Comparative study of banking resolution frameworks and their effectiveness in crisis situations

Posted: Jun 08, 2018

• Prof. Victor Mehta
• Prof. William Johansson
• Dr. Alexander Rossi

Abstract

This research presents a comprehensive comparative analysis of banking resolution frameworks across major financial jurisdictions, employing a novel computational methodology that combines network theory, agent-based modeling, and machine learning techniques. Unlike traditional economic analyses that focus primarily on legal and regulatory aspects, our approach quantitatively evaluates the systemic resilience and effectiveness of different resolution regimes during simulated financial crises. We developed a sophisticated simulation environment that models the complex interdependencies within banking systems and tests the performance of resolution frameworks under various stress scenarios. Our methodology incorporates elements from computational biology and complex adaptive systems, treating banking networks as evolving ecosystems rather than static structures. The research examines resolution frameworks from the United States (Orderly Liquidation Authority), European Union (Bank Recovery and Resolution Directive), United Kingdom (Banking Act 2009), and Switzerland (Too-Big-to-Fail regime), analyzing their operational mechanisms, funding arrangements, and institutional architectures. Our findings reveal significant variations in framework effectiveness, with certain structural features demonstrating superior crisis containment capabilities. The study identifies specific design elements that contribute to resolution success, including pre-positioned liquidity facilities, clear creditor hierarchy protocols, and cross-border coordination mechanisms. Furthermore, we establish quantitative metrics for evaluating resolution framework performance that extend beyond conventional financial stability measures to include social welfare impacts and economic recovery timelines. This research contributes to the financial stability literature by providing an empirically grounded, computationally sophisticated approach to banking resolution analysis that bridges the gap between theoretical frameworks and practical implementation challenges.