Ann F. Medinets – författare

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.

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.

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.

Unlike traditional financial data that originates from firms' internal information systems, exogenous data is generated outside business organizations, including a broad spectrum of sources that include social media posts, website cookies, Google search index, GPS traffic data, and satellite images. Exogenous data is distinguished from periodic and structured financial data by its timeliness, enormous variety, massive volume, tremendous velocity, and reduced likelihood of management manipulation.However, the present financial reporting framework and accounting and auditing textbooks do not typically discuss the proper use of exogenous data in practice. In response to the gap between industry demand and academia, Exogenous Data in Accounting and Auditing in the Rutgers Series in Accounting Information Systems seeks to provide practice-oriented guidance on which types of exogenous data sources might be used under varying audit contingencies; how to integrate exogenous data into the business reporting cycle to give stakeholders more value-relevant and timely information; and how exogenous data could contribute to the measurement and assurance of various ESG-related issues.With contributions from leaders in the field, this timely work outlines how emerging exogenous data sources can be used in both the accounting and auditing fields. It will be of interest to academics, researchers, business students, and accounting professionals.

Unlike traditional financial data that originates from firms’ internal information systems, exogenous data is generated outside business organizations, including a broad spectrum of sources that include social media posts, website cookies, Google search index, GPS traffic data, and satellite images. Exogenous data is distinguished from periodic and structured financial data by its timeliness, enormous variety, massive volume, tremendous velocity, and reduced likelihood of management manipulation.However, the present financial reporting framework and accounting and auditing textbooks do not typically discuss the proper use of exogenous data in practice. In response to the gap between industry demand and academia, Exogenous Data in Accounting and Auditing in the Rutgers Series in Accounting Information Systems seeks to provide practice-oriented guidance on which types of exogenous data sources might be used under varying audit contingencies; how to integrate exogenous data into the business reporting cycle to give stakeholders more value-relevant and timely information; and how exogenous data could contribute to the measurement and assurance of various ESG-related issues.With contributions from leaders in the field, this timely work outlines how emerging exogenous data sources can be used in both the accounting and auditing fields. It will be of interest to academics, researchers, business students, and accounting professionals.