Abstract: A system and method for video authentication may apply machine learning to analyze whether a person's face captured by live video matches a face in a photo ID captured by live video and to analyze other features based on a video session with the person. For example, machine learning may be applied to analyze a set of features indicating whether the person is a real, live person (as opposed to a photo image held up over the person's face in the video, etc.). Finally, the machine learning may be applied to analyze a set of features to determine whether a lower probability prediction that the person's face captured by live video matches a face in a photo ID captured by live video should be either pass authentication (due to one or more features/circumstances mitigating the lower probability) or fail authentication (due to one or more features not mitigating the lower probability). In such a situation, the set of features may indicate that mitigating factors/conditions exist that can offset the lower probability.

Abstract: The disclosed system and method can improve a selection process, such as selecting winners in a contest or request for proposal, by narrowing the submissions to a reasonable number of top submissions that can be more meaningfully considered by a decision making body. By using machine learning during the selection process, human biases may be avoided, processing speed is significantly increased, accuracy of review and scoring is improved, and auditability of results is possible. The disclosed system and method improve the process of selecting one or more submissions by summarizing the submissions into a minimal number of words that can be substituted for the full text of the submission in downstream processes of the selection process. Fewer words used in the downstream processes can improve the speed and efficiency of the downstream processes.

Abstract: An Artificial Intelligence (AI) based payments processing system analyzes data from a user's purchase invoice to identify a combination of payment modes to be used to pay for the user's purchases thereby maximizing the savings to the user while accounting for the user preferences. A savings oriented model including a mix and match model and a dynamic decision tree scoring model generates a savings based best offer suggesting the payment modes to be used by analyzing the user's purchases based on the offers associated with the purchased products. A user behavior model generates a user behavior based best offer by further accounting for user preferences. Based on the user's autopay settings, the payments processing system may automatically initiate payment for the user's purchases or may display the best offers to the user before initiating the payments.

Abstract: The disclosed system and method can improve a selection process, such as selecting winners in a contest or request for proposal, by narrowing the submissions to a reasonable number of top submissions that can be more meaningfully considered by a decision making body. By using machine learning during the selection process, human biases may be avoided, processing speed is significantly increased, accuracy of review and scoring is improved, and auditability of results is possible. The disclosed system and method improve the process of selecting one or more submissions by summarizing the submissions into a minimal number of words that can be substituted for the full text of the submission in downstream processes of the selection process. Fewer words used in the downstream processes can improve the speed and efficiency of the downstream processes.

Abstract: An intelligent product requirement configurator is a tool for assisting the implementation process of application platforms by generating a recommended configuration data set describing recommended configuration settings for a selected application platform. The tool acts as a repository for capturing requirements such as banking market practice requirements, regulatory requirements, and bank specific requirements. The tool further converts the requirements into profile data and business rules that are used to configure the application platform.

Abstract: An intelligent product requirement configurator is a tool for assisting the implementation process of application platforms by generating a recommended configuration data set describing recommended configuration settings for a selected application platform. The tool acts as a repository for capturing requirements such as banking market practice requirements, regulatory requirements, and bank specific requirements. The tool further converts the requirements into profile data and business rules that are used to configure the application platform.