Abstract: In some examples, a system receives first transaction data for first transactions processed by a payment service, and uses a first model to determine, based on the first transaction data, that a probability of default for a user of the payment service satisfies a threshold. The system generates, based on a first financing factor, a first offer of credit for the user, and sends the first offer to the user. The system determines, based on third party information, that the user has additional income, and receives, from one or more of the third-party systems, second transaction data indicating the additional income. The system uses a machine learning model included in the first model to determine a second financing factor based on the second transaction data, and generates, based on the first financing factor and the second financing factor, a second offer of credit to send to the user.

Abstract: In one embodiment, a method includes calculating, using a risk model for a merchant having an account with a payment service, a financing factor based on first data representing multiple transactions associated with the merchant and sending, to a computing device associated with the merchant, information associated with an offer of credit based on the financing factor for the merchant. The method also includes accessing second data stored by the payment service and containing information associated with the merchant that is not related to the transactions, where the second data provides an indication of additional future revenue for the merchant, and updating the offer of credit sent to the merchant based on the second data.