Opportunities for artificial intelligence development in the accounting domain: the case for auditing

This paper reviews the nature of accounting and auditing problems and the need for application of artificial intelligence (AI) technologies to the discipline. The discussion includes current accounting issues for which new AI development should be fruitful, particularly auditing and assurance.

[1]  Jay C. Thibodeau,et al.  The Development and Transferability of Task Knowledge , 2002 .

[2]  Anurag Agarwal,et al.  Predicting the outcome following bankruptcy filing: a three-state classification using neural networks , 1997, Intell. Syst. Account. Finance Manag..

[3]  Guido Dedene,et al.  A Comparison of State-of-The-Art Classification Techniques for Expert Automobile Insurance Claim Fraud Detection , 2002 .

[4]  Anthony Wensley,et al.  Structuring the Assessment of Audit Evidence -- An Expert Systems Approach , 1990 .

[5]  Parag C. Pendharkar,et al.  A threshold-varying artificial neural network approach for classification and its application to bankruptcy prediction problem , 2005, Comput. Oper. Res..

[6]  Ram S. Sriram,et al.  A Comparison of Selected Artificial Neural Networks that Help Auditors Evaluate Client Financial Viability , 2000, Decis. Sci..

[7]  Ran Barniv,et al.  Predicting the outcome following bankruptcy filing: a three-state classification using neural networks , 1997, Intell. Syst. Account. Finance Manag..

[8]  John S. Chandler,et al.  Auditor: a microcomputer‐based expert system to support auditors in the field , 1985 .

[9]  Carol E. Brown,et al.  Expert Systems for Management Accounting Tasks , 1995 .

[10]  Glenn Shafer,et al.  Belief-Function Formulas for Audit Risk , 2008, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[11]  David E. Booth,et al.  An Analysis of Fuzzy Clustering and a Hybrid Model for the Auditor's Going Concern Assessment , 2000, Decis. Sci..

[12]  Thomas E. McKee,et al.  Genetic programming and rough sets: A hybrid approach to bankruptcy classification , 2002, Eur. J. Oper. Res..

[13]  Amelia Annette Baldwin-Morgan.  The impact of expert system audit tools on auditing firms in the year 2001: A Delphi investigation , 1993 .

[14]  Jesse F. Dillard,et al.  A Responsibility Ethics for Audit Expert Systems , 2001 .

[15]  Jerrold H. May,et al.  A Hybrid System Improves Claims Auditing at Blue Cross , 1993 .

[16]  Gregory R. Madey,et al.  The Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision* , 1995 .

[17]  Jean C. Bedard,et al.  KRiskSM: A Computerized Decision Aid for Client Acceptance and Continuance Risk Assessments , 2002 .

[18]  Carol E. Brown,et al.  Artificial neural networks in accounting and finance: modeling issues , 2000, Intell. Syst. Account. Finance Manag..

[19]  Szymon Wilk,et al.  Evaluating business credit risk by means of approach-integrating decision rules and case-based learning , 2001, Intell. Syst. Account. Finance Manag..

[20]  Margaret F. Shipley,et al.  Assessing risks due to threats to internal control in a computer-based accounting information system: a pragmatic approach based on fuzzy set theory , 2004, Intell. Syst. Account. Finance Manag..

[21]  Ashutosh Deshmukh,et al.  Measurement and Combination of Red Flags to Assess the Risk of Management Fraud: A Fuzzy Set Approach , 1997 .

[22]  Monica Lam,et al.  Neural network techniques for financial performance prediction: integrating fundamental and technical analysis , 2004, Decis. Support Syst..

[23]  Michael Y. Hu,et al.  Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis , 1999, Eur. J. Oper. Res..

[24]  Robert H. Michaelsen.  An expert system for federal tax planning , 1984 .

[25]  Philip M. J. Reckers,et al.  The Effects of Decision‐Aid Use and Reliability on Jurors' Evaluations of Auditor Liability , 2002 .

[26]  N. Connell.  Expert Systems in Accountancy: A Review of Some Recent Applications , 1987 .

[27]  R. J. Chambers.  Accounting, finance and management , 1969 .

[28]  Carol E. Brown,et al.  Artificial neural networks in accounting and finance: modeling issues , 2000 .

[29]  Robert Scott,et al.  An intelligent forecasting support system in auditing: expert system and neural network approach , 1994, 1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences.

[30]  J. Peters.  A Cognitive Computational Model Of Risk Hypothesis Generation , 1990 .

[31]  L. Thorne McCarty,et al.  Reflections on "Taxman": An Experiment in Artificial Intelligence and Legal Reasoning , 1977 .

[32]  Catherine Usoff,et al.  A longitudinal study of applicable decision aids for detailed tasks in a financial audit , 2001, Intell. Syst. Account. Finance Manag..

[33]  Carol E. Brown,et al.  The Uses of Advanced Information Technology in Audit Planning , 1992 .

[34]  Carol E. Brown.  Expert systems in public accounting: Current practice and future directions , 1991 .

[35]  George M. Mohay,et al.  Machine-independent audit trail analysis - a tool for continuous audit assurance , 2004, Intell. Syst. Account. Finance Manag..

[36]  Gregory R. Madey,et al.  The Design and Validation of a Hybrid Information System for the Auditor's Going Concern Decision , 1998, J. Manag. Inf. Syst..

[37]  Thomas E. Reeves,et al.  Using a genetic algorithm-based classifier system for modeling auditor decision behavior in a fraud setting , 1998 .

[38]  Emmanuel Haven,et al.  The fuzzy multicriteria analysis method: an application on NPV ranking , 1998, Intell. Syst. Account. Finance Manag..

[39]  Thomas G. Calderon,et al.  A roadmap for future neural networks research in auditing and risk assessment , 2002, Int. J. Account. Inf. Syst..

[40]  Thomas R. Sexton,et al.  A Fuzzy Logic Approach to Assessing Materiality , 2005 .

[41]  Kostas S. Metaxiotis,et al.  Expert systems in business: applications and future directions for the operations researcher , 2003, Ind. Manag. Data Syst..

[42]  Eija Koskivaara,et al.  Artificial neural networks in analytical review procedures , 2004 .

[43]  Clyde W. Holsapple,et al.  Supporting managers' internal control evaluations: an expert system and experimental results , 2001, Decis. Support Syst..

[44]  Clyde W. Holsapple,et al.  The development of an expert system for managerial evaluation of internal controls , 2004, Intell. Syst. Account. Finance Manag..

[45]  Alan Sangster.  The adoption of IT in management accounting: the expert systems experience , 1994, J. Inf. Technol..

[46]  Rayman D. Meservy,et al.  Internal Control Evaluation: A Computational Model of the Review Process , 1986 .

[47]  Andrew D. Bailey,et al.  Risk assessment in internal auditing: a neural network approach , 1999, Intell. Syst. Account. Finance Manag..

[48]  M. Abdolmohammadi.  Factors affecting auditors' perceptions of applicable decision aids for various audit tasks* , 1991 .

[49]  Carol E. Brown,et al.  The Fourth International Symposium on Intelligent Systems in Accounting, Finance and Management , 1994 .

[50]  Mohammad J. Abdolmohammadi,et al.  Decision Support and Expert Systems in Auditing: A Review and Research Directions , 1987 .

[51]  Thomas E. McKee,et al.  Bankruptcy theory development and classification via genetic programming , 2006, Eur. J. Oper. Res..

[52]  James V. Hansen,et al.  Expert systems for decision support in EDP auditing , 1982, International Journal of Computer & Information Sciences.

[53]  Ram S. Sriram,et al.  A comparison of the relative costs of financial distress models: artificial neural networks, logit and multivariate discriminant analysis , 1997, Intell. Syst. Account. Finance Manag..

[54]  Ingoo Han,et al.  CRAS‐CBR: Internal control risk assessment system using case‐based reasoning , 2004, Expert Syst. J. Knowl. Eng..

[55]  David S. Murphy,et al.  Auditor evidence evaluation: Expert systems as credible sources , 1996, Behav. Inf. Technol..

[56]  David C. Yen,et al.  Auditing in the e-commerce era , 2004, Inf. Manag. Comput. Secur..

[57]  L. Richard Ye,et al.  The Impact of Explanation Facilities in User Acceptance of Expert System Advice , 1995, MIS Q..

[58]  Daniel E. O'Leary,et al.  Auditor environmental assessments , 2003, Int. J. Account. Inf. Syst..

[59]  Hian Chye Koh,et al.  Going concern prediction using data mining techniques , 2004 .

[60]  C. E. Brown.  Accounting expert systems: a comprehensive, annotated bibliography , 1989 .

[61]  Jae K. Shim,et al.  Expert systems applications to managerial accounting , 1988 .

[62]  Emmanuel E. Haven.  The fuzzy multicriteria analysis method: an application on NPV ranking , 1998 .

[63]  Laurie Swinney,et al.  Consideration of the social context of auditors' reliance on expert system output during evaluation of loan loss reserves , 1999, Intell. Syst. Account. Finance Manag..

[64]  Rajendra P. Srivastava,et al.  Detection of management fraud: a neural network approach , 1995, Proceedings the 11th Conference on Artificial Intelligence for Applications.

[65]  Murugan Anandarajan,et al.  Bankruptcy prediction of financially stressed firms: an examination of the predictive accuracy of artificial neural networks , 2001, Intell. Syst. Account. Finance Manag..

[66]  R. P. Srivastava,et al.  Attribute Sampling: A Belief‐Function Approach to Statistical Audit Evidence , 2000 .

[67]  Gregory R. Madey,et al.  Decision-making capabilities of a hybrid system applied to the auditor's going-concern assessment , 2001, Intell. Syst. Account. Finance Manag..

[68]  Donald R. Jones,et al.  Reliance on Decision Aids: An Examination of Auditors' Assessment of Management Fraud , 1997 .

[69]  Mark I. Hwang,et al.  A fuzzy neural network for assessing the risk of fraudulent financial reporting , 2003 .

[70]  Anne P. Massey,et al.  Supporting a complex audit judgment task: An expert network approach , 1997 .

[71]  Kimberly K. Moreno,et al.  The Effect of Client vs. Decision Aid as a Source of Explanations upon Auditors' Sufficiency Judgments: A Research Note , 2003 .

[72]  Eija Koskivaara.  Artificial neural network models for predicting patterns in auditing monthly balances , 1997, ECIS.