Discussion of:A Taxonomy to Guide Research on the Application of Data Mining to
Fraud Detection in Financial Statement Analysis
Severin Grabski Department of Accounting & Information
SystemsMichigan State University
The Good – Why Data Mining“Data mining outperforms rules-based systems for detecting fraud, even as fraudsters become more sophisticated in their tactics. “Models can be built to cross-reference data from a variety of sources, correlating nonobvious variables with known fraudulent traits to identify new patterns of fraud,”…”
Source:http://www.sas.com/content/dam/SAS/en_us/doc/whitepaper1/data-mining-a-z-104937.pdf
The Good• Builds upon Data Mining of E-
Mail Research/Framework• Liked Framework • Incorporated Data Outside of
the AIS into Data Mining (Fig. 5)• Linked Data Mining to “Potential
Payoff” Matrix (Fig. 6)
The Good• Data Mining Makes the Most Sense
When You Have a Story • Need Institutional & Audit Knowledge
• Research Linked Fraud Types to a Story• Account Schemes• Evidence Schemes
The Missing• Could not find a Precise Definition
of “Data Mining” • Is it “Big D” or “Little D”?
Knowledge Discovery in Databases - KDD
Source:http://www.kmining.com/info_definitions.html
The Missing• Data Mining Task
• Automatic (Semi-Automatic) Analysis of Large Quantities of Data to Extract Patterns, Anomalies, Dependencies
Data Mining TasksAnomaly Detection Association Rule
Learning
Clustering Classification
Regression Summarization
Sequential Pattern Matching
The Missing• Data Mining Process Should be
Based upon an Existing Standard Methodology
• CRISP-DM• Cross Industry Standard Process for
Data Mining
The Missing• CRISP-DM
• Business Understanding• Data Understanding• Data Preparation• Modeling• Evaluation• Deployment
• CRISP-DM
Source: http://en.wikipedia.org/wiki/File:CRISP-DM_Process_Diagram.png
The Missing
The Missing• List of Data Mining Techniques/Tools• Suggestion of Appropriate
Techniques to use in a Given Situation
• Example of Data Mining Tool Application
The Missing• Title is “A Taxonomy to Guide
Research on the Application of Data Mining to Fraud Detection in Financial Statement Analysis”
• Not Sure How the Taxonomy is Supposed to Guide Research
The Unanswered• Where does Data Mining Most
Benefit the Audit?• Suspected Frauds?• Entire Audit Process?Planning Risk
AssessmentExecution Tests of ControlsReporting Substantive
Tests
Questions
Given the Benefits of Continuous Auditing, is Data Mining a “Temporary” Solution?
QuestionsCost-Benefit of Data Mining w/r/t Potential Fraud
• Gao & Srivastava (2011) – 100 SEC Enforcement Actions 1997-2002• If 2800 NYSE & 3200 NASDAQ
Firms• Not Even .0028% Had Action!
Questions
Cost-Benefit of Data Mining?
Audit FirmClientSociety (Investor)
Conclusion• Liked Development of Framework• Liked the Matrix (Fig. 6)• Would Have Liked More:
• Precision• Linkage to Data Mining
Methodologies• Linkage of Techniques to Audit
Settings• Use Outside of Fraud Audit
