Toast, Inc.

Alan Z Zhao

Jared J Rand

Kevin A Vo

Alexander H Hails

Martin Kressirer

Binghuan Zhang

Pearse J O'Flynn

Hardeep K Gill

Benjamin Gordon

Clement Masson

Benjamin C W Tang

A computer-implemented method for predicting interchange charges includes: retrieving a historical transactions set, where each completed transaction in the set includes transaction features, a bank identification number (BIN), and a corresponding true interchange code; transforming all BINs in the set into a corresponding plurality of BIN features that comprise probabilities; creating a first training set including all transaction features, all pluralities of BIN features, and all true interchange codes associated with the historical transactions set; training a random forest model using the first training set and generating a second training set including rounded BIN features, rounded transaction features, discrete ones of the transaction features, and the true interchange codes; training the random forest model using the second training set to generate a trained random forest model for prediction of the interchange codes; and executing the trained random forest model for new transactions to generate corresponding predicted interchange codes.

Interchange code prediction system for processing credit card transactions

Optimized interchange code prediction system for processing credit card transactions

Stochastic apparatus and method for estimating credit card type when predicting interchange code to process credit card transactions

Low latency bank card type prediction system for estimation of interchange codes during transaction processing

System for dynamic prediction of interchange rates for credit card transaction processing

A system for automated origination of capital includes a rate processor, a revenue forecaster, and an offer processor. The rate processor generates prices for capital product offers to subscribers of a point-of-sale (POS) subscription service, where the prices are generated by employing probability of default (PD) values that are derived from historical POS data corresponding to each of the subscribers. The revenue forecaster is coupled to the rate processor and is configured to employ the configured to employ the historical POS data and locations of establishments corresponding to the each of said subscribers to predict future POS data for the establishments corresponding to the each of the subscribers, and to employ the future POS data to generate predicted total revenues corresponding to the each of the subscribers over a payback period. The offer processor generates and transmits the capital product offers corresponding to the each of the subscribers, where the capital product offers comprise the payback period, the prices, and maximum dollar amounts that are a percentage of the predicted total revenues.

System for automated origination of capital based on point-of-sale data informed by location

A system for automated origination of capital includes a rate processor, a revenue forecaster, and an offer processor. The rate processor generates prices for capital product offers to subscribers of a point-of-sale (POS) subscription service, where the prices are generated by employing probability of default (PD) values that are derived from historical POS data corresponding to each of the subscribers. The revenue forecaster employs the historical POS data to predict future POS data for establishments corresponding to the each of the subscribers and employs the future POS data to generate predicted total revenues corresponding to the each of the subscribers over a payback period. The offer processor generates and transmits the capital product offers corresponding to the each of the subscribers, where the capital product offers comprise the payback period, the prices, and maximum dollar amounts that are a percentage of the predicted total revenues.

System for automated origination of capital based on point-of-sale data

A system for automated origination of capital includes a rate processor, a revenue forecaster, and an offer processor. The rate processor is configured to generate prices for capital product offers to subscribers of a point-of-sale (POS) subscription service, where the prices are generated by employing probability of default (PD) values that are derived from historical POS data corresponding to each of the subscribers, and where each historical POS datum comprises an indicator denoting a season of the year in which the datum was generated. The revenue forecaster employs the historical POS data to predict future POS data for establishments corresponding to the each of the subscribers and employs the future POS data to generate predicted total revenues corresponding to the each of the subscribers over a payback period. The offer processor generates and transmits the capital product offers corresponding to the each of the subscribers, where the capital product offers comprise the payback period, the prices, and maximum dollar amounts that are a percentage of the predicted total revenues.

System for automated origination of capital based on point-of-sale data informed by time of year

A system for dynamic origination of capital includes a rate processor, a revenue forecaster, and an offer processor. The rate processor is configured to generate a price for a capital product offer to a first subscriber of a point-of-sale (POS) subscription service, where the interest rate is generated by employing a probability of default (PD) value that is derived from historical POS data corresponding to all subscribers. The revenue forecaster is coupled to the rate processor and is configured to employ first historical POS data for an establishment corresponding to the first subscriber to predict future POS data using a neural network trained on the historical data corresponding to all subscribers, and to employ the future POS data to generate a predicted total revenue over a payback period for the first subscriber. The offer processor is configured to generate and transmit the capital product offer corresponding to the first subscriber, where the capital product offer comprises the payback period, the price, and a maximum dollar amount that is a percentage of the predicted total revenue.

Dynamic origination of capital pricing determination based on forecasted point-of-sale revenue

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Cambridge, MA, United States of America

Alan Z Zhao