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Cao Phuong Thao
Construction auditing risk detection using machine learning approaches /Cao Phuong Thao. -H.,2020
9 tr. ;27 cm
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 automatically detects auditing risk using machine learning approaches. The criteria to assess auditing risks will serve as inputs in the machine learning algorithms;and the output will be the ranking of low;medium;high level of auditing risk. The proposed two machine learning methods was tested on 80 construction projects in Vietnam and the result shows the high accuracy level of this method in auditing risk detection
1.Auditing2.Audit risk detection3.Neural network4.Random forest5.Machine learning

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