NEURAT - Intelligent Digital Audit Knowledge Base Engine

The Intelligent Digital Audit Knowledge Base Engine project aims to make financial audit processes more accessible and clear, and to allow greater justice and fiscal equity. To achieve this, the consortium proposes the development of a knowledge-based intelligent decision support system in the financial audit process. This system should be able to (intelligently and autonomously) identify useful hidden patterns in data from the analysis of the work of auditors, infer the corresponding logical propositions, and thus improve, incrementally and autonomously, the accuracy and efficiency of the system in identifying "positive" occurrences.

In this solution, the consortium proposes to use the SAF-T files of organizations as the origin of the data on which the knowledge extraction processes will be applied, and to maintain the Human expert in the loop. The long term goals are to improve the effectiveness and efficiency of audit processes, allowing auditors to better focus their work on the cases that really matter.