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COMPUTER-BASED SYSTEMS CONFIGURED FOR AUTOMATED ACTIVITY VERIFICATION BASED ON OPTICAL CHARACTER RECOGNITION MODELS AND METHODS OF USE THEREOF

Abstract:

Systems and methods for detecting and mitigating fraud include a processor for performing steps including receiving a digital image of a receipt and utilizing an optical character recognition model to encode a digital representation of transaction information from the receipt. The processor extracts a payee feature, an amount feature, and a payment date feature from the transaction data, and generating a receipt feature vector from the payee feature, the amount feature and the payment date feature. The processor receives historical transaction data representing historical transactions, generates a transaction feature vector for each historical transaction and then utilizes a machine learning model to predict a matching transaction from the transaction history that matches the receipt based on the receipt feature vector and each of the transaction feature vectors to determine a difference between the payment amount of the receipt and the payment authorization of the matching transaction.