A Mixed Approach to Assess Information System Risk, Operational Risk, and Congolese Microfinance Institutions Performance

Authors: Alfred Kamate Siviri, Angelus Mafikiri Tsongo, Jean Robert Kala Kamdjoug

Abstract:

Well organized digitalization and information systems have been selected as relevant measures to mitigate operational risks within organizations. Unfortunately, information system comes with new threats that can cause severe damage and quick organization lockout. This study aims to measure perceived information system risks and their effects on operational risks within the microfinance institution in D.R. Congo. Also, the factors influencing the operational risk are to be identified, and the link between operational risk with other risks and performance is to be assessed. The study proposes a research model drawn on the combination of Resources-Based-View, dynamic capabilities, the agency theory, the Information System Security Model, and social theories of risk. Therefore, we suggest adopting a mixed methods research with the sole aim of increasing the literature that already exists on perceived operational risk assessment and its link with other risk and performance, with a focus on information system risks.

Keywords: information system risk, operational risk, microfinance performance, DR Congo

References:

[1] Ferreira, S. J., E. Redda, and S. H. Dunga, A structural equation model of reputational risk in South Africa. Cogent Economics & Finance, 2019. 7(1): p. 1625739.
[2] Zhong, X. and S. Zhou, Risk analysis method of bank microfinance based on multiple genetic artificial neural networks. Neural Computing and Applications, 2020. 32(10): p. 5367-5377.
[3] Afolabi, T. S., T. M. Obamuyi, and T. Egbetunde, Credit Risk and Financial Performance: Evidence from Microfinance Banks in Nigeria. IOSR Journal of Economics and Finance, 2020. 11(1): p. 8-15.
[4] Coetzee, J., Bank Management in South Africa: A Risk-based Perspective. 2016: Juta.
[5] Kartalia, J., Reputation at risk? Risk management, 2000. 47(7): p. 51.
[6] Cheng, L., et al., Credit risk, operational risk, liquidity risk on profitability. A study on South Africa commercial banks. A PLS-SEM Analysis. Revista Argentina de Clínica Psicológica, 2020. 29(5): p. 5.
[7] Congo, B .C. D., Rapport d'activités de la microfinance 2016. 2016, Banque Centrale du Congo: Kinshasa.
[8] Fadun, O. S. and D. Oye, Impacts of Operational Risk Management on Financial Performance: A Case of Commercial Banks in Nigeria. International Journal of Finance & Banking Studies, 2020. 9(1): p. 22-35.
[9] Masakona, M., The impact of digitisation on risk management in financial institutions. 2019.
[10] Meno, T., An Assessment of Risk Associated with Digitalisation in the South African Construction Industry. 2020: University of Johannesburg (South Africa).
[11] Marc Andries; David Carteau, S. C. and P. G. C. G. C. L. Maguer, Le risque informatique, B.d.F. CPR, Editor. 2018.
[12] Kozlenkova, I. V., S. A. Samaha, and R. W. Palmatier, Resource-based theory in marketing. Journal of the Academy of Marketing Science, 2014. 42(1): p. 1-21.
[13] Wuen, C. H., F. Ibrahim, and K. J. Ringim, The Impact of Human Resource Management Practices on SMEs Performance: An Exploratory Study in Brunei Darussalam. International Journal of Asian Business and Information Management (IJABIM), 2020. 11(2): p. 68-87.
[14] Teece, D. J., G. Pisano, and A. Shuen, Dynamic capabilities and strategic management. Strategic management journal, 1997. 18(7): p. 509-533.
[15] Wang, C. L. and P. K. Ahmed, Dynamic capabilities: A review and research agenda. International journal of management reviews, 2007. 9(1): p. 31-51.
[16] Nelson, R. R., An evolutionary theory of economic change. 2009: Harvard University Press.
[17] Eisenhardt, K. M., Agency theory: An assessment and review. Academy of management review, 1989. 14(1): p. 57-74.
[18] Wilson, R., The theory of syndicates. Econometrica: journal of the Econometric Society, 1968: p. 119-132.
[19] Tate, W. L., et al., An agency theory perspective on the purchase of marketing services. Industrial Marketing Management, 2010. 39(5): p. 806-819.
[20] Abdullah, H. and B. Valentine, Fundamental and ethics theories of corporate governance. Middle Eastern Finance and Economics, 2009. 4(4): p. 88-96.
[21] Murengezi, C., Impacts du crédit dans la promotion des PME: Études de cas sur la ville de Ouagadougou-Burkina Faso. 2008: Presses univ. de Louvain.
[22] Mayer, N., P. Heymans, and R. Matulevicius. Design of a Modelling Language for Information System Security Risk Management. 2007
[23] Danaan, V., Risk management in microfinance: identities, perceptions, behaviours and interests of microfinance stakeholders in Plateau State, Nigeria. 2019.
[24] Brown, P., Risk and Social Theory: the legitimacy of risks and risk as a tool of legitimation. 2014, Taylor & Francis.
[25] Stoel, M. D. and W. A. Muhanna, IT capabilities and firm performance: A contingency analysis of the role of industry and IT capability type. Information & Management, 2009. 46(3): p. 181-189.
[26] Amit, R. and P. J. H. Schoemaker, Strategic assets and organizational rent. Strategic management journal, 1993. 14(1): p. 33-46.
[27] Ravichandran, T., C. Lertwongsatien, and C. Lertwongsatien, Effect of information systems resources and capabilities on firm performance: A resource-based perspective. Journal of management information systems, 2005. 21(4): p. 237-276.
[28] Carmen, R. and P. Laura, Operational Risk & Cybersecurity. Management Strategies Journal, 2016. 32(2): p. 30-33.
[29] Dávila-Aragón, G., H. X. Ramírez-Pérez, and S. Rivas-Aceves, Familiness as determinant of operational risk: a bayesian analysis. 2020.
[30] Basel II, B. C. o. B. S., Working paper on the regulatory treatment of the operational risk”, September, 2001.
[31] Trenca, I. and I. Neag, Considerations Regarding Operational Risk Management in the Context of the Basel II Agreement. Romanian Economic Journal, 2010. 13(36): p. 171-185.
[32] Zindel, M. L., T. Zindel, and M. G. Quirino, Cognitive bias and their implications on the financial market. International Journal of Engineering and Technology, 2014. 14(3): p. 11-17.
[33] Grable, J. E., Financial risk tolerance and additional factors that affect risk taking in everyday money matters. Journal of business and psychology, 2000. 14(4): p. 625-630.
[34] Crespo, Á. H., I. R. Del Bosque, and M. M. G. de los Salmones Sánchez, The influence of perceived risk on Internet shopping behavior: a multidimensional perspective. Journal of Risk Research, 2009. 12(2): p. 259-277.
[35] Sweeney, J. C., G. N. Soutar, and L. W. Johnson, The role of perceived risk in the quality-value relationship: A study in a retail environment. Journal of retailing, 1999. 75(1): p. 77-105.
[36] Featherman, M. S. and P. A. Pavlou, Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 2003. 59(4): p. 451-474.
[37] Kankam, P. K., Approaches in Information Research. New Review of Academic Librarianship, 2020. 26(1): p. 165-183.
[38] Bryman, A., Social research methods. 2016: Oxford university press.
[39] Santos, J. L. G. d., et al., Mixed methods research in latin america: initiatives and opportunities for expansion. Texto & Contexto-Enfermagem, 2020. 29.
[40] Andrew, S. and E. Halcomb, Mixed methods research for nursing and the health sciences. 2009: Wiley Online Library.
[41] Condomines, B. and É. Hennequin, Studying sensitive issues: The contributions of a mixed approach. RIMHE: Revue Interdisciplinaire Management, Homme Entreprise, 2014(5): p. 3-19.