The Effect of Red Flags, Task Specific Knowledge, Brainstorming, and Data Analytics on Auditors' Ability to Detect Fraud
DOI:
https://doi.org/10.5281/Keywords:
Detect Fraud, Red Flags, BrainstormingAbstract
The purpose of this study is to determine the effect of red flags, task- specific knowledge, brainstorming, and data analytics on auditors' ability to detect fraud (a study of the Riau Provincial Inspectorate). The quantitative research is an method that implemented in this study. The Riau Provincial Inspectorate office employs sixty-three auditors that make up the research population. Sixty-three respondents made up the study's sample, which was drawn from the total population via saturated sampling, also known as census sampling. A Likert scale was employed as the measuring tool in this study, and the basic data came straight from statements (questionnaires) given to respondents. The IBM Statistical Product and Service Solutions (SPSS) version 29 computer program was utilized to do multiple linear regression analysis, which was the method of data analysis used in this study. Based on the results of the determination test, the R Square value was 0.901 or 90.1%, meaning that fraud detection was influenced by the variables of red flags, task specific knowledge, brainstorming, and data analytics. Other factors that were not investigated in this study had an impact on the remaining 9.9%. The study's findings suggest that auditors' capacity to identify fraud is significantly impacted by red flags, task specific knowledge, and data analytics. In the meantime, auditors' capacity to identify fraud is not significantly impacted by brainstorming.
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