Abstract: Embodiments provide systems and methods that update analytical models which are changing over time. Upon receipt of a model creation request, a synchronization is performed to receive updated metadata reflecting a current state of a model. Where such updating indicates a change in status (e.g., privacy) of the model metadata, the user is prompted with a sensitive metadata field, and an empty context metadata field. The user must fill in the context metadata field (e.g., with an appropriate ID) thereby providing authorization to access data of the model. Then, a model view including sensitive information can be passed to the user. Absent successfully inputting the context metadata field, error message(s) are returned to the user, and the model view will not be passed. Embodiments may find particular use in efficiently updating analytical models to ensure their continuing compliance with evolving privacy regulation (e.g., ongoing revision and/or interpretation of GDPR language).