Literature review: Whistleblowing system activist simultancy, big data analytics on fraud prevention
List of Authors
  • Enggar Diah , Iwan Putra

Keyword
  • Simultaneous, Whistleblowing System, Big Data Analytics, Prevention Fraud

Abstract
  • The issue of fraudulent practices in Indonesia has become one of the main problems of this nation because of the increasing prevalence of violations. This informs that fraud has really become an acute and systemic problem that is very dangerous and detrimental to the State and society, especially in small and developing countries such as Indonesia. (Dimant, E., & Tosato, G., 2018). The development of the turbulence of human activity gives rise to criminal behavior such as fraudulent acts, one of which is in the form of financial crimes that are undergoing transformation (Rezaee, 2018; Indriani & Terzaghi, 2017; Septriyani & Handayani, 2018; Rusmana & Tanjung, 2019).Several reports from various institutions and world organizations provide an overview of the shifts that have occurred during the pandemic(Huang, Y., 2018). This action is due to the fact that each actor is required to submit accurate and relevant financial information. The purpose of this study is to explore early detection and fraud prevention methods in a conceptual framework that combines elements of a whistleblowing system and big data analytics. In conclusion, there is a gap in the concept of a whistleblowing system and big data analytics in current practice to prevent it, as well as the auditor's perspective in making a proactive anti-fraud model. To explore this, it is necessary to synthesize information through a literature review from various information obtained in terms of generalizing information related to the problems that are the center topic in this study.

Reference
  • 1. Alleyne, P. (2016). The influence of organizational commitment and corporate ethical values on non-public accountants' whistle-blowing intentions in Barbados. Journal of Applied Accounting Research, 17(2), 190–210.https://doi.org/10.1108/JAAR-12-2013-0118

    2. Ariastiani, NKD, Yuniarta, GA, & Kurniawan, P. S, (2018). Influence of Human Resource Competence, Internal Control System, Proactive Fraud Audit, and Whistleblowing System on Fraud Prevention in BOS Fund Management in Klungkung Regency, JIMAT (Accounting Student Scientific Journal), 8(2), 13–69.https://ejournal.undiksha.ac.id/index.php/S1ak/article/view/13291

    3. Chen, T., Wu, D., Chen, H., Ning, Q. (2020). Clinical characteristics of 113 deceased patients with coronavirus disease 2019: Retrospective study. The BMJ, 368.https://doi.org/10.1136/bmj.m1091

    4. Clarke, R. (1994). The digital persona and its application to data surveillance. Information Society,The Information Society: An International Journal, 10:2, 77-92 https://doi.org/10.1080/01972243.1994.9960160

    5. Cressey, D. (1953). Other people's money, in: “Detecting and Predicting Financial Statement Fraud: The Effectiveness of The Fraud Triangle and SAS No. 99,

    6. DeFond, ML, Li, S, Li, Y, & Hung, M., (2015). Does mandatory IFRS adoption affect crash risk? Accounting Review, 90(1), 265–299.https://doi.org/10.2308/accr-50859

    7. Dimant, E., & Tosato, G. (2018). Causes and Effects of Corruption: What Has Past Decade'S Empirical Research Taught Us? a Surveys. Journal of Economic Surveys, 32(2), 335–356.https://doi.org/10.1111/joes.12198

    8. Fritz Heider, (1958). The Psychology of Interpersonal Relations. New York: Wiley

    9. Gottfredson, MR & Hirschi, T. (1990). A General Theory of A Crime. Stanford: Stanford University Press.

    10. Huang, F., Liu, Y., & Vasarhelyi, MA (2018). The impact of nontimely 10-Q fi lings and audit firm size on audit fees. Managerial Auditing Journal, 33(5), 503–516.https://doi.org/10.1108/MAJ-10-2017-1673

    11. Janvrin, DJ, & Weidenmier Watson, M, (2017). Big Data”: A new twist to accounting, Journal of Accounting Education, 38, 3–8.https://doi.org/10.1016/j.jaccedu.2016.12.009

    12. Johansson, E., & Carey, P, (2020). Detecting Fraud: The Role of the Anonymous Reporting Channel, International Journal of Innovation, Creativity and Change, 12(3), 77–88.

    13. Khan, M., Khan, H., Khan, S., & Nawaz, M. (2020). Epidemiological and clinical characteristics of coronavirus disease (COVID-19) cases at a screening clinic during the early outbreak period: a single-centre study. Journal of Medical Microbiology, 69(8), 1114–1123.https://doi.org/10.1099/jmm.0.001231

    14. Kurniawan Saputra, KA, Subroto, B., Rahman, AF, & Saraswati, E., (2020). Issues of morality and whistleblowing in short prevention accounting, International Journal of Innovation, Creativity and Change, 12(3), 77–88.

    15. Liu, J., Gu, X., & Shang, C., (2020). Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data, Complexity, 2020.https://doi.org/10.1155/2020/6685888

    16. Lee, G., & Fargher, N, (2013). Companies' Use of Whistle-Blowing to Detect Fraud: An Examination of Corporate Whistle-Blowing Policies, Journal of Business Ethics, 114(2), 283–295.https://doi.org/10.1007/s10551-012-1348-9

    17. Matthew Herland, Taghi M. Khoshgoftaar and Richard A. Bauder, (2018). Big Data fraud detection using multiple medicare data sources, Journal Big Data (2018) 5:29

    18. Mersa, NA, Sailawati, & Malini, NE L, (2021). Effect of Whistleblowing System Internal Control System Organizational Culture and Organizational Justice on Fraud Prevention, Journal of Financial and Business Accounting, 14(1), 85–92.

    19. Mursalim, M., Su, M., Ahmad, H., & Hajering, H., (2021). Point of View Research Accounting and Auditing Whistleblowing's effectiveness in preventing fraud through forensic audit and investigative audit, Point of View Research Accounting and Auditing, 2(1), 81–91.https://journal.accountingpointofview.id/index.php/povraa

    20. Personal, M., & Archive, R. (2017). Causes And Consequences Of Underground, MPRA Paper No. 36438, Posted 06 Feb 2012 16:22 Utc

    21. Poppy Indriani and M. Titan Terzaghi, (2017). Fraund Diamond in Detecting Fraudulent Financial Statements, I- Finance : a Research Journal on Islamic Finance Vol. 3. No. 2. December 2017,https://doi.org/10.19109/ifinance.v3i2.1690

    22. Pramudyastuti, OL, Rani, U., Nugraheni, AP, & Susilo, GF A, (2021). Effect of Whistleblowing System Implementation on Fraud with Independence as Moderator, Scientific Journal of Accounting, 6(1), 115.https://doi.org/10.23887/jia.v6i1.32335

    23. Randolph, JJ (2009). A guide to writing the dissertation literature review. peer-reviewed electronic journal, 14(13). Retrieved April 15, 2019 fromhttp://doi.org/10.1306/ D426958A-2B26-11D7-8648000102C1865D

    24. Rezaee, Zabihollah and Jim Wang. (2018). Relevance of big data to forensic accounting practice and education. Managerial Auditing Journal. 268-288.https://doi.org/10.1108/MAJ-08-2017-1633

    25. Roger Clarke, (2016). Big data, big risks, Info Systems J (2016) 26, 77–90doi: 10.1111/isj.12088

    26. Romadaniati, Taufik, T., & Nazir, A, (2020). The effect of village apparatus competence, internal control system, and whistleblowing system on fraud prevention in village government with individual morality as a moderating variable, Bilancia: Scientific Journal of Accounting, 4(3), 227–237.

    27. Rusmana, O and H. Tanjung, (2019). Identification of Fraud Financial Statements with Pentagon Fraud Empirical Study of BUMN Listed on the Indonesia Stock Exchange. Journal of Economics, Business and Accounting (JEBA). Vol. 21. No. 4.

    28. Saputra, KAK, & Sanjaya, IKP W, (2019). Whistleblowing and Tri Hita Karana to Prevent Village Fund Fraud in Bali, International Journal of Religious and Cultural Studies, 1(2), 68–73.https://doi.org/10.34199/ijracs.2019.10.03

    29. Septriani and Desi Handayani, (2018). Detecting Financial Statement Fraud with Pentagon Fraud Analysis, Journal of Accounting, Finance and Business Vol. 11, No. 1, May 2018, 11-23

    30. Shonhadji, N., & Maulidi, A., (2021). The roles of whistleblowing system and fraud awareness as financial statement fraud deterrent, International Journal of Ethics and Systems, 37(3), 370–389.https://doi.org/10.1108/IJOES-09-2020-0140

    31. Sohn, DW (2016). Residential crimes and neighborhood built environment: Assessing the effectiveness of crime prevention through environmental design (CPTED). Cities, 52, 86–93.https://doi.org/10.1016/j.cities.2015.11.023

    32. Tang, J., & Karim, KE (2019). Financial Fraud Detection and Big Data Analytics – Implications on Auditors' Use of Fraud Brainstorming Session. Managerial Auditing Journal, 34(3), 324–337.https://doi.org/10.1108/MAJ-01-2018-1767

    33. Triantoro, HD, Utami, I., & Joseph, C, (2020). Whistleblowing system, Machiavellian personality, fraud intention: An experimental study, Journal of Financial Crime, 27(1), 202–216.https://doi.org/10.1108/JFC-01-2019-0003

    34. Vikash Sharma, (2016). Importance of Big Data in financial fraud detection, Int. J. Automation and Logistics, Vol. 2, No. 4, 2016,DOI: 10.1504/IJAL.2016.080339

    35. Waheduzzaman, W. (2019). Challenges in transitioning from new public management to new public governance in a developing country context. International Journal of Public Sector Management, 32(7), 689–705.https://doi.org/10.1108/IJPSM-02-2019-0057

    36. Wolfe, DT, & Hermanson, DR (2004). The Fraud Diamond : Considering the Four Elements of Fraud: Certified Public Accountant. The CPA Journal, 74(12), 38–42.

    37. Yulian Maulida, W., & Indah Bayunitri, B, (2021). the influence of whistleblowing system toward fraud prevention, International Journal of Financial, Accounting, and Management, 2(4), 275–294.https://doi.org/10.35912/ijfam.v2i4.177

    38. Zeng, F., Huang, Y., Guo, Y., Yin, M., Chen, X., Xiao, L., & Deng, G. (2020). Association of inflammatory markers with the severity of COVID-19: A meta-analysis. International Journal of Infectious Diseases, 96, 467–474.https://doi.org/10.1016/j.ijid.2020.05.055