Methodology for assessing the risk associated with information and knowledge loss management
Abstract
In practice, there is a massive time lag between data loss and its cause identification. The existing techniques perform it comprehensively, but they consume too much time, so there is a need for fast and reliable methods. The article’s purpose is to develop a rapid methodology to assess the risk of information and knowledge loss management. It provides the implementation of eight steps and combines a risk mapping method modified by assessments based on risk factors and incidents as elements from set theory and using formalization via binary estimates. The methodology includes five significant events caused by the company staff, technical problems, software, cybercriminals, viral attacks, and 66 factors influencing company incidents. As a result, a risk map of 9 groups was built for a Ukrainian enterprise. Only two groups with the minimum number of incidents and low losses are represented by all five incidents. The defined overall level of each risk group ranges from 0.14 to 0.26, which indicates a low probability of all happenings in the group. In general, the resulting map shows the existence of specific security problems of the company under investigation. The proposed assessment allows us to interpret the level of risk in the company quickly, identify weaknesses in the information security system, and predict future losses.
Keyword : risk, information loss, knowledge loss management, factor and incident, binary estimate, risks map
How to Cite
Yarovenko, H., Bilan, Y., Lyeonov, S., & Mentel, G. (2021). Methodology for assessing the risk associated with information and knowledge loss management. Journal of Business Economics and Management, 22(2), 369-387. https://doi.org/10.3846/jbem.2021.13925
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Kendiukhov, I., & Tvaronavičienė, M. (2017). Managing innovations in sustainable economic growth. Marketing and Management of Innovations, 3, 33–42. https://doi.org/10.21272/mmi.2017.3-03
Kollár, C., & Zsuzsanna Bellász, Z. V. (2017). Terrorism and the information security of media content with special regard to ISIS, the Balkans and Russia. SocioEconomic Challenges, 1(1), 13–19. https://doi.org/10.21272/sec.2017.1-02
Kolomiiets, U., & Petrushenko, Yu. (2017). The human capital theory. Encouragement and criticism. SocioEconomic Challenges, 1(1), 77–80. https://doi.org/10.21272/sec.2017.1-09
Kostyuchenko, N., Starinskyi, М., Tiutiunyk, I., & Kobushko, I. (2018). Methodical approach to the assessment of risks connected with the legalization of the proceeds of crime. Montenegrin Journal of Economics, 14(4), 023–043. https://doi.org/10.14254/1800-5845/2018.14-4.2
Kuzmenko, O., & Bozhenko, A. (2014). Optimization of the risk level of net retention in the insurance market. Economic Annals-XXI, 11–12, 76–79. http://soskin.info/userfiles/file/2014/11-12_2014/Kuzmenko_Bozhenko.pdf
Lazaroiu, G., Kovachova, M., Kliesticova, J., Kubla, P., Valaskova, K., & Dengov, V. (2018). Data governance and automated individual decision-making in the digital privacy General Data Protection Regulation. Administratie si Management Public, 31, 132–141.
Lee, D. (2020). Cathay Pacific fined £500,000 by British privacy watchdog for 2018 data breach but avoids potentially heftier penalty under European regulation. https://www.scmp.com/news/hong-kong/transport/article/3065071/cathay-pacific-fined-ps500000-british-privacy-watchdog
Leonov, S. V., Vasilyeva, T. A., & Shvindina, H. O. (2017). Methodological approach to design the organizational development evaluation system. Scientific Bulletin of Polissia, 3(11), 2, 51–56. https://doi.org/10.25140/2410-9576-2017-2-3(11)-51-56
Leonov, S. V., Vasylieva, T. A., & Tsyganyuk, D. L. (2012). Formalization of functional limitations in functioning of co-investment funds basing on comparative analysis of financial markets within FM CEEC. Actual Problems of Economics, 134(8), 75–85. https://www.researchgate.net/publication/294565974_Formalization_of_functional_limitations_in_functioning_of_co-investment_funds_basing_on_comparative_analysis_of_financial_markets_within_FM_CEEC
Leonov, S., Yarovenko, H., Boiko, A., & Dotsenko, T. (2019, May). Information system for monitoring banking transactions related to money laundering. In Proceedings of the 8th International Conference on Monitoring, Modeling and Management of Emergent Economy: Experimental Economics and Machine Learning for Prediction of Emergent Economy Dynamics, M3E2-EEMLPEED 2019 (pp. 297–307). Odessa, Ukraine. http://ceur-ws.org/Vol-2422/paper24.pdf
Levchenko, V., Boyko, A., Bozhenko, V., & Mynenko, S. (2019). Money laundering risk in developing and transitive economies: Analysis of cyclic component of time series. Business: Theory and Practice, 20, 492–508. https://doi.org/10.3846/btp.2019.46
Limba, T., Stankevičius, A., & Andrulevičius, A. (2019). Towards sustainable cryptocurrency: Risk mitigations from a perspective of national security. Journal of Security and Sustainability, 9(2), 375–389. https://doi.org/10.9770/jssi.2019.9.2(2)
Lyeonov, S., Kuzmenko, O., Yarovenko, H., & Dotsenko, T. (2019). The innovative approach to increasing cybersecurity of transactions through counteraction to money laundering. Marketing and Management of Innovations, 3, 308–326. https://doi.org/10.21272/mmi.2019.3-24
Lyulyov, O., & Shvindina, H. (2017). Stabilization pentagon model: Application in the management at macro- and micro-levels. Problems and Perspectives in Management, 15(3), 42–52. https://doi.org/10.21511/ppm.15(3).2017.04
Morsher, Ch., Horsch, A., & Stephan, J. (2017). Credit information sharing and its link to financial inclusion and financial intermediation. Financial Markets, Institutions and Risks, 1(3), 22–33. https://doi.org/10.21272/fmir.1(3).22-33.2017
Mura, L., Marchevska, M., & Dubravska, M. (2018). Slovak retail business across panel regression model. Marketing and Management of Innovations, 4, 203–211. https://doi.org/10.21272/mmi.2018.4-18
Nasr, A. K., Alaei, S., Bakhshi, F., Rasoulyan, F., Tayaran, H., & Farahi, M. (2019). How enterprise risk management (ERM) can affect on short-term and long-term firm performance: Evidence from the Iranian banking system. Entrepreneurship and Sustainability Issues, 7(2), 1387–1403. https://doi.org/10.9770/jesi.2019.7.2(41)
Nocoń, A., & Pyka, I. (2019). Sectoral analysis of the effectiveness of bank risk capital in the Visegrad Group countries. Journal of Business Economics & Management, 20(3), 424–445. https://doi.org/10.3846/jbem.2019.9606
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