A UK-based retail cashback platform incentivizing users to upload shopping receipts for rewards experienced a growing issue with fraudulent submissions. As the platform scaled, cases of tampered receipts, duplicate claims, and synthetic receipt submissions increased, leading to financial losses and operational inefficiencies. Fraud detection was handled manually, requiring extensive verification efforts from the internal team.

Business Objective

The company sought an AI-powered fraud detection system capable of analyzing large volumes of receipt submissions, identifying fraudulent patterns, and reducing the need for manual review while ensuring legitimate claims were processed efficiently.

How We Accomplished It

Codino experts developed a sophisticated fraud detection system leveraging machine learning and computer vision techniques to analyze receipt authenticity and user behavior patterns. The solution employed deep learning-based image recognition to detect signs of tampering, including altered text, inconsistencies in fonts, and pixel-level manipulations. Additionally, a behavioral analytics module monitored user activity, flagging suspicious submission patterns such as excessive claims from a single account or repeated submissions of the same receipt.

The AI model was integrated into the company’s workflow, enabling real-time fraud detection and automated decision-making. Fraudulent claims were automatically flagged for review, significantly reducing the manual verification burden.

The Results

• Fraud Prevention: The AI system identified and prevented a significant volume of fraudulent claims, reducing financial losses.

• Operational Efficiency: Manual verification efforts decreased by over 70%, allowing the fraud detection team to focus on more complex cases.

• Scalability: The AI solution processed thousands of receipt submissions per day, ensuring seamless platform growth.