In one embodiment, a method includes receiving, by a payment server and from a messaging application executing on a first mobile device operated by a first user, a request to initiate a payment transaction using a payment application. The request includes a payment amount and an identifier associated with the first user. The method includes facilitating a first adjustment to a balance associated with the financial account of the first user in the data store identified based on the identifier. The method includes generating a link associated with the first adjustment and transmitting the link to the first mobile device. The method includes, upon receiving from a second user operating a messaging application, an indication that the second user has interacted with the link within the messaging application, facilitating a second adjustment of a balance of a financial account of the second user according to the payment amount.

A device may receive data that is related to historical reports associated with an organization, historical audits of the historical reports, and individuals associated with the historical reports. The device may determine a multi-entity profile for the data. The multi-entity profile may include a set of groupings of the data by a set of attributes included in the data. The device may determine, using the multi-entity profile, a set of supervised model features for the historical reports. The device may determine, using the multi-entity profile, a set of unsupervised model features for the historical reports independent of the historical audits. The device may determine, utilizing a model, a score for a report. The device may perform one or more actions.

In an embodiment, a system for preventing the mailing of duplicate checks is provided. When payment information is received for a check, a code is generated. The code may identify the payment and may be based on the payment information. When the check is composed for the payment, the code is included such that when the check is printed, the code is printed on the check. After the check is printed and sent to the inserter for insertion into an envelope, the inserter reads the code on the check. The inserter compares the code to a list of previously scanned codes. If the inserter finds the code on the list, then the check is a duplicate check and can be prevented from being mailed. If the code is not one the list, then the inserter adds the code to the list, and allows the check to be mailed.

Relative to a gaming system, a jackpot processing server is configured to generate at least one gaming win reporting form, such as a W2G, in response to a gaming win by the player. The jackpot processing server is configured to store that form and provide access to the form. A code may be provided to the player which is used to generate a communication link to a webserver for accessing the form. Alternatively, the form may be emailed to the player, such as in response to a request to an email server. The email server may be a public email server that communicates to the jackpot processing server via a secure communication module.

A computer-implemented method includes: receiving, by a computing device, a plurality of journal entries from a plurality of transactional systems; determining, by the computing device, association scores for a plurality of pairs of journal entries selected from the plurality of journal entries; generating, by the computing device, a reconciliation graph including a plurality of nodes representing the plurality of journal entries and a plurality of edges based on the determined association scores; recommending, by the computing device, actions to apply to at least one journal entry of the plurality of journal entries to minimize a number of nodes not connected by the plurality of edges in the reconciliation graph; receiving, by the computing device, feedback regarding the recommended actions to apply to the at least one journal entry; and updating, by the computing device, the reconciliation graph based on the feedback.

Musical catalog amplification services that leverage or deploy a computer-based musical composition system are described. The computer-based musical composition system employs algorithms and, optionally, artificial intelligence to generate new music based on analyses of existing music. The new music may be wholly distinctive from, or may include musical variations of, the existing music. Rights in the new music generated by the computer-based musical composition system are granted to the rights holder(s) of the existing music. In this way, the musical catalog(s) of the rights holder(s) is/are amplified to include additional music assets. The computer-based musical composition system may be tuned so that the new music sounds more like, or less like, the existing music of the rights holder(s). Revenues generated from the new music are shared between the musical catalog amplification service provider and the rights holder(s).

Musical catalog amplification services that leverage or deploy a computer-based musical composition system are described. The computer-based musical composition system employs algorithms and, optionally, artificial intelligence to generate new music based on analyses of existing music. The new music may be wholly distinctive from, or may include musical variations of, the existing music. Rights in the new music generated by the computer-based musical composition system are granted to the rights holder(s) of the existing music. In this way, the musical catalog(s) of the rights holder(s) is/are amplified to include additional music assets. The computer-based musical composition system may be tuned so that the new music sounds more like, or less like, the existing music of the rights holder(s). Revenues generated from the new music are shared between the musical catalog amplification service provider and the rights holder(s).

A method, apparatus, system, and computer program product for creating a forecasting model for payroll records. Payroll records are received for a group of employers. The payroll records comprise granular data parameters about employees of the group of employers. A forecasting model is created the that aligns the payroll records to high-level employment data. Creating the forecasting model includes identifying predictor variables from the granular data parameters of the payroll records. Creating the forecasting model includes generating a set of basis functions from the predictor variables. Creating the forecasting model includes combining the set of basis functions to create the forecasting model.

A computerized-method for generating a dataset for a Machine Learning (ML) model for an increased accurate financial crime detection from an initiation stage of the ML model implementation. The computerized-method includes: retrieval of financial transaction records from a database of financial transaction records to arrange a dataset of financial transaction records, according to preconfigured techniques. Then, processing the records in the dataset; Then, operating feature engineering on preselected anomalous related features to yield probabilistic categorical features and to yield probabilistic numerical features, and then combining the probabilistic categorical features with the probabilistic numerical features to generate a complex features dataset, and providing the probabilistic categorical features, the probabilistic numerical features and the complex features dataset to an ML model, thus, increasing accuracy of detection that is performed right from an initiation stage of the ML model implementation.

Provided is a computer-implemented method for determining a dominant account profile of an account. The method may include receiving transaction data associated with a plurality of payment transactions conducted within a predetermined time interval of activation of an account involved in the plurality of payment transactions, generating a dominant account profile classification model, determining a plurality of prediction scores for the account based on the dominant account profile classification model and the transaction data, where determining the plurality of prediction scores includes determining, for the user, a prediction score for each dominant account profile, where a prediction score includes a prediction of whether the user will conduct a threshold value of payment transactions using the account in one or more payment transaction categories of a plurality of payment transaction categories, and communicating data associated with the plurality of prediction scores.