Different scenarios of applying emerging technologies in accounting and auditing: text mining, machine learning, and visualization
Creators: name: Lee, Heejae
Publisher: name: No Publisher Supplied
Year: 2023

description: Digitization of business transactions and the advancement of information technology have changed how accounting professionals execute their job. Although tools and techniques have been available for a long time in the accounting domain, only limited technologies have been used in practice. This dissertation, consisting of three essays, demonstrates different scenarios on how various emerging technologies can be applied to solve existing problems in the accounting and auditing domain.The first essay describes the design and implementation of a prototype multi-label classification method to categorize nonprofit organizations using the textual contents of their mission statement. Multiple machine learning algorithms were applied to evaluate the performance to classify nonprofit organizations. Positive unlabeled learning was implemented to improve the performance of partially labeled data. The result shows that the Support Vector Machine algorithm performed best among the four algorithms examined. The Support Vector Machine classifier identified a larger sample of ‘Housing &amp; Shelter’ organizations than the NTEE classification method. In addition, new classification can change the ‘industry benchmark’ used to evaluate the organization’s financial performance. The new classification method can provide more inclusive benchmarks that may help assess nonprofits for auditors. It can also help donors, grant providers, and researchers to identify similar nonprofit organizations at the operational level.The second essay proposes a Text Visual Analysis (TVA) approach for auditing. Business transaction data includes numeric values of the transactions, the date/time when the transactions are recorded, and textual data such as descriptions. Understanding the textual information of business transactions is also essential since this information captures the nature of transactions qualitatively. Combining text analysis and data visualization can improve the efficiency of audit data analytics for textual data in the organization’s accounting information system. The proposed method was demonstrated using a year-round general ledger and trial balance data set. The data visualization softwares Orange and Tableau were used for the demonstration. The proposed method can be used to understand a client’s business and identify abnormal or unusual transactions from both quantitative and qualitative information.The third essay examines the implementation of continuous monitoring in payroll systems in the government sector. Identifying high risk is essential in continuous auditing implementation since the volume of exceptions flagged by continuous auditing and continuous monitoring system is usually too large to be manually examined. The case study demonstrates that the continuous monitoring system with interactive visualization can help auditors to identify abnormal transactions from the government payroll system. This study can guide how interactive data visualization can be integrated into the continuous monitoring system to improve internal audit procedures.