Abstract: A method for using aggregated merchant analytics to analyze merchant loan risk is provided. The method includes defining sectors of a geographic region and receiving transaction data for financial transactions occurring within a period of time, the transaction data associated with a plurality of merchants located in the geographic region. The method also includes identifying, for each merchant, one sector in which the merchant is located. The method further includes generating aggregated merchant analytics for each sector based on the transaction data associated with all merchants in the sector. The method also includes determining a total pending loan amount for a subset of the sectors, each sector in the subset having merchants with loans issued thereto, and calculating a loan risk score for each sector using the aggregated merchant analytics and the total pending loan amount. The method further includes displaying on the user computing device the aggregated merchant analytics.

Abstract: A method for intelligent switching for multiple transaction types includes: storing a plurality of action events, each associated with one of a plurality of data types and including corresponding executable processes; storing each of the executable processes corresponding to each action event; receiving a data message from a third party system; identifying a specific data type of the data message; and executing a specific action event that is associated with the specific data type, wherein executing the specific action event includes executing each of the corresponding executable processes, at least one of the corresponding executable processes includes transmitting the received data message to an authorization system associated with the specific data type, and the plurality of data types includes at least a financial transaction message and an automated clearing house message.