Abstract: Intelligent application of reserves to transactions are described. In an example, server(s) associated with a payment processing service receive, from a point-of-sale (POS) device operated by a merchant, transaction data associated with a payment transaction between the merchant and a customer. Based on a predictive model, the server(s) can determine a level of risk associated with the merchant and/or the payment transaction and can determine a portion of the transaction to withhold from a settlement amount of the payment transaction based at least in part on the level of risk. The portion can be deposited into a reserves account associated with the payment processing service to satisfy costs associated with chargeback requests.

Abstract: Verified transactions through integrations of social network and payment service computing platforms are described. A payment service computing platform may retrieve one or more profiles of users having a relationship with a first user based on a request received from the first user in the context of a payment transaction with a second user. The payment service computing platform may further determine, based on the one or more profiles, an indirect relationship between the first user and the second user, determine, based at least in part on the determination of the indirect relationship, a trust signal associated with the second user, and cause a user interface to be displayed via a payment application executing on an electronic device associated with the first user, wherein the user interface comprises an indication of an identity of the second user and an indication of the trust signal.

Abstract: Verified transactions through integrations of social network and payment service computing platforms are described. A payment service computing platform may determine a relationship between one or more users and a first user based on interaction data, and, in response to an interaction with a first interactive element corresponding to a second user, cause display of a second asset profile of the second user and a second interactive element to request to purchase assets that correspond to an allocation of a set of assets owned by the second user. The payment service computing platform may further receive a request to purchase a subset of the set of assets based on an interaction with the second interactive element, determine units for each of the assets to be purchased in accordance with a specified value amount, and assign ownership interest of the units to an account associated with the first user.

Abstract: Verified transactions through integrations of social network and payment service computing platforms are described. A payment service computing platform may generate a token associated with a first account associated with a payment service, the token being configured to facilitate a number of transfers of an amount from the first account to one or more second accounts. The payment service computing platform may further receive a first request, from an electronic device of a second user associated with the one or more second accounts, to redeem the amount associated with the token, facilitate acquisition of one or more assets for the second user, wherein the one or more assets are determined by the second user or based at least in part on a machine-learning model trained to infer a preference of the first or second user, and associate the one or more assets with a second account of the second user.

Abstract: Intelligent application of reserves to transactions are described. In an example, server(s) associated with a payment processing service receive, from a point-of-sale (POS) device operated by a merchant, transaction data associated with a payment transaction between the merchant and a customer. Based on a predictive model, the server(s) can determine a level of risk associated with the merchant and/or the payment transaction and can determine a portion of the transaction to withhold from a settlement amount of the payment transaction based at least in part on the level of risk. The portion can be deposited into a reserves account associated with the payment processing service to satisfy costs associated with chargeback requests.

Abstract: Intelligent application of reserves to transactions are described. In an example, server(s) associated with a payment processing service receive, from a point-of-sale (POS) device operated by a merchant, transaction data associated with a payment transaction between the merchant and a customer. Based on a predictive model, the server(s) can determine a level of risk associated with the merchant and/or the payment transaction and can determine a portion of the transaction to withhold from a settlement amount of the payment transaction based at least in part on the level of risk. The portion can be deposited into a reserves account associated with the payment processing service to satisfy costs associated with chargeback requests.