How Ignacio Piñeiro scaled fraud control with exception-based AI review

Galgo, a Mexican motorcycle-lending fintech, automated its delivery-proof review process to reduce fraud risks and relieve a team previously responsible for manually inspecting more than 3,000 customer-and-vehicle photos each month. Using Zapier, GPT-5-mini, HubSpot, Google Sheets, and Slack, the system verifies whether photos show a real customer with an eligible motorcycle, flags invalid submissions, identifies rejection reasons, and routes only exceptions to human fraud reviewers. The change replaced roughly 150 monthly hours of manual work with review of fewer than 60 flagged photos, while invalid delivery evidence reportedly fell from about 8% to under 2%. Galgo maintains human oversight through accessible logs and feedback-driven prompt adjustments, and Ignacio Piñeiro views the approach as a model for exception-based review in areas such as fraud prevention, quality control, compliance, and content moderation.

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