Implementation of comprehensive software risk management frameworks in banking IT

Posted: Sep 08, 2022

• Joseph White
• Levi Wilson
• Liam Jones

Abstract

The digital transformation of banking services has created an increasingly complex software ecosystem where traditional risk management approaches struggle to address the dynamic nature of modern threats. Banking institutions face unprecedented challenges in managing software risks that span across legacy systems, cloud infrastructure, mobile platforms, and third-party integrations. Conventional risk management frameworks, largely derived from industrial safety models and compliance requirements, often fail to capture the emergent properties and interconnected vulnerabilities characteristic of contemporary banking IT environments. This research addresses this gap by proposing a fundamentally new approach to software risk management that integrates principles from quantum computing and federated learning. The novelty of our work lies in reconceptualizing software risk not as a static property to be measured, but as a dynamic, multi-dimensional phenomenon that requires continuous, adaptive assessment. We move beyond the binary classifications of traditional risk matrices toward probabilistic risk landscapes that can capture the complex interdependencies and emergent behaviors in banking software systems. Our approach represents a significant departure from existing methodologies by incorporating