What Fraud Detection Actually Requires for a Mid-Size FinTech
Mid-size fintechs occupy an uncomfortable middle ground: too small for an eight-figure enterprise fraud platform, too large and too exposed to get by on spreadsheet rules and a Slack channel for suspicious transactions. A real fraud detection capability needs five things working together — clean real-time data pipelines, a hybrid model architecture that blends rules with machine learning, an explainability layer that satisfies regulators, an operational review process staffed for the alert volume you'll actually generate, and a build-vs-buy decision made on a three-year total cost basis, not a demo. Skipping any one of these doesn't make the system cheaper. It just moves the cost to next year, usually in the form of a loss, a fine, or a compliance finding.