajaThe Institute of Electrical and Electronics Engineers
    ISBN (painettu)978-1-5090-6020-7
    DOI - pysyväislinkit
    TilaJulkaistu - 2018
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
    Tapahtuma2018 IEEE International Conference on Fuzzy Systems (FUZZ) - 2018 IEEE International Conference on Fuzzy Systems (FUZZ)
    Kesto: 8 heinäk. 201813 heinäk. 2018


    Konferenssi2018 IEEE International Conference on Fuzzy Systems (FUZZ)


    • Analytics
    • Fraud detection
    • Fuzzy C-Means