مجلة الإدارة والتنمية للبحوث والدراسات
Volume 14, Numéro 2, Pages 337-356
2025-12-01

Effectiveness Of Using Artificial Neural Networks In Mitigating Audit Risks: Case Study Of Setif Cement Company



Authors : Djarmouni Asma .

Abstract

Abstract: Study investigates effectiveness of applying artificial neural networks in reducing audit risks at Setif Cement Company, exploring how Artificial intelligence techniques can revolutionize audit practices by transforming traditional manual processes into technology-enhanced digital audits. A neural network model was developed and tested using SPSS v26 to classify audit risks across three levels (low, medium, high) within various operational domains including financial, commercial, production, maintenance, and purchasing activities. Study reached a set of results, most important of which are: artificial neural network achieved perfect classification accuracy (0.0% error) across the three risk categories, demonstrating superior performance with lift values of 5.0-10.0 compared to traditional methods while effectively managing complex relationships between audit risk variables, as it enhanced risk management culture by providing advanced analytical tools.

Keywords

artificial neural networks, audit risk, risk assessment, artificial intelligence.

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