Abstract: An electronic platform to measure a maturity or level of an entity in view of regulatory and business risks relating to regulatory compliance. The methods and systems can collect various data (e.g., regulatory agency reports, regulatory agency warning letters (e.g. FDA warning letters), internal and vendor company audit results, fines and settlement information, country business risks, regulatory agency product recalls, etc.) from various different data sources. The collected information is analyzed using machine learning techniques to determine a risk compliance level or score for one or more of an entity's companies, functions, control types, and locations arising from regulatory audit non-conformances. The risk compliance scores can be used to generate a risk prediction and identify one or more actions to be taken by the entity to improve or increase an associated compliance level.

Abstract: An electronic platform to measure a maturity or level of an entity in view of regulatory and business risks relating to regulatory compliance. The methods and systems can collect various data (e.g., regulatory agency reports, regulatory agency warning letters (e.g. FDA warning letters), internal and vendor company audit results, fines and settlement information, country business risks, regulatory agency product recalls, etc.) from various different data sources. The collected information is analyzed using machine learning techniques to determine a risk compliance level or score for one or more of an entity's companies, functions, control types, and locations arising from regulatory audit non-conformances. The risk compliance scores can be used to generate a risk prediction and identify one or more actions to be taken by the entity to improve or increase an associated compliance level.