SET Training - Banking and Fintech

By Stanley Epstein -  In the high-stakes theatre of modern finance, we have become masters at managing what we can measure. Boardrooms are well-versed in the precise mathematics of credit and market risk, viewing them as predictable variables in a controllable equation. Yet, there is a "silent disruptor" that refuses to be neatly boxed or fully quantified. Operational risk—the risk of loss resulting from inadequate or failed internal processes, people, systems, or external events—is the ghost in the machine. It is messy, human, and deeply interconnected. To navigate this complexity, we must return to a fundamental framework of inquiry. As Rudyard Kipling famously wrote: “I keep six honest serving-men / (They taught me all I knew); / Their names are What and Why and When / And Where and Who and How.” In an era where banking and fintech are converging into a single, hyper-connected ecosystem, these six questions provide the essential mental map for leaders to move beyond the ...

- By Stanley Epstein - Why escalating cyberattacks, ICT vulnerabilities, and sophisticated fraud are now at the core of operational risk management across Europe’s financial sector. Introduction European banks have entered a new era of operational risk exposure — one dominated not by rogue traders or faulty models, but by invisible adversaries in cyberspace. As digitalisation accelerates and financial institutions migrate core processes to the cloud, operational resilience has become the defining risk management challenge of the decade. The European Banking Authority (EBA) now consistently identifies cyber and ICT (Information and Communication Technology systems) risk as the most critical operational risk facing the banking sector. Rising losses, growing dependence on external technology providers, and an intensifying threat environment underscore the urgency of this challenge. At the same time, fraud, conduct risk, and third-party dependency are converging with cyber threats, amplify...

Artificial intelligence (AI) is transforming the banking industry, not just in customer-facing applications but also behind the scenes in operational risk management. While traditional methods focus on compliance and rule-based systems, AI offers a new frontier for proactive risk mitigation and intelligent response. This article explores five unconventional approaches that leverage AI's power to create a more dynamic and comprehensive risk management strategy: 1. The Conversational Comrade: AI Chatbots for Incident Response Imagine a tireless assistant, always available to guide staff through the initial stages of a security incident. AI-powered chatbots can be trained on historical data, regulations, and best practices to become valuable assets during critical moments. These chatbots can triage incoming reports, categorize them by severity, and offer step-by-step guidance on initial response protocols. Furthermore, they can facilitate root cause analysis by asking focused question...

Every organization, from a bustling startup to a well-established corporation, navigates a sea of uncertainty. This uncertainty manifests as risk, the potential for events to disrupt operations and impact success. But not all risks are created equal. Understanding the difference between operational risk and strategic risk is crucial for effective risk management. Operational Risk: The Engine Room Imagine the engine room of a ship. Here, a network of pipes, valves, and machinery keeps the vessel moving. Operational risks are like leaks, malfunctions, or human error in the engine room. They arise from the day-to-day functions of a business and can disrupt its core operations. Examples: System failures (IT outages, power disruptions) Human error (accidents, negligence) Compliance issues (regulatory violations) Third-party disruptions (supplier delays, transportation problems) Natural disasters (floods, fires) Operational risks tend to be more frequent but have a lower impact on the organi...