Genpact Usa, Inc.

Genpact Luxembourg S.à R.l. II

Kathryn Stein

Lavi Sharma

Vivek Saxena

Vikram Jha

Sachin Gupta

Anand Jhaveri

Rajesh Sanghvi

Atul Kumar

Garima Kapoor

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. The method additionally includes generating a nudge quotient for the data-to-action loop based on the zero time-to-insight quotient, the insight-to-nudge quotient, and the D2A PMF.

Method and system for driving zero time to insight and nudge based action in data-driven decision making

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.

Method and system for measuring, monitoring and enhancing user experience for personas across their end to end journey

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.

System and method for machine learning based detection, reporting and correction of exceptions and variances impacting financial data

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New York, NY, United States of America

Kathryn Stein