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 automatically assessing project health and providing persona-based recommendations to improve the project health is provided. In some embodiments, the method includes identifying a set of metrics to be monitored for a project; calculating different levels of scores based on the set of metrics, each score being a health indicator of the project; analyzing the different levels of scores; identifying different levels of actions corresponding to the different levels of scores, an action being taken to improve an improvement area of the project; determining a user role of a user; identifying and providing a type of analytic view for the user based on the user role and analyzing the different levels of scores; and notifying the user to take the action corresponding to a level of scores based on the user role.