Abstract: A method includes a processing computer querying a data store for plurality of network data since a last epoch of data. The processing computer can generate matrices based on the plurality of network data and then perform tensor factorization on the matrices, to obtain latent values in the network data. The processing computer can then determine that the latent values satisfy a predetermined criterion. The processing computer can input the latent values into a model associated with the signal, wherein the model generates output data. The processing computer can then generate an alert comprising the output data and then transmit the alert to a remote server computer.

Abstract: A computer-implemented method of identifying federations of manufacturing apps using House of Quality (HoQ) analysis includes receiving user request information comprising a plurality of desired functions and an importance value for each of the plurality of desired functions and generating a correlation matrix between the plurality of apps, wherein each element of the correlation matrix indicates a degree of correlation between a pair of apps. A relationship matrix is generated which comprises numerical values indicating relationships between a plurality of apps and the plurality of desired functions, wherein each column of relationship matrix is associated with an app and each row is associated with a desired function. Next, a weighted matrix is created by multiplying each row in the relationship matrix by the importance value corresponding to the desired function associated with the row.

Abstract: Embodiments of the invention relate in part to determining a testing model and providing a testing transaction score for transactions. The testing transaction score may indicate a likelihood that the transaction is a testing transaction. One embodiment of the invention discloses a method comprising receiving a first authorization message for a first transaction using an account, determining a testing transaction score for the first transaction using a testing model, and determining that the first transaction is a testing transaction based on the testing transaction score, wherein the testing transaction score for the first transaction is used for declining a second transaction using the same account conducted after the first transaction.

Abstract: A computer-implemented method of identifying federations of manufacturing apps using House of Quality (HoQ) analysis includes receiving user request information comprising a plurality of desired functions and an importance value for each of the plurality of desired functions and generating a correlation matrix between the plurality of apps, wherein each element of the correlation matrix indicates a degree of correlation between a pair of apps. A relationship matrix is generated which comprises numerical values indicating relationships between a plurality of apps and the plurality of desired functions, wherein each column of relationship matrix is associated with an app and each row is associated with a desired function. Next, a weighted matrix is created by multiplying each row in the relationship matrix by the importance value corresponding to the desired function associated with the row.

Abstract: Embodiments of the invention relate in part to determining a testing model and providing a testing transaction score for transactions. The testing transaction score may indicate a likelihood that the transaction is a testing transaction. One embodiment of the invention discloses a method comprising receiving a first authorization message for a first transaction using an account, determining a testing transaction score for the first transaction using a testing model, and determining that the first transaction is a testing transaction based on the testing transaction score, wherein the testing transaction score for the first transaction is used for declining a second transaction using the same account conducted after the first transaction.

Abstract: Embodiments of the invention relate in part to determining a testing model and providing a testing transaction score for transactions. The testing transaction score may indicate a likelihood that the transaction is a testing transaction. One embodiment of the invention discloses a method comprising receiving a first authorization message for a first transaction using an account, determining a testing transaction score for the first transaction using a testing model, and determining that the first transaction is a testing transaction based on the testing transaction score, wherein the testing transaction score for the first transaction is used for declining a second transaction using the same account conducted after the first transaction.

Abstract: Embodiments of the invention relate in part to determining a testing model and providing a testing transaction score for transactions. The testing transaction score may indicate a likelihood that the transaction is a testing transaction. One embodiment of the invention discloses a method comprising receiving a first authorization message for a first transaction using an account, determining a testing transaction score for the first transaction using a testing model, and determining that the first transaction is a testing transaction based on the testing transaction score, wherein the testing transaction score for the first transaction is used for declining a second transaction using the same account conducted after the first transaction.

Abstract: A system, apparatus, and method for reducing fraud in payment transactions by identifying a potential point of compromise (POC) that may lead to subsequent fraudulent transactions, or confirming that a suspected point of compromise is in fact responsible for a security breach leading to fraudulent payment transactions. The invention is also directed to a system, apparatus, and method for identifying data or transaction characteristics that may be used to most effectively identify a point of compromise in a payment transaction system.

Abstract: A system, apparatus, and method for reducing fraud in payment transactions by identifying a potential point of compromise (POC) that may lead to subsequent fraudulent transactions, or confirming that a suspected point of compromise is in fact responsible for a security breach leading to fraudulent payment transactions.