Analyzing the Relationship Between Interest Rate Risk and Profitability in the Banking Industry

Posted: May 18, 2023

• Mason Davis
• Mason Lopez
• Mateo Rivera

Abstract

The banking industry operates within a complex financial ecosystem where interest rate risk represents one of the most significant challenges to sustained profitability. Traditional approaches to understanding this relationship have predominantly relied on linear models and static financial ratios, which often fail to capture the dynamic, non-linear interactions between interest rate exposures and bank performance metrics. This research introduces a paradigm shift in how we conceptualize and analyze this critical relationship by leveraging computational techniques from quantum computing and complex systems theory. Conventional financial literature has established that interest rate risk affects bank profitability through multiple channels, including net interest margin compression, changes in the value of fixed-income assets, and alterations in customer behavior. However, these studies typically assume linear relationships and stationary conditions, overlooking the emergent properties that arise from the complex interplay of multiple risk factors. Our research addresses this gap by proposing a novel methodological framework that treats the banking system as a complex adaptive system rather than a collection of independent financial variables. This paper makes several distinctive contributions to the field. First, we develop a quantum-inspired optimization algorithm specifically tailored for financial risk analysis, capable of identifying optimal risk thresholds that maximize profitability under varying interest rate scenarios. Second, we introduce a multi-dimensional risk assessment framework that integrates traditional financial metrics with unconventional indicators such as technological adaptability and strategic flexibility. Third, we demonstrate through empirical analysis that