데이터마이닝 기반의 정부보조금 부정수급 모니터링 기법에 관한 연구 - 직업능력개발 원격훈련 부정행위 모니터링 사례 중심으로 -

The advent of the fourth industrial revolution is bringing about innovation in various fields. In particular, big data analytics has emerged as a core innovative technology and has become an advanced audit techniques in audit and monitoring techniques. The audit and monitoring through big data-driven data mining techniques also increases the likelihood of cost savings and preventive system deployment. However, due to the lack of cases, methodologies and expertise at the audit site, the techniques are not sufficiently used. This study synthesized previous studies of data mining procedures and methods and analyzed the operating cases of the monitoring of e-learning fraud in TVET(Technical and Vocational Education and Training) conducted by government funding. In this study, the data mining procedures were divided into 5 stages such as ① problem definition → ② data processing → ③ modeling and evaluation → ④ application → ⑤ verification and feedback, and each stage for the monitoring process of e-learning fraud was analyzed. Based on this case study, the potential and implications of applying the general procedures of data mining to the audit and monitoring areas were presented.