Abstract: A method for predicting future spending can include receiving, by processing circuitry, at least one data point of a user, wherein the at least one data point includes at least one transaction attribute of at least one user transaction, analyzing the at least one data point, determining at least one peer group of the user based in part on the at least one data point of the user, comparing the at least one data point of the user with data associated with the at least one peer group of the user, and predicting at least one future spending activity of the user.

Abstract: Methods, systems, and computer readable media for providing a personalized offers integration platform are provided. Personalized offers may be based on transaction details, geographic locations, and/or consumer preferences. In one embodiment, a wallet system, user equipment, electronic devices, and a payment and offers integration platform (POIP) are provided. The wallet system can receive of transaction details, geographic locations, and/or consumer preferences associated with a point of sale transaction. The received information may be translated into metadata, and an offer request is generated that includes the metadata. The POIP is configured to receive the offer request, determine a set of criteria from the metadata, query a plurality of offer or reward engines using the set of criteria for retrieving offers that correlate to the offer request, receive a plurality of offers from the plurality of offer or reward engines, and integrate the plurality of offers for formulating an offer response.