Abstract: Systems and methods are presented for determining risk levels for consumer-to-consumer (C2C) transactions on brokering websites. The risk levels can be based on payment processing network (e.g. Visa) account data as well as external data, such as geo-location using IP addresses, fraud bureau data, and star ratings. The buying and selling consumers can have multiple risk scores for each transaction, such as a fraud, credit, return/chargeback, dissatisfaction, product misuse, nonreturnable, and defect risk scores. The buying and selling consumers can trade their risk levels before proceeding with the transaction.

Abstract: A system, apparatus, computer readable media, and method are disclosed for generating analytics on customers of service provider merchants. In an example, a transaction record associated with an account identifier of a customer that purchased a first service from a first merchant may be processed and a service date for the first service may be determined. Other transaction records comprising the account identifier and that satisfy a temporal filter may be identified. Each of the other transaction records may include transaction data associated with at least one of: (1) purchase of another service to be provided within a first predetermined amount of time of the service date, and (2) purchase of a product within a second predetermined amount of time of the service date. A spending profile including information on the first service, the service date, and the transaction data for each of the other transaction records may be generated.

Abstract: A system, apparatus, computer readable media, and method are disclosed for generating analytics on customers of service provider merchants. In an example, a transaction record associated with an account identifier of a customer that purchased a first service from a first merchant may be processed and a service date for the first service may be determined. Other transaction records comprising the account identifier and that satisfy a temporal filter may be identified. Each of the other transaction records may include transaction data associated with at least one of: (1) purchase of another service to be provided within a first predetermined amount of time of the service date, and (2) purchase of a product within a second predetermined amount of time of the service date. A spending profile including information on the first service, the service date, and the transaction data for each of the other transaction records may be generated.

Abstract: Systems and methods are presented for determining risk levels for consumer-to-consumer (C2C) transactions on brokering websites. The risk levels can be based on payment processing network (e.g. Visa) account data as well as external data, such as geo-location using IP addresses, fraud bureau data, and star ratings. The buying and selling consumers can have multiple risk scores for each transaction, such as a fraud, credit, return/chargeback, dissatisfaction, product misuse, nonreturnable, and defect risk scores. The buying and selling consumers can trade their risk levels before proceeding with the transaction.