This is the Electee Review. Today, operational risk management for SMEs and why most small businesses are already managing it wrong. The core argument is this operational risk is not a compliance exercise. It is the gap between what your processes are supposed to do and what they actually do, measured in money, time, and reputation. A delayed shipment, a software glitch that halts invoicing, and unauthorized access that exposes client data, these are not edge cases. They are the ordinary failure modes of any SME that has not mapped where things go wrong. The article draws on the Bank of Italy's AMA framework, which identifies four essential data sources: internal loss data, external loss data, scenario analysis, and factors related to the operating environment and internal controls. The takeaway for an SME is not to replicate a bank's capital model, but to adopt its logic. Convert operational exposure into a measurable estimate, then allocate controls accordingly. The standard European method sets a capital requirement at 15% of the relevant indicator. That number is a signal, not just a regulation. It tells you that regulators have already quantified how much operational slippage costs, and for SMEs, the margin is thinner. The article introduces quantitative tools that matter, frequency and severity distributions, combined into an aggregate loss distribution with the 99.9th percentile used to estimate the cost of the worst plausible operating day. The point is not statistical sophistication, it is decision quality. When you know the tail risk, you know whether a new control, a backup system, or a process redesign is worth the investment. On governance, the three lines of defense model is adapted for SMEs, operations, control functions, and independent verification. The warning is direct. If any line is missing, the risk becomes either unrecognized or uncontrolled. AI enters not as a trend, but as a gap filler. When monitoring is manual, weak signals get lost between emails, tickets, and end-of-month reports. Automated anomaly detection and predictive analysis close that lag. The article is clear. AI does not replace managerial judgment. It makes it faster, more informed, and less dependent on chance. The practical roadmap runs five phases context analysis, risk identification, evaluation and prioritization, control implementation, and ongoing monitoring with KRIs and dashboards. The underlying logic, residual risk after controls is what actually matters, is the right place to end. Operational risk is not invisible, it is just unmeasured. That's the review.