Systems, methods, and computer program products are provided for validating a deposit request. The method includes receiving a deposit request from a user device. The deposit request includes a deposit transaction information relating to an intended deposit. The method also includes determining a deposit transaction confidence level based on the deposit transaction information. The deposit transaction confidence level indicates a likelihood of the intended deposit being perfected. The method further includes causing a transmission of an audit request to the user device relating to the deposit request upon determining the deposit transaction confidence level is below a confidence level threshold. The audit request includes a request to confirm one or more details relating to the deposit request. The method still further includes determining a deposit determination based on a response to the audit response. The deposit determination indicates whether the intended deposit will be executed.

Aspects of the disclosure relate to isolating and reinstating nodes in a distributed ledger using proof of innocence. In some embodiments, a first plug-in embedded with the blockchain network may monitor consumer-initiated transactions submitted to an enterprise organization node to determine the legitimacy of each consumer-initiated transaction. The first plug-in may identify consumer-initiated transactions associated with malicious activity and may flag the consumer node for further analysis. A second plug-in may identify and analyze the consumer-initiated transactions associated with the consumer node to determine a proof of innocence value associated with the consumer node. The first plug-in may isolate the consumer node from the distributed ledger if the proof of innocence value exceeds a proof of innocence threshold. Alternatively, the first plug-in may permit the consumer node to remain within the distributed ledger if the proof of innocence value falls below the proof of innocence threshold.

A federated-data-room server manages information about a collection of electronic documents residing elsewhere (under different organizational/customer control). The server can anchor documents to a blockchain, record usage history of each document, and provide access to the documents for authorized users. As a result, the federated-data-room server operates on customers' data, while leaving the data in control of the customers. At the same time, the federated-data-room server provides data access and enables traceability via blockchain recordation of document identifiers and document hash values.

Systems as described herein generate an outstanding check alert. An alert generating server may receive transaction records associated with a plurality of checking accounts. The alert generating server may user a first machine learning classifier to determine a transaction pattern indicating a merchant has failed to process outstanding checks for a period of time. The alert generating server may receive sequential check information comprising at least one missing check number associated with a particular checking account. The alert generating server may user a second machine learning classifier to determine at least one outstanding check associated with the particular checking account. The alert generating server may send an alert indicating the at least one outstanding check to a user device.

Systems as described herein generate an outstanding check alert. An alert generating server may receive transaction records associated with a plurality of checking accounts. The alert generating server may user a first machine learning classifier to determine a transaction pattern indicating a merchant has failed to process outstanding checks for a period of time. The alert generating server may receive sequential check information comprising at least one missing check number associated with a particular checking account. The alert generating server may user a second machine learning classifier to determine at least one outstanding check associated with the particular checking account. The alert generating server may send an alert indicating the at least one outstanding check to a user device.

A method of rating credit risk is provided. The method comprises calculating a number of credit risk factors associated with a financial instrument, wherein each credit risk factor is calculated iteratively at a first timestep as a discrete probabilistic wave function representing a superposition state of scores. The discrete probabilistic wave function of each credit risk factor is measured after each calculation iteration for the first timestep. The probabilistic wave functions of the credit risk factors are then linearly combined to calculate a discrete probabilistic wave function for a final credit rating of the financial instrument for the first timestep, which is displayed in a user interface. The above steps are repeated for a second timestep using the probabilistic wave functions of the credit risk factors at the first timestep as initial states for the second timestep.

The purpose of the present disclosure is to enhance the degree of freedom for settlement, even once the settlement method has been selected by the user. A method for processing information makes an information processing device execute: acquiring information from a unit storing settlement history information including at least one piece of settlement information on each of a plurality of users, the acquired information containing at least one piece of settlement information on a first user; specifying at least one piece of settlement information from the settlement history information, in response to operation by the first user with another information processing device, on which the settlement history information is displayed; displaying an amount of money based on a settlement amount included in the at least one piece of settlement information on the other information processing device, the displayed amount being an amount to be loaned to the first user; and lending the amount of money determined in response to the operation by the first user with the other information processing device to the first user.

In some implementations, a prediction and monitoring system may processing, using a machine learning model, account data associated with an account that is associated with a user of a user device to identify a series of recurring events associated with the user device. The prediction and monitoring system may generate, using the machine learning model, a predicted transaction date and a predicted transaction amount that are both associated with the series of recurring events. The prediction and monitoring system may select, based on additional account data associated with the account and at least one of the predicted transaction date or the predicted transaction amount, a particular communication scheme, of a plurality of communication schemes, for communicating with the user. The prediction and monitoring system may transmit at least one message according to the particular communication scheme to facilitate authentication of the user.

In some implementations, a prediction and monitoring system may processing, using a machine learning model, account data associated with an account that is associated with a user of a user device to identify a series of recurring events associated with the user device. The prediction and monitoring system may generate, using the machine learning model, a predicted transaction date and a predicted transaction amount that are both associated with the series of recurring events. The prediction and monitoring system may select, based on additional account data associated with the account and at least one of the predicted transaction date or the predicted transaction amount, a particular communication scheme, of a plurality of communication schemes, for communicating with the user. The prediction and monitoring system may transmit at least one message according to the particular communication scheme to facilitate authentication of the user.

A computer-implemented system and method includes determining, by a mobile device associated with a user, a location of the user, generating, by the mobile device, a code comprising a tokenized value for sending funds and the location of the user, transmitting, by the mobile device, the code to a point of sale (POS) terminal associated with a merchant as part of a mobile wallet transaction, and receiving, by the mobile device, an indication that the mobile wallet transaction has been completed.