CBR Based Engine for Business Internal Control

The complexity of current organization systems and the increase in importance of the realization of internal controls in firms makes the construction of models that automate and facilitate the work of the auditors crucial. A tool for the decision support process has been developed based on a multi-cbr system that incorporates two case-based reasoning systems and automates the business control process. The objective of the system is to facilitate the process of internal audit in small and medium firms. The multi-cbr system analyses the data that characterises each one of the activities carried out by the firm, then determines the state of each activity, calculates the associated risk, detects the erroneous processes, and generates recommendations to improve these processes. Therefore, the system is a useful tool for the internal auditor in order to make decisions based on the obtained risk. Each one of the case-based reasoning systems that integrates the multi-agent system uses a different problem solving method in each step of the reasoning cycle: a Maximum Likelihood Hebbian learning-based method that automates the organization of cases and the retrieval phase, an Radial Based Function neural network and a multi-criterion discreet method during the reuse phase and a rule based system for recommendation generation. The multi-cbr system has been tested in 14 small and medium size companies during the last 26 months in the textile sector, which are located in the northwest of Spain. The achieved results have been very satisfactory