Recent Advances in Risk Management Using Business Intelligence

Swapnil Raj; Mrinal Paliwal

doi:10.55524/ijirem.2022.9.1.37

Abstract

Over the last several decades, risk supervision has been a hot subject in both academic world and practice. The complexity of the company and the environment in which it works determine operational risk. As the company or the environment becomes more dynamic, i.e., where change is a constant characteristic and a factor to consider into the management of the firm, such complexity grow. The important issue is how companies react to such changes today, and what measures can businesses take to anticipate and prepare for change as the nature of business and the environment becomes more dynamic. The majority of business intelligence (BI) programs or software have been utilized to improve risk supervision, and business intelligence methods have improved risk management solutions. This introductory paper offers an overview of current business intelligence research in risk management.

Keywords

Business Intelligence, Risk Supervision, Operations Research.

References

Risk Management & Business Intelligence [Internet]. [cited 2018 Sep 11]. Available from: http://www.rmbi.ust.hk/web/eng/capstone.php
Fan X. Financial risk early warning constraint method based on weighted logistic regression. Bol Tec Bull. 2017;
Lopez C, Salmeron JL. Dynamic risks modelling in ERP maintenance projects with FCM. Inf Sci (Ny). 2014;
Pham H V., Cooper EW, Cao T, Kamei K. Hybrid Kansei-SOM model using risk management and company assessment for stock trading. Inf Sci (Ny). 2014;
Feng N, Wang HJ, Li M. A security risk analysis model for information systems: Causal relationships of risk factors and vulnerability propagation analysis. Inf Sci (Ny). 2014;
Li Y, Zhang W, Zhang Y, Zhang X, Xiong X. Calibration of the agent-based continuous double auction stock market by scaling analysis. Inf Sci (Ny). 2014;
Krstevska A. Early Warning Systems: Testing in Practice. IUP J Financ Risk Manag. 2012;
Castell MRF, Dacuycuy LB. Exploring the use of exchange market pressure and RMU deviation indicator for early warning system (EWS) in the ASEAN+3 region. DLSU Bus Econ Rev. 2009;
Xie K, Liu J, Peng H, Chen G, Chen Y. Early-warning management of inner logistics risk in SMEs based on label-card system. Prod Plan Control. 2009;
Otim S, Dow K, Grover V, Wong J. The impact of information technology investments on downside risk of the firm: Alternative measurement of the business value of IT. J Manag Inf Syst. 2012;
Silvestri A, De Felice F, Petrillo A. Multi-criteria risk analysis to improve safety in manufacturing systems. Int J Prod Res. 2012;
Nash JF. Equilibrium points in n-person games. Proc Natl Acad Sci. 1950;
Zhao L, Jiang Y. A game theoretic optimization model between project risk set and measure set. Int J Inf Technol Decis Mak. 2009;

Cites this article as

S. R. , M. P. , "Recent Advances in Risk Management Using Business Intelligence", International Journal of Innovative Research in Engineering and Management (IJIREM), Vol-9, Issue-1, Page No-199-202, 2022. Available from: https://doi.org/10.55524/ijirem.2022.9.1.37