SET Training - Banking and Fintech

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...