The Impact of Audit Process Automation on Fraud Detection in Technology-Oriented Companies

In recent decades, technology-oriented companies have faced significant risks of financial fraud due to the complexity and volume of their data. Audit process automation, leveraging artificial intelligence, machine learning, and data mining, offers new opportunities to enhance fraud detection capabilities. This study examines the impact of audit process automation on the effectiveness of fraud detection in technology-oriented companies. Data were collected via questionnaires from both internal and external auditors of technology firms and analyzed using multivariate regression and structural equation modeling (SEM). Results indicate that increased automation significantly improves fraud detection accuracy. Additionally, auditor expertise and organizational culture were found to moderate this relationship. The findings highlight the necessity of investing in audit technologies and training specialized personnel to improve financial reporting quality and reduce fraud risk.

کلیدواژه ها:

Audit automation ، Fraud detection ، Technology companies ، Artificial intelligence ، Auditor expertise