DESIGNING CONTINUOUS AUDIT ANALYTICS AND FRAUD PREVENTION SYSTEMS USING EMERGING TECHNOLOGIES by YUNSEN WANG A Dissertation submitted to the Graduate School-Newark Rutgers, The State University of New Jersey In partial fulfillment of requirements for the degree of Doctor of Philosophy Graduate Program in Management written under the direction of Dr. Alexander Kogan and approved by _____________________________ ____________________________ ____________________________ ____________________________ Newark, New Jersey May, 2018 ©[2018] Yunsen Wang ALL RIGHTS RESERVED ABSTRACT OF THE DISSERTATION Designing Continuous Audit Analytics and Fraud Prevention Systems Using Emerging Technologies By YUNSEN WANG Dissertation Director: Dr. Alexander Kogan This dissertation consists of three essays that design and evaluate the continuous audit analytics and fraud prevention systems using three emerging technologies (i.e., the blockchain, in-memory cloud computing, and deep learning). The first essay designs a framework of Blockchain-based Transaction Processing System using the homomorphic encryption and zero-knowledge proof mechanisms. Furthermore, this study develops a prototype of the designed system to demonstrate its applications in real-time accounting, continuous monitoring, and fraud prevention. Although the simulation tests show the Blockchain-based Transaction Processing System consumes more computational overhead than the conventional database-based ERP system, the blockchain should be considered as a promising technology for future accounting and auditing practice. The second essay introduces the database architecture that manages data in main physical memory and columnar format. This essay proposes a conceptual framework for applying the in-memory columnar database system to support high-speed continuous audit analytics. Moreover, this study develops a prototype and conducts the simulation tests to ii evaluate the proposed framework. The test results show the high efficiency and effectiveness of the in-memory columnar database relative to the conventional ERP system regarding the computational time and the storage volume. Furthermore, the deployment of the in-memory columnar database to the cloud shows great promise of applying the in- memory columnar database for continuous audit analytics. The third essay designs a continuous fraud detection system based on modified deep learning technology. Specifically, this essay builds an accounting layer on top of the deep learning architecture to process financial data for predicting the fraudulent financial statements. A prototype is developed to evaluate the prediction accuracy of the proposed design. The test results show the deep learning-based continuous fraud detection system provides high prediction accuracy relative to the existing studies of financial statement fraud detection. iii ACKNOWLEDGMENTS I would like to express my deepest appreciation to my advisor, Dr. Alexander Kogan, who has provided strong encouragement, valuable guidance, and full trust all along my doctoral journey. You will always be the mentor that leads me to become a serious researcher and a finer person. I would also like to express my sincere gratitude to Dr. Miklos A. Vasarhelyi, who has given me continuous support, warm caring, and insightful advice. Your academic spirit will always inspire me to become a better scholar. I am very grateful to Dr. Hussein Issa. Your constructive feedback and suggestions have perfected my research work over the years. I would also like to express my sincere gratitude to Dr. Graham Gal, your insightful comments and valuable support have always been beneficial to my dissertation and helped improve it in many aspects. Also, I would like to give special thanks to Dr. Dan Palmon for your continuous support and helpful suggestions that have motivated me in becoming a better accounting educator. I am indebted to my dear parents, Zhiguo Wang and Maobin Zhu, and my lovely wife, Tiffany Chiu. Your unconditional love, whole-hearted support, and continuous faith in me have enabled me to discover my potential, achieve my goals, and fulfill my dream. From the bottom of my heart, thank you all for making my achievement possible. I owe thanks to my dearest colleagues and friends, especially to Victoria Chiu, Feiqi Huang, He Li, Yue Liu, Jun Dai, Pei Li, Qi Liu, Ting Sun, Yan Li, Zhaokai Yan, Abdulrahman Alrefai, and Paul Byrnes, your warm friendship and academic support will always be cherished. iv This dissertation would not have been possible without the help and support of my dissertation advisor, my committee members, my friends, and my family. Thank you all for standing by me throughout this journey! v TABLE OF CONTENTS DESIGNING CONTINUOUS AUDIT AND FRAUD PREVENTION SYSTEMS USING EMERGING TECHNOLOGIES ABSTRACT OF THE DISSERTATION ................................................................................................... II ACKNOWLEDGEMENTS ........................................................................................................................ IV TABLE OF CONTENTS ............................................................................................................................ VI LIST OF TABLES ....................................................................................................................................... IX LIST OF FIGURES ...................................................................................................................................... X CHAPTER 1: INTRODUCTION ............................................................................................................ - 1 - CHAPTER 2: LITERATURE REVIEW ............................................................................................... - 7 - 1.1 CONTINUOUS AUDITING .............................................................................................................. - 7 - 1.2 FINANCIAL STATEMENTS FRAUD DETECTION ............................................................................. - 9 - 1.3 EMERGING TECHNOLOGIES ....................................................................................................... - 11 - 1.3.1 Blockchain ........................................................................................................................... - 11 - 1.3.2 Cloud-based In-memory Columnar Computing .................................................................. - 12 - 1.3.3 Deep learning ...................................................................................................................... - 13 - CHAPTER 3: DESIGNING CONFIDENTIALITY-PRESERVING BLOCKCHAIN-BASED TRANSACTION PROCESSING SYSTEMS ...................................................................................... - 16 - 3.1 INTRODUCTION ......................................................................................................................... - 16 - 3.2 MOTIVATION AND LITERATURE REVIEW .................................................................................. - 19 - 3.2.1 The Dilemma: Transparency and Confidentiality .............................................................. - 19 - 3.2.2 Bitcoin and Smart Contracts ............................................................................................... - 20 - 3.2.3 Colored Coins, Sidechains and Private Blockchain ........................................................... - 22 - 3.2.4 Homomorphic Public Key Encryption ................................................................................ - 24 - 3.2.5 Zero-Knowledge Proofs ...................................................................................................... - 25 - 3.2.6 Continuous Monitoring and Real-Time Accounting ........................................................... - 26 - 3.3 BLOCKCHAIN FOR ACCOUNTING: A PRIVACY-PRESERVING DESIGN ........................................ - 27 - 3.3.1 Colored Coins and Assets Tokenization ............................................................................. - 27 - 3.3.2 Real-Time Accounting and Continuous Reporting ............................................................. - 30 - 3.3.3 Blockchain Neutrality ......................................................................................................... - 36 - 3.3.4 Continuous Monitoring, Fraud Prevention and Auditor’s Role ......................................... - 37 - 3.3.5 Internal Control and Permissions Management ................................................................. - 40 - 3.3.6 Blockchain Privacy and Homomorphic Public Key Encryption ......................................... - 42 - vi 3.3.7 Blockchain Privacy and Zero-knowledge Proofs ............................................................... - 45 - 3.4 PROTOTYPING AND EVALUATION ............................................................................................. - 48 - 3.4.1 Basic Infrastructure ............................................................................................................ - 48 - 3.4.2 The Prototype of Blockchain-based Transaction Processing System ................................. - 53 - 3.4.3 Simulation of Permissions Management ............................................................................. - 54 - 3.4.4 Simulation of Automatic Confirmation ............................................................................... - 56 - 3.4.5 Computational Overhead: Blockchain vs. Database .........................................................