System and framework for dynamic regulatory change management

A computer program product for dynamic regulatory change management for an enterprise, the computer program product comprising at least one non-transitory computer readable medium comprising computer readable instructions, the instructions comprising instructions for:

• continuously monitoring a plurality of regulatory data sources to identify regulatory change documentation;
• scanning descriptive fields within each identified regulatory change documentation for coverage area indicator terms and phrases;
• causing a machine learning system to determine an impact value of each identified regulatory change documentation for one or more regulatory inventories of the enterprise by analyzing the coverage area indicator terms and phrases within each regulatory change documentation;
• in response to determining that an impact value of a first regulatory change documentation for a first regulatory inventory meets or exceeds a predetermined threshold, causing a user dashboard associated with the first regulatory inventory to display a regulatory change alert for the first regulatory change documentation;
• or
• in response to determining that the impact value of the first regulatory change documentation for the first regulatory inventory is below the predetermined threshold, tagging the first regulatory change documentation as not being materially relevant to the first regulatory inventory,
• wherein the impact values are determined and dynamically updated based on sub-impact values of (1) individual coverage area indicator terms and phrases, (2) proximity levels between two or more specific coverage area indicator terms and phrases, (3) grammatical relationships between two or more specific coverage area indicator terms and phrases, and (4) time-based information, wherein the time-based information comprises at least a timing that a regulatory change is announced, a timing that the regulatory change documentation was received, a timing of when one or more portions of the regulatory change go into effect, and a timing of when one or more compliance standards need to be implemented in response to the regulatory change, which are determined based on a machine learning analysis of a continuously updated historical regulatory change database comprising previously received regulatory change documentation and user-verified determinations as to whether the previously received regulatory change documentation was materially relevant to one or more regulatory inventories.

A computer implemented method for dynamic regulatory change management for an enterprise, said computer implemented method comprising:

• providing a computing system comprising a computer processing device and a non-transitory computer readable medium, where the computer readable medium comprises configured computer program instruction code, such that when said instruction code is operated by said computer processing device, said computer processing device performs the following operations:
• continuously monitoring a plurality of regulatory data sources to identify regulatory change documentation;
• scanning descriptive fields within each identified regulatory change documentation for coverage area indicator terms and phrases;
• causing a machine learning system to determine an impact value of each identified regulatory change documentation for one or more regulatory inventories of the enterprise by analyzing the coverage area indicator terms and phrases within each regulatory change documentation;
• in response to determining that an impact value of a first regulatory change documentation for a first regulatory inventory meets or exceeds a predetermined threshold, causing a user dashboard associated with the first regulatory inventory to display a regulatory change alert for the first regulatory change documentation;
• or
• in response to determining that the impact value of the first regulatory change documentation for the first regulatory inventory is below the predetermined threshold, tagging the first regulatory change documentation as not being materially relevant to the first regulatory inventory,
• wherein the impact values are determined and dynamically updated based on sub-impact values of (1) individual coverage area indicator terms and phrases, (2) proximity levels between two or more specific coverage area indicator terms and phrases, (3) grammatical relationships between two or more specific coverage area indicator terms and phrases, and (4) time-based information, wherein the time-based information comprises at least a timing that a regulatory change is announced, a timing that the regulatory change documentation was received, a timing of when one or more portions of the regulatory change go into effect, and a timing of when one or more compliance standards need to be implemented in response to the regulatory change, which are determined based on a machine learning analysis of a continuously updated historical regulatory change database comprising previously received regulatory change documentation and user-verified determinations as to whether the previously received regulatory change documentation was materially relevant to one or more regulatory inventories.