Symposium 2009. Discussant’s comments -. Data Mining Journal Entries for Fraud Detection: A Pilot Study – R S Debreceny & Glen L Gray. Eckhardt Kriel. MOTIVATION - JUSTIFICATION. MOTIVATION - JUSTIFICATION. I want to congratulate the authors on a very interesting and topical paper .
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Data Mining Journal Entries for Fraud Detection: A Pilot Study – R S Debreceny & Glen L Gray
Trial Balance Roll-Up
Data Anomaly Tests
Blank Date Fields
Zero Dollar Items
Blank Account Numbers
Unbalanced Journal Entries
Blank transaction description
Blank Preparer ID
Foreign Currency Adjustments
Additional Testing Procedures:
Debits to Income Accounts and Credits to Expense Accounts
Debits to Liability Accounts and Credits to Income Accounts
Debits to Asset Accounts and Credits to Income Accounts
Debits to Fixed Assets and Credits to Expenses
etc., etc., etc.
SAS 99 details a number of procedures that auditors can follow to respond to the objective of consideration of fraud in F/S audit. Journal entry testing is one of these.
I have reservations that, on its own, journal entry testing, is effective. So any paper or article on the subject must include it as one of a combination of tests.
To detect potential irregularity in financial statements any analysis must be
It must contemplate fraudulent misstatement and profile its characteristics;
It must search for the characteristics;
It must be broadly based.
Expanding on SAS 99 Paragraphs 28/29/30
Benford on Listed Company Results – AD Saville1
1. Reference: SAJEMS NS 9 (2006) No 3 341
Advanced Financial Reporting Analysis – Example MICROSTRATEGY – Application of Different tests
Stephen Few’s2 Commentary on Gladwell:
“Modern problems, on the other hand, are not the result of missing or hidden information, Gladwell argues, but the result, in a sense, of too much information and the complicated challenge of understanding it.
The problems that we face today do not exist because we lack information, but because we don’t understand it. They can be solved only by developing skills and tools to make sense of information that is often complex.
In other words, the major obstacle to solving modern problems isn’t the lack of information, solved by acquiring it, but the lack of understanding, solved by analytics.”
2. Visual Business Intelligence
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