Construction auditing risk detection using neural network

Abstract

Audit report plays a key role in determining the validity of final accounting in the completion of any construction project. However, the quality of reports depends heavily on the quality of the auditors themselves, whose variety of skill set and bias level could lead to different assessment outcome of the accounting risk level. This paper presents a method that detects auditing risk using neural network. The criteria to assess auditing risks will serve as inputs in the neural network, and the output will be the ranking of low, medium, high level of auditing risk. The proposed neural network was tested on 80 construction projects in Vietnam and the result shows the high accuracy level of this method in auditing risk detection.