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

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 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