Download A Taxonomy to Guide Research on the Application of Data

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 Systems
Michigan 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 crossreference 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/datamining-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 Tasks
Anomaly 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
The Missing
• CRISP-DM
Source: http://en.wikipedia.org/wiki/File:CRISP-DM_Process_Diagram.png
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 Assessment
Execution
Tests of Controls
Reporting
Substantive Tests
Questions
Given the Benefits of
Continuous Auditing, is
Data Mining a “Temporary”
Solution?
Questions
Cost-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 Firm
Client
Society (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