Toast has patented a computer-implemented method for predicting interchange charges for credit card transactions. The method involves training a random forest model using historical transaction data and generating a lookup table to predict interchange charges for new transactions based on specific transaction features. GlobalData’s report on Toast gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Toast, Transaction splitting was a key innovation area identified from patents. Toast's grant share as of January 2024 was 71%. Grant share is based on the ratio of number of grants to total number of patents.

Predicting interchange codes for credit card transactions

Source: United States Patent and Trademark Office (USPTO). Credit: Toast Inc

A recently granted patent (Publication Number: US11861666B2) discloses 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, extracting transaction features and bank identification numbers (BINs), transforming BINs into corresponding BIN features, and creating training sets for a random forest model. The model is trained to generate a lookup table mapping transaction features to predicted interchange charges, allowing for accurate predictions for new transactions based on specific features like transaction amount, tip percentage, transaction type, and more. The method aims to streamline the prediction process and improve accuracy by utilizing historical data and machine learning techniques.

Furthermore, the patent includes additional claims related to the transaction features, BIN features, and the overall process of predicting interchange codes. These claims specify the inclusion of various transaction details like total transaction amount, tip percentage, transaction type, address verification system response, card network, card type, and merchant category code. The method also considers different BIN features such as regulated debit, debit, rewards, and high rewards to enhance the prediction accuracy. By storing instructions on a computer-readable storage medium and a computer program product, the patent provides a comprehensive framework for efficiently predicting interchange codes for credit card transactions, catering to the complex and varied nature of transaction data in the financial industry.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

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.