Database systems: achievements and opportunities
Communications of the ACM
Management information systems (6th ed.): a study of computer-based information systems
Management information systems (6th ed.): a study of computer-based information systems
Data mining with neural networks: solving business problems from application development to decision support
The data warehouse and data mining
Communications of the ACM
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Integrating inductive and deductive reasoning for data mining
Advances in knowledge discovery and data mining
Discovering data mining: from concept to implementation
Discovering data mining: from concept to implementation
Data mining using extensions of the rough set model
Journal of the American Society for Information Science - Special issue: knowledge discovery and data mining
Feature selection and effective classifiers
Journal of the American Society for Information Science - Special issue: knowledge discovery and data mining
Enhancing data quality in data warehouse environments
Communications of the ACM
Data mining: new arsenal for strategic decision-making
Journal of Database Management
An integrated overview of key issues in data mining
An integrated overview of key issues in data mining
Computers!
Statistical Themes and Lessons for Data Mining
Data Mining and Knowledge Discovery
Some Privacy Issues in Knowledge Discovery: The OECD Personal Privacy Guidelines
IEEE Expert: Intelligent Systems and Their Applications
An artificial intelligence application of backpropagation neural networks to simulate accountants' assessments of internal control systems using coso guidelines
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Accounting information systems enable the process of internal control and external auditing to provide a first-line defense in detecting fraud (Turpen & Messina, 1997). There are few valid indicators at either the individual or the organizational level which are reliable indicators of fraud prevention (Groveman, 1995). Recent studies have shown that it is nearly impossible to predict fraud. In fact, many of the characteristics associated with white-collar criminals are precisely the traits which organizations look for when hiring employees (Lord, 1997). This paper proposes the use of information systems to deal with fraud through proactive information collection, data mining, and decision support activities.