In the complex landscape of modern enterprises, risk management often appears sleek and forward-thinking on the surface. However, beneath this façade lies a significant issue: hidden risk debt, also known as “digital asbestos.” This concept was articulated by Alex Golbin, a senior financial services technology and data risk executive, who emphasizes that such liabilities are frequently overlooked within organizations. The accountability for this growing risk debt often dissipates and is not attributed to any specific individual or team, creating a pervasive issue that can have serious repercussions for organizations.

According to Golbin, the layers of liability accumulate when an organization prioritizes immediate efficiency over thorough validation and remediation processes. This practice can lead to a significant buildup of risk debt, especially in environments characterized by weak data lineage, reliance on manual workarounds that become entrenched, and dependencies on third-party vendors and artificial intelligence. Essentially, organizations may opt for quick fixes today, only to face complex challenges later on due to unaddressed vulnerabilities.

Golbin points out a critical flaw in the organizational structure regarding risk acceptance. Often, product owners push for expedient launches, while technology teams are quick to accept workarounds that sidestep due diligence. Meanwhile, risk managers document these exceptions without considering the long-term implications. Each decision may seem rational in isolation, but the cumulative effect results in increased exposure that no single team takes ownership of.

“Too often, one team books the speed, while another team inherits the liability,” Golbin remarked. The consequences become evident when systems fail; operations are left to manage the immediate disruption, technology departments bear the financial burden of remediation, and ultimately, the board of directors is left to grapple with the escalated risk. This cycle of accountability is problematic and requires a reevaluation of how organizations manage risk at multiple levels.

In a recent video interview with ISMG, Golbin elaborated on several key themes related to risk debt, including the warning signs that indicate risk debt is accumulating within an organization. He advocated for the adoption of a four-part framework that involves quantifying exposure, age, dependency, and retirement costs associated with legacy systems. This approach could help organizations better understand and manage their risk landscapes.

Additionally, Golbin addressed the potential pitfalls of artificial intelligence in exacerbating existing risk debt across enterprises. While AI can offer significant benefits, it also has the potential to accelerate vulnerabilities if not carefully managed. This duality necessitates a robust strategy for integrating AI within risk management frameworks.

With over two decades of experience in the field, Golbin’s insights are drawn from a wealth of knowledge gained in Fortune 500 companies and banks. His leadership experience encompasses various facets of enterprise risk, regulatory remediation, technology, data management, and resilience transformation. Having built and led a multi-bank risk-assessment initiative involving 16 financial institutions, he is well-equipped to navigate the complexities of risk management. His contributions to developing risk-management, cybersecurity, and resilience frameworks span intricate enterprise ecosystems and third-party interactions, highlighting the critical nature of these discussions in the current financial services landscape.

As organizations continue to evolve in a technology-driven environment, the need for a proactive approach to risk management becomes increasingly vital. By addressing hidden risk debt and establishing clear lines of accountability, enterprises can not only protect themselves from potential pitfalls but also ensure they are strategically positioned for future growth and stability.