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Audit Analytics in the Financial Industry. 金融業界における監査分析
・ISBN 978-1-78743-086-0 hard US$ 127.99
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お気に入り
★★★
| 著者・編者 | Dai, Jun / Vasarhelyi, M. A. / Medinets, A. F. (eds.), |
|---|---|
| シリーズ | Rutgers Studies in Accounting Analytics |
| 出版社 | (Emerald, UK) |
| 出版年月 | 2019 |
| ページ数 | 387 pp. |
| 言語 | ENG |
| ニュース番号 | ＜653-877 653-L528＞ |
解説
In Audit Analytics in the Financial Industry, editors Jun Dai, Miklos A. Vasarhelyi and Ann F. Medinets bring together a cast of expert contributors to explore ways to integrate Audit Analytics techniques into existing audit programs for the financial industry.
Separated into six parts, the contributors take a variety of approaches to this exploration. In Part One, the contributors present two articles illustrating the process of applying Audit Analytics to solving audit problems. Part Two contains four studies that use various Audit Analytics techniques to discover fraud risks and potential frauds in the credit card sector. In Part Three, the chapter focus on the insurance sector and show the application of clustering techniques in auditing. Part Four includes two chapters on how to employ Audit Analytics in the transitory system for fraud/anomaly detection. Finally, Parts Five and Six illustrate the use of Audit Analytics to assess risk in the lawsuit and payment processes.
For students, researchers, and professionals in the accounting sector, this is an unmissable read exploring the latest research in Audit Analytics.
Separated into six parts, the contributors take a variety of approaches to this exploration. In Part One, the contributors present two articles illustrating the process of applying Audit Analytics to solving audit problems. Part Two contains four studies that use various Audit Analytics techniques to discover fraud risks and potential frauds in the credit card sector. In Part Three, the chapter focus on the insurance sector and show the application of clustering techniques in auditing. Part Four includes two chapters on how to employ Audit Analytics in the transitory system for fraud/anomaly detection. Finally, Parts Five and Six illustrate the use of Audit Analytics to assess risk in the lawsuit and payment processes.
For students, researchers, and professionals in the accounting sector, this is an unmissable read exploring the latest research in Audit Analytics.