Rutgers studies in accounting analytics : audit analytics in the financial industry

Author

Additional Author(s)

• Dai, Jun
• Vasarhelyi, Miklos A.
• Medinets, Ann F.

Publisher

Bingley, UK: Emerald Group Publishing Limited, 2019

Language

English

ISBN

9781787430853

Series

Rutgers studies in accounting analytics

Subject(s)

• FINANCIAL SERVICES INDUSTRY--AUDITING
• ACCOUNTING
• BUSINESS & ECONOMICS--ACCOUNTING--GENERAL

Notes

• Emerald Business Management and Economics Ebooks 2019

. .

Abstract

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.

Physical Dimension

Number of Page(s)

online resource (x, 235 p.)

Dimension

-

Other Desc.

-

Summary / Review / Table of Content

Prelims
Part I: Audit Analytics Procedures
Chapter 1: An Application of Exploratory Data Analysis in Auditing – Credit Card Retention Case
Chapter 2: Audit Analytics: A Field Study of Credit Card After-sale Service Problem Detection at a Major Bank
Part II: Analytics in Credit Card Audits
Chapter 3: Automated Clustering: From Concept to Reality
Chapter 4: A Multi-faceted Outlier Detection Scheme for Use in Clustering
Chapter 5: Are Customers Offered Appropriate Discounts? An Exploratory Study of Using Clustering Techniques in Internal Auditing
Chapter 6: Predicting Credit Card Delinquency: An Application of the Decision Tree Technique
Part III: Analytics in Insurance Audits
Chapter 7: Cluster Analysis for Anomaly Detection in Accounting
Chapter 8: Multi-dimensional Approaches to Anomaly Detection: A Study of Insurance Claims
Part IV: Audit Analytics in Transitory Systems
Chapter 9: Development of an Anomaly Detection Model for a Bank’s Transitory Account System
Chapter 10: Development of an Anomaly Detection Model for an Insurance Company’s Wire Transfer System
Part V: Audit Analytics for Lawsuit Risk Detection
Chapter 11: A Legal Risk Prediction Model for Credit Cards
Part VI: Audit Analytics in the Payment Process
Chapter 12: Analyzing Payment Data and Its Process: A Bank Case

Exemplar(s)

#	Accession No.	Call Number	Location	Status
1.	00370/20	332 Rut	Online !	Available