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A framework for discovering internal financial fraud using analytics
Published in IEEE Conferences
Pages: 1 - 2
In today's knowledge based society, financial fraud has become a common phenomenon. Moreover, the growth in knowledge discovery in databases and fraud audit has made the detection of internal financial fraud a major area of research. On the other hand, auditors find it difficult to apply a majority of techniques in the fraud auditing process and to integrate their domain knowledge in this process. In this Paper a framework called "Knowledge-driven Internal Fraud Detection (KDIFD)" is proposed for detecting internal financial frauds. The framework suggests a process-based approach that considers both forensic auditor's tacit knowledge base and computer-based data analysis and mining techniques. The proposed framework can help auditor in discovering internal financial fraud more efficiently.
About the journal
JournalData powered by TypesetProceedings 2011 International Conference on Communication Systems and Network Technologies, CSNT 2011
PublisherData powered by TypesetIEEE Conferences
Open AccessNo