Bank of America Corporation
SYSTEMS AND METHODS FOR PRE-EXECUTING IDIOSYNCRATIC COMPUTATION THROUGH THE APPLICATION OF ALGORITHMIC PREDICTION OF USER BEHAVIOR PATTERNS

Abstract:

Aspects of the disclosure relate to a machine-learning transaction-prediction engine for seasoning an anticipated manual transaction. The transaction may occur in a transaction session. The seasoning may occur prior to execution of the anticipated manual transaction, The transaction-prediction engine may include a receiving/storage module configured to receive and store identification information of the transactor. The engine may also include a step-retrieval module configured to retrieve a set of in-session transaction steps associated with the transactor. In addition, the engine may include a history-retrieval module configured to retrieve, based on the stored identification information, historical transactional information associated with the transactor. The historical transaction information comprising a plurality of historical transaction patterns associated with the transactor. The engine may also include a processor module configured to initiate the anticipated manual transaction by predicting and provisionally completing the in-session transaction steps. The predicting may be based on the set of in-session transaction associated with the transactor and on the plurality of historical patterns.