Abstract: A method and system are provided to infer and use machine learning algorithms that is applied to financial data and also to determine: (i) compliance with the applied algorithms, and (ii) whether any exceptions to and/or variations from the algorithms are within an organization's norms. A method includes: receiving financial data; applying a set of dynamic or interdependent algorithms to the received financial data to obtain a set of outcomes; and using a machine learning classifier to classify the outcomes as: (i) algorithm compliant, (ii) potentially algorithm non-compliant, or (iii) algorithm non-compliant. Additionally, the method includes generating controllership persona based actionable triggers, which on acceptance corrects the anomalies in financial data, enabling the method and system to perform as a comprehensive, contextual, consistent & machine learning powered, persona based real time controllership engine leading to reduced misstatements in reported financial data.

Abstract: Zero-touch monitoring devices and systems are disclosed that are configured with hardware to perform a process-mining on an event-to-entry process associated with an organization to collect data information associated with the process, determine an input-related zero-touch quotient for the event-to-entry process based on the data information, determine a rule-related zero-touch quotient for the event-to-entry process based on the data information, determine a zero-touch potential predictive accounting factor (ZTP PAF) value for the event-to-entry process, and generate a zero-touch processing quotient for the event-to-entry process based on the input-related zero-touch quotient, the rule-related zero-touch quotient, and the ZTP PAF value. The ZTP PAF value quantifies an incremental zero-touch potential for the event-to-entry process and corresponding attributes.

Abstract: A method for driving zero time-to-insight and effectiveness of insight-to-nudge in a decision-making process. The method includes identifying a scope associated with a data-to-action loop in the decision-making process. The method further includes determining, by a zero time-to-insight engine, a zero time-to-insight quotient for a data-to-insight loop included in the data-to-action loop. The method additionally includes determining, by an insight-to-nudge engine, an insight-to-nudge quotient for an insight-to-action loop included in the data-to-action loop. The method additionally includes determining, by a predictive model factor component, a data-to-action prediction model factor (D2A PMF) for the data-to-action loop, where the D2A PMF quantifies an incremental zero time-to-insight potential for the data-to-action loop and corresponding attributes.

Abstract: A method for assessing user experience includes determining one or more experience journey maps, identifying personas included in the one or more experience journey maps, and collecting user experience related data from the personas included in the one or more experience journey maps. The method further includes identifying user experience gaps based on an analysis performed on the experience related data collected, and providing a graphical representation that highlights the user experience gaps. The method also includes generating recommendations for execution to mitigate the user experience gaps highlighted in the graphical representation, monitoring and tracking a progress of the executed recommendations, and performing automated monitoring and offset metric tracking of targeted experience-related input metrics used to gauge a performance of the executed recommendations.

Abstract: A method for assessing user experience includes determining one or more experience journey maps, identifying personas included in the one or more experience journey maps, and collecting user experience related data from the personas included in the one or more experience journey maps. The method further includes identifying user experience gaps based on an analysis performed on the experience related data collected, and providing a graphical representation that highlights the user experience gaps. The method also includes generating recommendations for execution to mitigate the user experience gaps highlighted in the graphical representation, monitoring and tracking a progress of the executed recommendations, and performing automated monitoring and offset metric tracking of targeted experience-related input metrics used to gauge a performance of the executed recommendations.

Abstract: A method and system are provided to infer and use machine learning algorithms that is applied to financial data and also to determine: (i) compliance with the applied algorithms, and (ii) whether any exceptions to and/or variations from the algorithms are within an organization's norms. A method includes: receiving financial data; applying a set of dynamic or interdependent algorithms to the received financial data to obtain a set of outcomes; and using a machine learning classifier to classify the outcomes as: (i) algorithm compliant, (ii) potentially algorithm non-compliant, or (iii) algorithm non-compliant. Additionally, the method includes generating controllership persona based actionable triggers, which on acceptance corrects the anomalies in financial data, enabling the method and system to perform as a comprehensive, contextual, consistent & machine learning powered, persona based real time controllership engine leading to reduced misstatements in reported financial data.

Abstract: A method for assessing user experience includes determining one or more experience journey maps, identifying personas included in the one or more experience journey maps, and collecting user experience related data from the personas included in the one or more experience journey maps. The method further includes identifying user experience gaps based on an analysis performed on the experience related data collected, and providing a graphical representation that highlights the user experience gaps. The method also includes generating recommendations for execution to mitigate the user experience gaps highlighted in the graphical representation, monitoring and tracking a progress of the executed recommendations, and performing automated monitoring and offset metric tracking of targeted experience-related input metrics used to gauge a performance of the executed recommendations.

Abstract: CD16A binding proteins useful for the reduction of a deleterious immune response are described. In one aspect, humanized anti-CD16A antibodies, optionally lacking effector function, are used for treatment of immune disorders such as idiopathic thrombocytopenic purpura and autoimmune hemolytic anemia.