Toast, Inc.

Clement Masson

Benjamin Gordon

Alexander H Hails

Alan Z Zhao

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 client engagement is provided. The system includes a rate processor, a revenue forecaster, and an offer processor. The rate processor is configured to perform a binary logistic regression on subscriber data and metrics derived from historical POS data corresponding to subscribers of a point-of-sale (POS) subscription service to generate logistic regression coefficients that are used to calculate probability of default (PD) values for each of the subscribers, and configured to employ new subscriber data and metrics to generate updated PD values for the each of the subscribers. The revenue forecaster is coupled to the rate processor and is configured to employ the historical POS data to predict future POS data for 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, and configured to employ new POS data to generate updated predicted total revenues corresponding to the each of the subscribers. The offer processor is configured to compare the updated predicted total revenues with the predicted total revenues and the updated PD values with the PD values, and configured to automatically generate and transmit engagement instructions for establishments that have received a capital product offer and whose updated PD has increased by more than a threshold amount over the PD.

System for automated origination of capital client engagement based on default probability derived from point-of-sale data

A system for dynamic origination of capital is provided. The system includes a rate processor, a revenue forecaster, and an offer processor. The rate processor is configured to perform a binary logistic regression on subscriber data and metrics derived from historical POS data corresponding to subscribers of a point-of-sale (POS) subscription service to generate logistic regression coefficients that are used to calculate probability of default (PD) values for each of the subscribers, and configured to employ new subscriber data and metrics to generate updated PD values for the each of the subscribers. The revenue forecaster is coupled to the rate processor and is configured to employ the historical POS data to predict future POS data for 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, and configured to employ new POS data to generate updated predicted total revenues corresponding to the each of the subscribers. The offer processor is configured to generate and transmit capital product offers corresponding to the each of the subscribers, where the capital product offers comprise a payback period, prices, and maximum dollar amounts that are a percentage of the predicted total revenues, and configured to compare the updated predicted total revenues with the predicted total revenues and the updated PD values with the PD values, and configured to dynamically adjust the prices and the maximum dollar amounts according to the updated PDs and the updated predicted total revenues.

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Brookline, MA, United States of America

Clement Masson