This study proposes using multiple criteria quadratic programming （MCQP） and other data mining approaches to predict auditor changes with early adopters of the Sarbanes-Oxley Act （SOX）. It compares 2003-2004 U.S. ...This study proposes using multiple criteria quadratic programming （MCQP） and other data mining approaches to predict auditor changes with early adopters of the Sarbanes-Oxley Act （SOX）. It compares 2003-2004 U.S. firm data with data from 2005-2006 to measure the SOX effect on firms that voluntarily adopted this new regulation nearly （other than the size of the business）. The results of the MCQP and other data mining approaches in this auditor change prediction study show that the MCQP method performs marginally better than other data mining approaches using financial and other data to predict auditor changes. In addition, the early SOX effect is not significant empirically using the auditor change prediction model of comparing the prediction rates of early adopters vs. those of later adopters.展开更多
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 Argument...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.展开更多
文摘This study proposes using multiple criteria quadratic programming （MCQP） and other data mining approaches to predict auditor changes with early adopters of the Sarbanes-Oxley Act （SOX）. It compares 2003-2004 U.S. firm data with data from 2005-2006 to measure the SOX effect on firms that voluntarily adopted this new regulation nearly （other than the size of the business）. The results of the MCQP and other data mining approaches in this auditor change prediction study show that the MCQP method performs marginally better than other data mining approaches using financial and other data to predict auditor changes. In addition, the early SOX effect is not significant empirically using the auditor change prediction model of comparing the prediction rates of early adopters vs. those of later adopters.
文摘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.
