Data-Driven Risk Visibility for Construction Lenders
Article Sidebar
Main Article Content
Abstract
This research aims to create a structural base for institutional investors to effectively monitor investment risks associated with residential construction projects in India under RERA regulations. Under prevailing scenarios, institutional financing bodies periodically evaluate the associated risks of construction projects, often with the support of due diligence reports from consulting firms. To effectively address existing challenges, this research aims to develop a consolidation platform to implement recent advancements in global risk-monitoring standards, including Bayesian networks, system dynamics, earned value management, and value-based control systems, within a proposed integrated system comprising five layers. This proposed idea has been supported by a literature review, data analysis, and further validation of the findings using the Tamil Nadu RERA data portal for residential construction projects in Chennai, Tamil Nadu, India. This research is significant for stakeholders in India’s construction finance ecosystem and provides practical validation of the theoretical correctness of risk monitoring.
Downloads
Article Details
Section
How to Cite
References
K. J. Aladayleh and M. J. Aladaileh, “Applying Analytical Hierarchy Process (AHP) to BIM-Based Risk Management for Optimal Performance in Construction Projects,” Buildings, vol. 14, no. 11, p. 3632, Nov. 2024, DOI: https://doi.org/10.3390/buildings14113632.
A. Heitz, C. Martin, and A. Ufier, “Bank Monitoring in Construction Lending,” SSRN Journal, 2022, DOI: https://doi.org/10.2139/ssrn.4197344.
J. Konior, “Monitoring of Construction Projects Feasibility by Bank Investment Supervision Approach,” cea, vol. 7, no. 1, pp. 31–35, Jan. 2019, DOI: https://doi.org/10.13189/cea.2019.070105.
E. Pekel, Z. D. Akschir, B. Meto, S. Akleylek, and E. Kilic, “A Bayesian Network Application in Occupational Health and Safety,” in 2018 3rd International Conference on Computer Science and Engineering (UBMK), Sarajevo: IEEE, Sep. 2018, pp. 239–243. DOI: https://doi.org/10.1109/UBMK.2018.8566568.
A. Siemaszko, B. Grzyl, and A. Kristowski, “Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN),” in 2018 Baltic Geodetic Congress (BGC Geomatics), Olsztyn, Poland: IEEE, Jun. 2018, pp. 191–195. DOI: https://doi.org/10.1109/BGC-Geomatics.2018.00042.
M. Ye, J. Wang, X. Si, S. Zhao, and Q. Huang, “Analysis on Dynamic Evolution of the Cost Risk of Prefabricated Building Based on DBN,” Sustainability, vol. 14, no. 3, p. 1864, Feb. 2022, DOI: https://doi.org/10.3390/su14031864.