Building a Model to Evaluate Internal Control at Industrial Companies Using Artificial Intelligence

Abstract

The study aimed to show the possibility of building a model to evaluate internal control at industrial companies using artificial intelligence, based upon the eight elements of internal control included in the COSO-ERM model. The study population consists of the industrial companies listed on Amman Stock Exchange, while the sampling unit consists of auditors and heads of audit departments in those companies. Concerning the tool of the study, two questionnaires and a practical program were prepared: the purpose of the first questionnaire was  to obtain data to help prepare the model, while the second questionnaire was prepared to obtain data to help evaluate the model. The descriptive analytical approach was used to describe the phenomenon and analyze the data statistically,  and the applied approach to build the study model practically, i.e.,  preparing a real practical program by  using artificial intelligence according to several algorithms (attached), then this model was practically evaluated by inputting the data obtained from the second questionnaire into the program to get the results (artificial intelligence decision), which  is related to the strength or weakness of companies' internal control. Also, the evaluation  was by  analyzing the data again statistically through using the SPSS program to obtain statistical results about the strength or weakness of the companies' internal control, and then to compare the results of the artificial intelligence program with the results of the statistical analysis. In case they are compatible, it is possible to rely on artificial intelligence in evaluating the internal control of companies, otherwise, it cannot be relied upon. The study got at  the possibility of building a model for evaluating internal control in industrial companies by using artificial intelligence, and it recommended to adopt the model for its ability to evaluate internal control, and to  try to perform other research to employ artifical intelligence in other fields in accounting.