Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for an end-to-end solution to auto-identifying features. In one embodiment, a novel architecture is presented that enables the identification of optimal features and feature processes for use by a machine learning model. The novel architecture introduces a feature orchestrator for managing, routing, and retrieving the data and features associated with analytical job request. The novel architecture also introduces a feature store designed to identify, rank, and store the features and data used in the analysis. To aid in identifying the optimal features and feature processes, a training system may also be included in the solution which can perform some of the training and scoring of the features.

Abstract: A mechanism is provided for secure sensitive private information dependent transactions. A query and a transaction token S associated with a current transaction between a SPI owner and the service provider is received. Particular SPI required is identified based on the query. A request for the particular SPI from the SPI owner is constructed thereby forming a constructed request. The constructed request is sent to one or more authorized devices associated with the SPI owner enrolled with the cognitive SPI broker. The particular SPI is received from a device of the SPI owner thereby forming received SPI. The received SPI is used complete the transaction. A notification is then sent to the SPI owner that the transaction has been completed.

Abstract: Systems and methods for regulating service behavior include a system provider device where a policy is registered. The policy defines a modified service behavior for a service running one or more remote servers. In some embodiments, the registered policy is transmitted to a first satellite agent located at a first remote server. By way of example, and after transmitting the registered policy to the first satellite agent, data is received from the first satellite agent corresponding to the service having the modified service behavior running on the first remote server. Thereafter, the system provider may verify that the service having the modified service behavior running on the first remote server satisfies a metric. In various embodiments, and in response to the verifying, the registered policy is transmitted to a second satellite agent located at a second remote server.

Abstract: There are provided systems and methods for intelligent clustering of account communities for account feature adjustment. A user may utilize an online account with the service provider to process transactions electronic. However, initially the account may be unverified or otherwise untrusted, and limits on electronic transaction processing may be imposed on the account. To provide intelligent feature adjustment, the service provider may utilize a machine learning technique to cluster verified accounts into communities based on their data representations. Thereafter, when a transaction by an unverified account violates a limit imposed on the unverified account, the service provider may process the unverified account using a machine learning model trained for account correlations to the community clusters in order to determine a corresponding community cluster of accounts and adjust a feature based on behaviors and traits of the verified accounts in the community cluster.

Abstract: Techniques are disclosed relating to using machine learning techniques to predict storage configurations for historical data. In some embodiments, a computer system stores representations of historical data according to a current set of storage parameters. The representations may include snapshots of historical data in a data repository at different points in time. The computer system may receive queries for historical data specifying points in time from which to retrieve the historical data. In some embodiments, the computer system responds to the queries using the stored representations and determines performance metrics for the responses. In some embodiments, the computer system trains a machine learning model using the performance metrics. Based on output of the trained model, the computer system updates the current set of storage parameters.

Abstract: Systems and methods for regulating service behavior include a system provider device where a policy is registered. The policy defines a modified service behavior for a service running one or more remote servers. In some embodiments, the registered policy is transmitted to a first satellite agent located at a first remote server. By way of example, and after transmitting the registered policy to the first satellite agent, data is received from the first satellite agent corresponding to the service having the modified service behavior running on the first remote server. Thereafter, the system provider may verify that the service having the modified service behavior running on the first remote server satisfies a metric. In various embodiments, and in response to the verifying, the registered policy is transmitted to a second satellite agent located at a second remote server.

Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for an end-to-end solution to auto-identifying features. In one embodiment, a novel architecture is presented that enables the identification of optimal features and feature processes for use by a machine learning model. The novel architecture introduces a feature orchestrator for managing, routing, and retrieving the data and features associated with analytical job request. The novel architecture also introduces a feature store designed to identify, rank, and store the features and data used in the analysis. To aid in identifying the optimal features and feature processes, a training system may also be included in the solution which can perform some of the training and scoring of the features.

Abstract: A mechanism is provided for secure sensitive private information dependent transactions. A query and a transaction token S associated with a current transaction between a SPI owner and the service provider is received. Particular SPI required is identified based on the query. A request for the particular SPI from the SPI owner is constructed thereby forming a constructed request. The constructed request is sent to one or more authorized devices associated with the SPI owner enrolled with the cognitive SPI broker. The particular SPI is received from a device of the SPI owner thereby forming received SPI. The received SPI is used complete the transaction. A notification is then sent to the SPI owner that the transaction has been completed.