Title :
On-line evolving clustering for financial statements´ anomalies detection
Author :
Omanovic, Samir ; Avdagic, Zikrija ; Konjicija, Samim
Author_Institution :
Fac. of Electr. Eng., Dept. of Comput. & Inf., Univ. of Sarajevo, Sarajevo, Bosnia-Herzegovina
Abstract :
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.
Keywords :
accounts data processing; fraud; management accounting; pattern classification; pattern clustering; software maintenance; accounting system; business financial activity; financial fraud detection; financial statement anomaly detection; journal recording; ledger recording; official record; online evolving clustering algorithm; software error; software maintenance lifecycle change; supervised classification process; Authentication; Data security; Databases; Information security; Performance analysis; Privacy; Product codes; Radio frequency; Radiofrequency identification; Scalability; anomalies detection; evolving clustering; fraud detection;
Conference_Titel :
Information, Communication and Automation Technologies, 2009. ICAT 2009. XXII International Symposium on
Conference_Location :
Bosnia
Print_ISBN :
978-1-4244-4220-1
Electronic_ISBN :
978-1-4244-4221-8
DOI :
10.1109/ICAT.2009.5348416
