Introduction and Aim: In today’s world, combating economic corruption in any organization, especially in the sensitive and vital health sciences sector, is of utmost importance. This research aims to identify and rank key audit drivers, seeking to provide practical solutions for strengthening the fight against economic corruption in health sciences organizations.
Methodology: This study employed a mixed-methods approach (qualitative and quantitative) and was conducted within the year 1403 (Persian calendar). In the qualitative phase, the grounded theory method was used to conduct interviews with 25 experts until theoretical saturation was achieved. In the quantitative phase, Friedman’s test was applied to rank the drivers.
Findings: According to the research results, twelve main drivers and forty sub-drivers were identified. Furthermore, the main driver of using Artificial Intelligence (AI) in auditing ranked first, the main driver of using data analytics in auditing ranked second, the main driver of using data analytics in auditing ranked third, the main driver of independence ranked fourth, the main driver of risk analysis ranked fifth, the main driver ranked sixth, the main driver ranked seventh, the main driver ranked eighth, the main driver ranked ninth, the main driver ranked tenth, the main driver ranked eleventh, and the main driver ranked twelfth.
Conclusion: The drivers of new technologies in auditing are powerful and efficient tools for detecting economic fraud and corruption. The use of blockchain, artificial intelligence, data analytics, network analysis, risk analysis, and environmental factor analysis can assist auditing in identifying financial statement fraud by reducing the possibility of unauthorized information alteration.