IIM  Vol.5 No.3 , May 2013
Business Intelligence Expert System on SOX Compliance over the Purchase Orders Creation Process
ABSTRACT

The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility and quality of the Purchase Orders Creation Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques. This proposed model directly contributes to both scientific research artificial intelligent area and business practices. From business perspective it empowers the use of artificial intelligent models and techniques to drive decision making processes over financial statements. From scientific and research area the impact is based on the combination of 1) an Information Seeking Dialog Protocol in which a requestor agent inquires the business case, 2) a Facts Valuation based Protocol in which the previously gathered facts are analyzed, 3) the already incorporated initial knowledge of a human expert via initial beliefs, 4) the Intra-Agent Decision Making Protocol based on deductive argumentation and 5) the semi automated Dynamic Knowledge Learning Protocol. Last but not least the suggested way of integration of this proposed model in a higher level multiagent intelligent system in which a Joint Deliberative Dialog Protocol and an Inter-Agent Decision Deductive Argumentation Making Protocol are described.


Cite this paper
J. Fernandez, Q. Martin and J. Rodriguez, "Business Intelligence Expert System on SOX Compliance over the Purchase Orders Creation Process," Intelligent Information Management, Vol. 5 No. 3, 2013, pp. 49-72. doi: 10.4236/iim.2013.53007.
References
[1]   J. Fox, P. Krause and S. Ambler, “Arguments, Contradictions and Practical Reasoning,” Proceedings of the 10th European Conference on Artificial Intelligence (ECAI-92), Vienna, 3-7 August 1992, pp. 623-627.

[2]   P. Krause, S. Ambler, M. Elvang-Goransson and J. Fox, “A Logic of Argumentation for Reasoning under Uncertainty,” Computational Intelligence, Vol. 11, No. 1, 1995, pp. 113-131. doi:10.1111/j.1467-8640.1995.tb00025.x

[3]   Y. Dimpoulos, B. Nebel and F. Toni, “Preferred Arguments Are Harder to Compute than Stable Extensions,” Proceedings of the 16th International Joint Conference on Artificial Intelligence (IJCAI-99), Stockholm, 31 July-6 August 1999, pp. 36-41.

[4]   P. M. Dung, “On the Acceptability of Arguments and Its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and N-Person Games,” Artificial Intelligence, Vol. 77, No. 2, 1995, pp. 321-357. doi:10.1016/0004-3702(94)00041-X

[5]   P. Besnard and A. Hunter, “Elements of Argumentation,” The MIT Press, Cambridge, 2008.

[6]   T. J. M. Bench-Capon and P. E. Dune, “Argumentation in Artificial Intelligence,” Artificial Intelligence, Vol. 171, No. 10-15, 2007, pp. 619-641. doi:10.1016/j.artint.2007.05.001

[7]   S. Kraus, K. Sycara and A. Evenchik, “Reaching Agreements through Argumentation: A Logical Model and Implementation,” Artificial Intelligence, Vol. 104, No. 1-2, 1998, pp. 1-69. doi:10.1016/S0004-3702(98)00078-2

[8]   I. Rahwan and P. McBurney, “Argumentation Technology,” IEEE Intelligent Systems, Vol. 22, No. 6, 2007, pp 21-23. doi:10.1109/MIS.2007.109

[9]   I. Rahwan and G. Simari, “Argumentation in Artificial Intelligence,” Springer, New York, 2009.

[10]   G. Boella, J. Hulstijn and L. Torre, “A Logic of Abstract Argumentation,” In: S. Parsons, N. Maudet, P. Moraitis and I. Rahwan, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2005), Vol. 4049, Springer, Berlin, 2006, pp. 29-41.

[11]   D. N. Walton and C. W. Krabbe, “Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning,” Suny Press, Albany, 1995.

[12]   E. Cogan, S. Parsons and P. McBurney, “New Types of Inter-Agent Dialogues,” In: S. Parsons, N. Maudet, P. Moraitis and I. Rahwan, Eds., Argumentation in MultiAgent Systems (ArgMAS 2005), Vol. 4049, Springer, Berlin, 2006, pp. 154-168.

[13]   L. Amgoud and N. Hameurlain, “An ArgumentationBased Approach for Dialog Move Selection,” In: N. Maudet, S. Parsons and I. Rahwan, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2006), Vol. 4766, Springer, Berlin, 2007, pp. 128-141.

[14]   Y. Tang and S. Parsons, “Argumentation-Based MultiAgent Dialogues for Deliberation,” In: S. Parsons, N. Maudet, P. Moraitis and I. Rahwan, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2005), Vol. 4049, Springer, Berlin, 2006, pp. 229-244.

[15]   L. Amgoud, N. Maudet and S. Parsons, “Modelling Dialogues using Argumentation,” Proceedings of the 4th International Conference on Multi-Agent Systems (ICMAS-2000), Boston, 10-12 July 2000, pp. 31-38.

[16]   C. Reed, “Dialogue Frames in Agent Communication,” Proceedings of the 3rd International Conference on Multi Agent Systems (ICMAS-98) Paris, 3-7 July 1998, pp. 246-253.

[17]   S. Parsons, M. Wooldridge and L. Amgoud, “On the Outcomes of Formal Inter-Agent Dialogues,” ACM Press, New York, 2003.

[18]   E. Sklar and S. Parsons, “Towards the Application of Argumentation-Based Dialogues for Education,” Proceedings of the 3rd International Conference on Autonomous Agents and Multi-Agent Systems, New York, 23 July 2004, pp. 1420-1421.

[19]   A. Belesiotis, M. Rovatsos and I. Rahwan, “A Generative Dialogue System for Arguing about Plans in Situation Calculus,” In: P. McBurney, I. Rahwan, S. Parsons and N. Maudet, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2009), Vol. 6057, Springer, Berlin, 2010, pp. 23-41.

[20]   J. Devereux and C. Reed, “Strategic Argumentation in Rigorous Persuasion Dialogue,” In: P. McBurney, I. Rahwan, S. Parsons and N. Maudet, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2009), Vol. 6057, Springer, Berlin, 2010, pp. 94-113.

[21]   P.-A. Matt, F. Toni and J. Vaccari, “Dominant Decisions by Argumentation Agents,” In: P. McBurney, I. Rahwan, S. Parsons and N. Maudet, Eds., Argumentation in MultiAgent Systems (ArgMAS 2009), Vol. 6057, Springer, Berlin, 2010, pp. 42-59.

[22]   M. Wardeh, T. Bech-Capon and F. Coenen, “Multi-Party Argument from Experience,” In: P. McBurney, I. Rahwan, S. Parsons and N. Maudet, Eds., Argumentation in MultiAgent Systems (ArgMAS 2009), Vol. 6057, Springer, Berlin, 2010, pp. 216-235.

[23]   M. Morge and P. Mancarella, “Assumption-Based Argumentation for the Minimal Concession Strategy,” In: P. McBurney, I. Rahwan, S. Parsons and N. Maudet, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2009), Vol. 6057, Springer, Berlin, 2010, pp. 114-133.

[24]   M. Thimm, “Realizing Argumentation in Multi-Agent Systems Using Defeasible Logic Programming,” In: P. McBurney, I. Rahwan, S. Parsons and N. Maudet, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2009), Vol. 6057, Springer, Berlin, 2010, pp. 175-194.

[25]   C. Changchit, C. Holsapple and D. Madden, “Positive Impacts of an Intelligent System on Internal Control Problem Recognition,” Proceedings of the 32nd Hawaii International Conference on System Sciences, Maui, 5-8 January 1999, p. 10.

[26]   R. Meservy, “Auditing Internal Controls: A Computational Model of the Review Process (Expert Systems, Cognitive, Knowledge Acquisition, Validation, Simulation),” PhD Thesis, University of Minnesota, Minneapolis, 1985.

[27]   S. O’Callaghan, “An Artificial Intelligence Application of Backpropagation Neural Networks to Simulate Accountants’ Assessments of Internal Control Systems Using COSO Guidelines,” PhD Thesis, University of Cincinnati, Cincinnati, 1994.

[28]   F. Liu, R. Tang and Y. Song, “Information Fusion Oriented Fuzzy Comprehensive Evaluation Model on Enterprises’ Internal Control Enviroment,” Proceedings of the 2009 Asia-Pacific Conference on Information Processing, Shenzhen, 18-19 July 2009, pp. 32-34. doi:10.1109/APCIP.2009.16

[29]   A. Kumar and R. Liu, “A Rule-Based Framework Using Role Patterns for Business Process Compliance,” In: N. Bassiliades, G. Governatori and A. Paschke, Eds., Proceedings of the International Symposium on Rule Representation, Interchange and Reasoning on the Web, Vol. 5321, Orlando, 30-31 October 2008, pp. 58-72. doi:10.1007/978-3-540-88808-6_9

[30]   C. Changchit and C. W. Holsapple, “The Development of an Expert System for Managerial Evaluation of Internal Controls,” Intelligent Systems in Accounting, Finance and Management, Vol. 12, No. 2, 2004, pp. 103-120. doi:10.1002/isaf.246

[31]   A. Korvin, M. Shipley and K. Omer, “Assessing Risks Due to Threats to Internal Control in a Computer-Based Accounting Information System: A Pragmatic Approach Based on Fuzzy Set Theory,” Intelligent Systems in Accounting, Finance and Management, Vol. 12, No. 2, 2004, pp. 139-152. doi:10.1002/isaf.249

[32]   A. Deshmukh and L. Talluru, “A Rule-Based Fuzzy Reasoning System for Assesing the Risk of Management Fraud,” Intelligent Systems in Accounting, Finance & Management, Vol. 7, No. 4, 1998, pp. 223-241. doi:10.1002/(SICI)1099-1174(199812)7:4%3C223::AID-ISAF158%3E3.0.CO;2-I

[33]   K. M. Fanning and K. O. Cogger, “Neural Network Detection of Management Fraud Using Published Financial Data,” International Journal of Intelligent Systems in Accounting, Finance & Management, Vol. 7, No. 1, 1998, pp. 21-41. doi:10.1002/(SICI)1099-1174(199803)7:1%3C21::AID-ISAF138%3E3.0.CO;2-K

[34]   J. Coakley, L. Gammill and C. Brown, “Artificial Neural Networks in Accounting and Finance,” Oregon State University, Corvallis, 1995.

[35]   K. M. Fanning and K. O. Cogger, “A Comparative Analysis of Artificial Neural Networks Using Financial Distress Prediction,” International Journal of Intelligent Systems in Accounting, Finance and Management, Vol. 3, 1994, pp. 241-252.

[36]   O. J. Welch, T. E. Reeves and S. T. Welch, “Using a Genetic Algotithm-Based Classifier System for Modeling Auditor Decision Behaviour in a Fraud Setting,” International Journal of Intelligent Systems in Accounting, Finance and Management, Vol. 7, No. 3, 1998, pp. 173-186. doi:/10.1002/(SICI)1099-1174(199809)7:3<173::AID-ISAF147>3.0.CO;2-5

[37]   R. P. Srivastava, S. K. Dutta and R. W. Johns, “An Expert System Approach to Audit Planning and Evaluation in the Belief-Function Framework,” International Journal of Intelligent Systems in Accounting, Finance and Management, Vol. 5, No. 3, 1996, pp. 165-183.

[38]   S. Sarkar, R. S. Sriram and S. Joykutty, “Belief Networks for Expert System Development in Auditing,” International Journal of Intelligent Systems in Accounting, Finance and Management, Vol. 5, No. 3, 1998, pp. 147-163. doi:/10.1002/(SICI)1099-1174(199609)5:3<147::AID-ISAF108>3.0.CO;2-F

[39]   M. Capobianco, C. Chesñevar and G. R. Simari, “An Argument-Based Framework to Model an Agent’s Beliefs in a Dynamic Environment,” In: I. Rahwan, P. Moraitis and C. Reed, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2004), Vol. 3366, Springer, Berlin, 2005, pp. 95-110.

[40]   T. Fukumoto and H. Sawamura, “Argumentation-Based Learning,” In: N. Maudet, S. Parsons and I. Rahwan, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2006), Vol. 4766, Springer, Berlin, 2007, pp. 17-35.

[41]   D. Capera, J. P. Georgé, M. P. Gleizes and P. Glize, “Emergence of Organisations, Emergence of Functions,” AISB03 Convention, 2003.

[42]   R. Razavi, J. Perrot and N. Guelfi, “Adaptive Modeling: An Approach and a Method for Implementing Adaptive Agents,” Massively Multi-Agent Systems, Vol. 3446, 2005, pp. 136-148.

[43]   D. Weyns, K. Schelfthout, T. Holvoet and O. Glorieux, “Role Based Model for Adaptive Agents,” BASYS04 Convention, 2004.

[44]   F. Zambonelli, N. R. Jennings and M. Wooldridge, “Developing Multiagent Systems: The Gaia Methodology,” ACM Transactions on Software Engineering and Methodology, Vol. 12, No. 3, 2003, pp. 317-370.

[45]   S. Ontañon and E. Plaza, “Arguments and Counterexamples in Case-Based Joint Deliberation,” In: N. Maudet, S. Parsons and I. Rahwan, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2006), Vol. 4766, Springer, Berlin, 2007, pp. 36-53.

[46]   S. Parsons and E. Sklar, “How Agents Alter Their Beliefs after an Argumentation-Based Dialogue,” In: S. Parsons, N. Maudet, P. Moraitis and I. Rahwan, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2005), Vol. 4049, Springer, Berlin, 2006, pp. 297-312.

[47]   A. Kakas, N. Maudet and P. Moraitis, “Layered Strategies and Protocols for Argumentation-Based Agent Interaction,” In: I. Rahwan, P. Moraitis and C. Reed, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2004), Vol. 3366, Springer, Berlin, 2005, pp. 64-77.

[48]   S. Rodriguez, Y. de Paz, J. Bajo and J. M. Corchado, “Social-Based Planning Model for Multiagent Systems,” Expert Systems with Applications, Vol. 38, No. 10, 2011, pp. 13005-13023. doi:/10.1016/j.eswa.2011.04.101

[49]   J. M. Corchado and R. Laza, “Constructing Deliberative Agents with Case-Based Reasoning Technology,” International Journal of Intelligent Systems, Vol. 18, No. 12, 2003, pp. 1227-1241. doi:/10.1002/int.10138

[50]   J. M. Corchado, R. Laza, L. Borrajo, J. C. Yanes and M. Valiño, “Increasing the Autonomy of Deliberative Agents with a Case-Based Reasoning System,” International Journal of Computational Intelligence and Applications, Vol. 3, No. 1, 2003, p. 101 doi:/10.1142/S1469026803000823

[51]   M. Esteva, J.-A. Rodríguez-Aguilar, C. Sierra, P. Garcia and J. L. Arcos, “On the Formal Specifications of Electronic Institutions,” In: F. Dignum and C. Sierra, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2001), Vol. 1991, Springer, Berlin, 2001, pp. 126-147. doi:/10.1007/3-540-44682-6_8

[52]   J. F. Hübner, J. S. Sichman and O. Boissier, “Using the MOISE+ for a Cooperative Framework of MAS Reorganisation,” In: A. L. C. Bazzan and S. Labidi, Eds., Advances in Artificial Intelligence-SBIA 2004, Vol. 3171, Springer, Berlin, 2004, pp. 506-515.

[53]   H. Van D. Parunak and J. J. Odell, “Representing Social Structures in UML,” In: M. J. Wooldridge, G. Weiß and P. Ciancarini, Eds., Agent-Oriented Software Engineering II, Vol. 2222, Springer, Berlin, 2002, pp. 1-16.

[54]   M. Morge and P. Mancarella, “The Hedgehog and the Fox. An Argumentation-Based Decison Support System,” Proceedings of the 4th International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2007), Springer, Berlin, 2008, pp. 55-68.

 
 
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