On-line evolving clustering for financial statements' anomalies detection

On-line evolving clustering for financial statements' anomalies detection

This document proposes an approach for financial statements' anomalies detection by using on-line evolving clustering. Official records of the financial activities of a business are called financial statements and they are recorded in journals and general ledger in a supervised process. Anomali...

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Bibliographische Detailangaben
Hauptverfasser: Omanovic, S., Avdagic, Z., Konjicija, S.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
anomalies detection
Authentication
Data security
evolving clustering
fraud detection
Information security
Performance analysis
Privacy
Product codes
Radio frequency
Radiofrequency identification
Scalability
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Beschreibung
Zusammenfassung:This document proposes an approach for financial statements' anomalies detection by using on-line evolving clustering. Official records of the financial activities of a business are called financial statements and they are recorded in journals and general ledger in a supervised process. Anomalies in financial statements are caused by human mistakes during forming of financial statements, or as a result of changes in the software that produced un-expected errors, or as possible financial fraud.
DOI:10.1109/ICAT.2009.5348416