The detection of outliers and change points from time series has become research focus in the area of time series data mining since it can be used for fraud detection, rare event discovery, event/trend change detectio...The detection of outliers and change points from time series has become research focus in the area of time series data mining since it can be used for fraud detection, rare event discovery, event/trend change detection, etc. In most previous works, outlier detection and change point detection have not been related explicitly and the change point detections did not consider the influence of outliers, in this work, a unified detection framework was presented to deal with both of them. The framework is based on ALARCON-AQUINO and BARRIA's change points detection method and adopts two-stage detection to divide the outliers and change points. The advantages of it lie in that: firstly, unified structure for change detection and outlier detection further reduces the computational complexity and make the detective procedure simple; Secondly, the detection strategy of outlier detection before change point detection avoids the influence of outliers to the change point detection, and thus improves the accuracy of the change point detection. The simulation experiments of the proposed method for both model data and actual application data have been made and gotten 100% detection accuracy. The comparisons between traditional detection method and the proposed method further demonstrate that the unified detection structure is more accurate when the time series are contaminated by outliers.展开更多
Forensic accounting gained importance due to increasing number of financial frauds and scams. This new area in accounting encompasses accounting, auditing, and investigative skills, thus emerged to detect frauds. They...Forensic accounting gained importance due to increasing number of financial frauds and scams. This new area in accounting encompasses accounting, auditing, and investigative skills, thus emerged to detect frauds. They involve themselves in different areas like employee-related frauds, settlement and arbitrations, etc.. A forensic accountant has a financial sixth sense. Despite the fact that forensic accounting can bridge the gap between conventional accounting and auditing, this profession has not been able to gain the needed momentum due to some hassles. This paper tries to shed light on the theoretical concept, nature, practice, need, role of forensic accounting in preventing fraud, and the practical difficulties faced by forensic accountants. The study is based on information collected from interviewing practicing forensic accounting in India during 2011-12. The paper was able to assess the importance and rising scope of forensic accounting as a job. It also understood the practical difficulties they faced like lack of organized databases in Indian scenario which makes it difficult to access all needed information. Expectation level of the clients is very high and at times even unreasonable. This paper fulfills an identified need to study the important rising field of forensic accounting in India.展开更多
基金Project(2011AA040603) supported by the National High Technology Ressarch & Development Program of ChinaProject(201202226) supported by the Natural Science Foundation of Liaoning Province, China
文摘The detection of outliers and change points from time series has become research focus in the area of time series data mining since it can be used for fraud detection, rare event discovery, event/trend change detection, etc. In most previous works, outlier detection and change point detection have not been related explicitly and the change point detections did not consider the influence of outliers, in this work, a unified detection framework was presented to deal with both of them. The framework is based on ALARCON-AQUINO and BARRIA's change points detection method and adopts two-stage detection to divide the outliers and change points. The advantages of it lie in that: firstly, unified structure for change detection and outlier detection further reduces the computational complexity and make the detective procedure simple; Secondly, the detection strategy of outlier detection before change point detection avoids the influence of outliers to the change point detection, and thus improves the accuracy of the change point detection. The simulation experiments of the proposed method for both model data and actual application data have been made and gotten 100% detection accuracy. The comparisons between traditional detection method and the proposed method further demonstrate that the unified detection structure is more accurate when the time series are contaminated by outliers.
文摘Forensic accounting gained importance due to increasing number of financial frauds and scams. This new area in accounting encompasses accounting, auditing, and investigative skills, thus emerged to detect frauds. They involve themselves in different areas like employee-related frauds, settlement and arbitrations, etc.. A forensic accountant has a financial sixth sense. Despite the fact that forensic accounting can bridge the gap between conventional accounting and auditing, this profession has not been able to gain the needed momentum due to some hassles. This paper tries to shed light on the theoretical concept, nature, practice, need, role of forensic accounting in preventing fraud, and the practical difficulties faced by forensic accountants. The study is based on information collected from interviewing practicing forensic accounting in India during 2011-12. The paper was able to assess the importance and rising scope of forensic accounting as a job. It also understood the practical difficulties they faced like lack of organized databases in Indian scenario which makes it difficult to access all needed information. Expectation level of the clients is very high and at times even unreasonable. This paper fulfills an identified need to study the important rising field of forensic accounting in India.
