Development of advanced models for banking sector economic capital calculation

Posted: Jun 04, 2023

• Prof. Emma Mehta
• Prof. Emma Zhang
• Prof. Ethan Mendes

Abstract

The calculation of economic capital represents a cornerstone of modern banking risk management, serving as a critical buffer against unexpected financial losses. Traditional approaches to economic capital calculation have predominantly relied on statistical methods developed in the late 20th century, with Value at Risk (VaR) methodologies and various extensions forming the backbone of contemporary practice. However, these conventional frameworks exhibit significant limitations in capturing the complex, non-linear dependencies that characterize modern financial markets, particularly during periods of systemic stress. This research addresses these challenges through the development of a Quantum-Enhanced Neural Capital Framework (QENCF), which represents a paradigm shift in how financial institutions conceptualize and calculate economic capital. The novelty of our approach lies in its integration of quantum computing principles with deep learning architectures, creating a hybrid computational framework that fundamentally reimagines economic capital calculation.