Toast has been granted a patent for a computer-implemented method that predicts interchange charges for credit card transactions. The method involves retrieving historical transaction data, transforming bank identification numbers, training a random forest model, and generating predicted interchange codes for new transactions. GlobalData’s report on Toast gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Toast, Transaction splitting was a key innovation area identified from patents. Toast's grant share as of May 2024 was 61%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting interchange codes for credit card transactions
A recently granted patent (Publication Number: US12002022B2) outlines a computer-implemented method for predicting interchange codes corresponding to credit card transactions. The method involves retrieving a historical set of completed transactions from a database, transforming bank identification numbers (BINs) into BIN features, creating training sets, and utilizing a random forest model for prediction. Transaction features such as total transaction amount, tip percentage, time between authorization and capture, transaction type, address verification response, card network, card type, and merchant category code are considered in the prediction process. The interchange codes generated are a weighted sum of interchange rates and fees, with probabilities assigned to each predicted interchange code based on transaction characteristics.
Furthermore, the patent includes details on a non-transitory computer-readable storage medium storing instructions for predicting interchange codes and a computer program product with program instructions for the same purpose. These components follow a similar process of retrieving historical transactions, transforming BINs into features, creating training sets, training a random forest model, and executing the model for new transactions. The transaction features and BIN features play a crucial role in the prediction process, with the interchange codes being determined based on a weighted sum of interchange rates and fees. The weights assigned to each predicted interchange code indicate the probability of a transaction being assigned to that specific code, providing a comprehensive method for predicting interchange codes accurately in credit card transactions.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
