Case study: Tailored fraud detection model for fintech

A fintech startup was struggling to continue operating due to 20% of its transactions being fraudulent.

Find out how this organization used the Darwin platform to build a machine learning model to detect fraud without any data science expertise, saving the company an estimated $457,214 each year.

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