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Developing an Intelligent Assistant for the Audit Plan Brainstorming Session Developing an Intelligent Assistant for the Audit Plan Brainstorming Session by Qiao Li A dissertation submitted to the Graduate School - Newark Rutgers, the State University of New Jersey In partial fulfillment of the requirements for the degree of Doctor of Philosophy Graduate Program in Management Written under the direction of Professor Miklos Vasarhelyi and approved by Dr. Miklos A. Vasarhelyi __________________________________________ Dr. Alexander Kogan __________________________________________ Dr. Helen Brown-Liburd __________________________________________ Dr. Donald Warren __________________________________________ Newark, New Jersey January 2019 ©[2019] QIAO LI ALL RIGHTS RESERVED ABSTRACT OF THE DISSERTATION Developing an Intelligent Assistant for the Audit Plan Brainstorming Session By QIAO LI Dissertation Director: Dr. Miklos A. Vasarhelyi During the initial stages of an audit, audit engagement teams are required to conduct brainstorming sessions to evaluate risk factors and discuss the susceptibility of the entity’s financial statements to material misstatement, either as a result of error or fraud (AICPA 2012). At present, the most commonly used decision support tool for audit plan brainstorming is the checklist (Bellovary and Johnstone 2007), which has shown limitations. Large audit firms have been investing in substantive resources to the utilization of Artificial Intelligence (AI) to take advantage of their past audit experience and industry knowledge (Kokina and Davenport 2017). This dissertation suggests that the latest intelligent assistant technology can be applied in the auditing domain to provide risk assessment decision supports to audit engagement teams during audit plan brainstorming discussions. Firstly, an interactive audit cognitive assistant framework is proposed to provide auditors with information retrieval and risk assessment help. The proposed framework provides a new method of knowledge organization for the audit domain, which potentially develops a knowledge base that stores many auditors’ knowledge and experience in audit risk identification and assessment. ii Furthermore, a Natural Language Processing (NLP)-based audit plan knowledge discovery system (APKDS) is proposed. By applying NLP techniques, the proposed system can continuously collect auditors’ professional experience and expertise in audit brainstorming discussions and transfer the discussion into classified knowledge for future use. The output of the proposed system can provide insights into how auditors identify and assess risks during the audit plan and how audit decisions are made. Finally, we propose a prototype for the APKDS framework and illustrate the development of important modules in the system. Experimental brainstorming meeting recordings are used as training and testing datasets in model building and training. We demonstrate that the proposed objectives of the system can be realized and the proposed system can provide effective decision-making support to auditors. In the end, we proposed the potential application of the audit cognitive assistant to other audit phases. iii ACKNOWLEDGEMENTS It is a sentimental moment to write this note of thanks as the finishing touch of my dissertation. This thesis represents the cohesion of painstaking efforts of several years of work, and could not have been accomplished without the love and support from many people. Here I would like to express my greatest appreciation to all the people who provided me tremendous support and help during my Ph.D. study. I would like first to express my deep gratitude to my mentor and adviser, Prof. Miklos A. Vasarhelyi. He brought me to academia and encouraged me to explore on my own. He provides me intellectual guidance, inspiring insights, inexhaustible patience, and extraordinary knowledge, which are necessary to survive and thrive the graduate school and the beyond. When my step faltered, he often told me the quote “if we knew what it was we were doing, it would not be called research, would it?” (by Albert Einstein). I thank him for generously giving me motivation, support, time, understandings, assistance, opportunities, trust, and friendship for all these years. Moreover, I want to thank him for providently positioning and guiding me on the right direction of the pioneer research work of audit data analytics. He helped me to be a better writer, speaker, and scholar. I also sincerely grateful to those who served in my committees: Prof. Alexander Kogan, Prof. Helen Brown-Liburd and Prof. Donald Warren. I deeply appreciate their time and efforts in reviewing my dissertation and attending my dissertation defense. All of them not only provide thought-provoking and constructive suggestions on my research, but also offer tremendous support and help in my academic job-hunting process. I would like to acknowledge my gratitude to Prof. Dan Palmon for his consistent support as department iv chair. Special thanks are due to Prof. Won Gyun No, Prof. Hussein Issa, Prof. Michel Alles, Prof. Kyungha Lee, Prof. Kevin C. Moffitt and Prof. Irfan Bora in the AIS department of Rutgers Business School and for their help with both my job search and research work. I would also like to acknowledge the CARLAB (Continuous Auditing & Reporting Lab) of Rutgers Business School for supplying me with the best equipment and working environment that helped me to accomplish much of this work. It is an honor to be affiliated with such a great research group and a loving family. I also owe a hefty amount of thanks to my friends and colleagues at Rutgers: Dr. Victoria Chiu, Dr. Jun Dai, Dr. Kyunghee Yoon, Xuan Peng, Dr. Tiffany Chiu, Feiqi Huang, Kexing Ding, Yue Liu, Dr. Ting Sun, Dr. Jingyuan Yang, Dr. Meng Qu, Dr. Meng Li et al. for their help, friendship, and valuable suggestions. Finally, my deepest thanks and love to my husband Junming Liu, who gave me infinite joy, love, and support to make this work possible. Especially, I thank him for providing me tremendous professional suggestions and help to my research work. I also thank him for making it very challenging to take care of him in daily life, which helped me to be a stronger woman and have the courage to face other difficulties such as completing the thesis. I owe my deepest gratitude and love to my parents and in-laws for their unwearied devotion and unconditional love. v TABLE OF CONTENTS ABSTRACT OF THE DISSERTATION ...................................................................... II ACKNOWLEDGEMENTS ........................................................................................... IV LIST OF TABLES ........................................................................................................ XII LIST OF FIGURES ..................................................................................................... XIV CHAPTER 1: INTRODUCTION ................................................................................ - 1 - 1.1 BACKGROUND & PRELIMINARIES ............................................................... - 3 - 1.1.1 AUDIT BRAINSTORMING SESSIONS .................................................................... - 3 - 1.1.2 COGNITIVE ASSISTANT ...................................................................................... - 4 - 1.2 RESEARCH MOTIVATION AND RESEARCH CONTRIBUTIONS ............ - 7 - 1.3 OVERVIEW .......................................................................................................... - 10 - CHAPTER 2: DEVELOPING A COGNITIVE ASSISTANT FOR THE AUDIT PLAN BRAINSTORMING SESSION ...................................................................... - 11 - 2.1 INTRODUCTION................................................................................................. - 11 - 2.2 BACKGROUND ON AUDIT BRAINSTORMING SESSIONS ...................... - 14 - 2.2.1 AUDIT BRAINSTORMING SESSIONS ................................................................. - 14 - 2.2.2 ISSUES OF THE CURRENT AUDIT BRAINSTORMING AUDIT TOOL ..................... - 15 - 2.3 FEATURES OF COGNITIVE ASSISTANTS AND THEIR ADVANTAGES IN IMPROVING AUDIT PLANNING .......................................................................... - 17 - vi 2.3.1 FEATURES ........................................................................................................ - 17 - 2.3.2 CHALLENGES ................................................................................................... - 20 - 2.4 METHODOLOGY ............................................................................................... - 20 - 2.5 PROPOSED AUDIT COGNITIVE ASSISTANT FRAMEWORK................. - 22 - 2.5.1 USER INTERFACE ............................................................................................. - 23 - 2.5.2 RECOMMENDER SYSTEM ................................................................................. - 24 - 2.5.3 ARCHITECTURE ............................................................................................... - 25 - 2.5.4 APPLICATIONS ................................................................................................. - 26 - 2.5.5 KNOWLEDGE BASE ........................................................................................... - 27 - 2.5.6 IMPORTANT MODULES IN THE PROPOSED SYSTEM ......................................... - 28 - a. Speech Recognition ........................................................................................... - 29 - b. Language Understanding and Language Generation (Natural Language Processing) ..........................................................................................................
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