SET Training - Banking and Fintech

By Stanley Epstein -  The emerging operational, financial, and governance risks of autonomous AI agents in modern banking systems Introduction Artificial intelligence has long been part of banking operations. Fraud detection, credit scoring, and anti-money laundering systems have relied on machine learning models for years. But a new phase is emerging. Banks are beginning to deploy AI agents —autonomous or semi-autonomous systems capable of planning tasks, executing transactions, interacting with external tools, and making operational decisions with limited human oversight. This shift from passive analytics to agentic AI introduces profound efficiency gains. At the same time, it expands the risk landscape in ways that traditional governance frameworks were never designed to handle. Regulators and central banks are increasingly paying attention. The transformation is not simply technological. It raises questions about liability, systemic stability, operational resilience, and trus...

By Stanley Epstein -  Why 2026 Is the Inflection Point for Enterprise AI Agents — and Why Governance Will Decide the Winners -  Artificial intelligence agents are moving from pilot projects to production systems at remarkable speed. In 2026, the conversation is no longer about experimentation. It is about deployment, infrastructure, and control. This shift represents more than a technology upgrade. It signals a structural change in how organizations think about automation, decision-making, and productivity. But acceleration brings new risks alongside measurable gains. The Enterprise Shift When Jensen Huang, CEO of Nvidia, recently described enterprise adoption of AI agents as “skyrocketing,” he linked the surge directly to explosive demand for compute infrastructure. The implication is clear. Companies are not simply testing AI tools. They are building the backbone for agentic systems capable of planning, reasoning, and acting with increasing autonomy. This aligns with forwar...