The Impact of Judicial Scrutiny in Reducing Financial and Administrative Corruption: An exploratory study from the point of view of auditors and academics in the Kurdistan Region - Iraq - نوزاد كاكەرش, بليسة; سليمان حمه سعيد الصالحي, ڤيان (The Scientific Journal of Cihan University– Sulaimaniya, 2024)
The study aims to demonstrate the impact of judicial audit in detecting and combating financial and administrative corruption in institutions and within administrative units. Judicial auditing is one of the modern and advanced professions, in addition to the fact that there are limitations in judicial auditing that focus on detecting fraud in clarifying responsibilities at the company level. Redoubling the process of appointing a judicial auditor in that field, and providing universities with specialized courses to study accounting and judicial auditing in this regard. This study was carried out by using a questionnaire tool distributed to a sample that consisted of three groups, namely, a group of auditors, certified accountants, and a group of teachers (academics) in the universities and institutes of the Kurdistan Region of Iraq. (120) questionnaires were distributed and (111) valid questionnaires were retrieved from them for analysis using the ready-made statistical program, SPSS and AMOS programs. The study reached a set of results and conclusions indicating the existence of a significant relationship between the independent and fixed variables within the framework of the descriptive approach of the study and in the light of testing the study’s hypotheses. Especially the legal and administrative knowledge in the fight against financial and administrative corruption. In light of the results and conclusions, the researcher recommended a set of recommendations, the most important of which is that the financial authorities in the Kurdistan Region of Iraq should integrate judicial auditing into control procedures in order to reduce and combat financial and administrative corruption, and the results were analyzed among the variables using multiple linear regression.