Case Study: a fintech startup reduces fraud and saves $457,214 annually with SparkCognition’s Darwin

Tailored Fraud Detection Models for Fintech

A fintech startup in Mexico, struggling with an existential threat from fraud that accounted for 20% of its transactions, partnered with SparkCognition. Facing untenable losses and a potential shutdown within two years, the startup urgently needed a solution to accurately detect fraudulent activity.

Using SparkCognition's Darwin automated machine learning product, the startup built a highly accurate fraud detection model without any internal data science expertise. The resulting model detects fraud with 90% accuracy, processes transactions in real time, and has saved the company $457,214 annually, providing a massive return on investment and saving the business from bankruptcy.