Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry

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(13 chapters)

Prelims

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Part I: Audit Analytics Procedures

An Application of Exploratory Data Analysis in Auditing – Credit Card Retention Case*

Pages 3-15

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Citation: Liu, Q. (2019), "An Application of Exploratory Data Analysis in Auditing – Credit Card Retention Case*", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 3-15. https://doi.org/10.1108/978-1-78743-085-320191001

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Audit Analytics: A Field Study of Credit Card After-sale Service Problem Detection at a Major Bank

Pages 17-33

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Citation: Dai, J., Byrnes, P., Liu, Q. and Vasarhelyi, M. (2019), "Audit Analytics: A Field Study of Credit Card After-sale Service Problem Detection at a Major Bank", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 17-33. https://doi.org/10.1108/978-1-78743-085-320191002

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Part II: Analytics in Credit Card Audits

Automated Clustering: From Concept to Reality*

Pages 37-46

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Citation: Byrnes, P. (2019), "Automated Clustering: From Concept to Reality*", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 37-46. https://doi.org/10.1108/978-1-78743-085-320191003

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A Multi-faceted Outlier Detection Scheme for Use in Clustering*

Pages 47-58

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Citation: Byrnes, P. (2019), "A Multi-faceted Outlier Detection Scheme for Use in Clustering*", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 47-58. https://doi.org/10.1108/978-1-78743-085-320191004

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Are Customers Offered Appropriate Discounts? An Exploratory Study of Using Clustering Techniques in Internal Auditing

Pages 59-69

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Citation: Dai, J., Byrnes, P. and Vasarhelyi, M. (2019), "Are Customers Offered Appropriate Discounts? An Exploratory Study of Using Clustering Techniques in Internal Auditing", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 59-69. https://doi.org/10.1108/978-1-78743-085-320191005

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Predicting Credit Card Delinquency: An Application of the Decision Tree Technique

Pages 71-83

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Citation: Sun, T. and Vasarhelyi, M. (2019), "Predicting Credit Card Delinquency: An Application of the Decision Tree Technique", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 71-83. https://doi.org/10.1108/978-1-78743-085-320191006

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Part III: Analytics in Insurance Audits

Cluster Analysis for Anomaly Detection in Accounting*

Pages 87-110

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Citation: Thiprungsri, S. (2019), "Cluster Analysis for Anomaly Detection in Accounting*", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 87-110. https://doi.org/10.1108/978-1-78743-085-320191007

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Multi-dimensional Approaches to Anomaly Detection: A Study of Insurance Claims*

Pages 111-144

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Citation: Moharram, B. (2019), "Multi-dimensional Approaches to Anomaly Detection: A Study of Insurance Claims*", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 111-144. https://doi.org/10.1108/978-1-78743-085-320191008

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Part IV: Audit Analytics in Transitory Systems

Development of an Anomaly Detection Model for a Bank’s Transitory Account System¹

Pages 147-164

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Citation: Kim, Y. (2019), "Development of an Anomaly Detection Model for a Bank’s Transitory Account System¹", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 147-164. https://doi.org/10.1108/978-1-78743-085-320191009

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Development of an Anomaly Detection Model for an Insurance Company’s Wire Transfer System*

Pages 165-200

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Citation: Kim, Y. (2019), "Development of an Anomaly Detection Model for an Insurance Company’s Wire Transfer System*", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 165-200. https://doi.org/10.1108/978-1-78743-085-320191010

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Part V: Audit Analytics for Lawsuit Risk Detection

A Legal Risk Prediction Model for Credit Cards

Pages 203-213

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Citation: Huang, F., Liu, Q. and Vasarhelyi, M. (2019), "A Legal Risk Prediction Model for Credit Cards", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 203-213. https://doi.org/10.1108/978-1-78743-085-320191011

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Part VI: Audit Analytics in the Payment Process

Analyzing Payment Data and Its Process: A Bank Case

Pages 217-235

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Citation: Chandia, K. and Vasarhely, M. (2019), "Analyzing Payment Data and Its Process: A Bank Case", Dai, J., Vasarhelyi, M.A. and Medinets, A.F. (Ed.) Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry, Emerald Publishing Limited, Leeds, pp. 217-235. https://doi.org/10.1108/978-1-78743-085-320191012

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Cover of Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry

DOI

10.1108/9781787430853

Publication date

2019-10-28

Book series

Rutgers Studies in Accounting Analytics

Editors

Series copyright holder

Emerald Publishing Limited

ISBN

978-1-78743-086-0

eISBN

978-1-78743-085-3

Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial Industry

Synopsis

Table of contents

Prelims

Part I: Audit Analytics Procedures

An Application of Exploratory Data Analysis in Auditing – Credit Card Retention Case*

Audit Analytics: A Field Study of Credit Card After-sale Service Problem Detection at a Major Bank

Part II: Analytics in Credit Card Audits

Automated Clustering: From Concept to Reality*

A Multi-faceted Outlier Detection Scheme for Use in Clustering*

Are Customers Offered Appropriate Discounts? An Exploratory Study of Using Clustering Techniques in Internal Auditing

Predicting Credit Card Delinquency: An Application of the Decision Tree Technique

Part III: Analytics in Insurance Audits

Cluster Analysis for Anomaly Detection in Accounting*

Multi-dimensional Approaches to Anomaly Detection: A Study of Insurance Claims*

Part IV: Audit Analytics in Transitory Systems

Development of an Anomaly Detection Model for a Bank’s Transitory Account System¹

Development of an Anomaly Detection Model for an Insurance Company’s Wire Transfer System*

Part V: Audit Analytics for Lawsuit Risk Detection

A Legal Risk Prediction Model for Credit Cards

Part VI: Audit Analytics in the Payment Process

Analyzing Payment Data and Its Process: A Bank Case

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Table of contents

Part I: Audit Analytics Procedures

Part II: Analytics in Credit Card Audits

Part III: Analytics in Insurance Audits

Part IV: Audit Analytics in Transitory Systems

Part V: Audit Analytics for Lawsuit Risk Detection

Part VI: Audit Analytics in the Payment Process

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