A Study on Measuring Contagion Risks in Financial Conglomerates and Financial Supervision Costs: Focusing on Simulation Analysis

Abstract

Against the backdrop of the diminishing effectiveness of traditional regulations separating banking and commerce due to the expanding entry of BigTech firms into financial services, this study provides a simulation analysis quantitatively measuring the contagion risk of financial conglomerates based on graph theory. By combining the stand-alone risk vector of individual institutions with a weighted interconnectedness matrix among affiliates, we define risk-weighted centrality (criticality) and employ Euler's Theorem to decompose total systemic risk into the absolute risk contributions of individual institutions. Furthermore, we demonstrate the feasibility of a flexible macroprudential framework that differentially allocates financial supervision costs in proportion to individual risk contributions and adjusts the total regulatory budget in response to reductions in overall market risk. Simulation results from a financial network comprising 19 financial institutions and 1 BigTech firm indicate that targeted regulations restricting intra-group transactions and information sharing for core risk hubs not only significantly reduce total systemic risk, but also provide regulated entities with incentives for voluntary risk reduction.