Toast, Inc.

Jared J Rand

Alan Z Zhao

Kevin A Vo

Benjamin Gordon

Alexander H Hails

Ting-Ray Kuo

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 method for increasing a transaction amount corresponding a patron of an establishment, the method including: receiving inputs comprising transaction data corresponding to a transaction, where a portion of the transaction data comprises personally identifiable information (PII), and extracting the PII from the portion of the transaction data, and employing the PII to generate PII transaction data and metadata corresponding to the transaction; analyzing the PII transaction data and the metadata to generate a single universal guest record (UGR) corresponding to the PII transaction data and the metadata, where the single UGR corresponds to the patron, the single UGR comprising UGR transaction metadata corresponding to the transaction and historical transactions associated with the patron; statistically analyzing the UGR metadata to generate a guest segmentation record that corresponds to the patron; and generating content for display on point-of-sale (POS) terminals associated with the establishment, where the content is directed toward increasing an amount of the transaction.

Multichannel system for patron identification and dynamic ordering experience enhancement

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.

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West Roxbury, MA, United States of America

Jared J Rand