System and method of providing and recording personalized context-specific advice in the form of an artificial intelligence view of a hierarchical portfolio

A computer system for providing personalized, context-specific financial advice based on stored information for a hierarchical portfolio of assets owned by a user, the assets being organized based on a set of one or more hierarchical dimensions, the computer system comprising:

• a communication device connected to a network;
• a memory device storing executable instructions;
• and
• one or more processors coupled to the communication device and the memory device;
• wherein the executable instructions, when executed by the one or more processors, cause the computer system to perform operations comprising:
• receive, via the communication device, a first type of request, from a client device, regarding the hierarchical portfolio owned by the user;
• process the first type of request, including accessing the hierarchical portfolio information and compiling a data input package comprising user data associated with the user and financial data;
• process the data input package by machine learning algorithms running as trained machine learning models on one or more machine learning servers;
• generate, as an output of the machine learning models, individual suggestions for changing the structure or content of the hierarchical portfolio subject to constraints or conditions related to the user data;
• determine location data for the individual suggestions, the location data including structural positions of portfolio items within the hierarchical portfolio;
• assemble a first type of view of the hierarchical portfolio based on the first type of request, the first type of view including the individual suggestions and the location data for the individual suggestions;
• transmit the first type of view to the client device, via the communication device, for overlay of the first type of view upon a depiction of the hierarchical portfolio wherein the individual suggestions are displayed at locations corresponding to the portfolio items to which they refer;
• and
• transform the hierarchical portfolio to a revised hierarchical portfolio, create a snapshot of the hierarchical portfolio and a snapshot of the revised hierarchical portfolio, update the first type of view to include references to the snapshots, and record the updated first type of view on a private or public blockchain.

A non-transitory computer-readable medium for providing personalized, context-specific financial advice based on stored information for a hierarchical portfolio of assets owned by a user, the assets being organized based on a set of one or more hierarchical dimensions, the medium comprising executable instructions stored thereon that, when executed by one or more processors of a computer system, cause the computer system to:

• receive a first type of request, from a client device, regarding the hierarchical portfolio owned by the user;
• process the first type of request, including accessing the hierarchical portfolio information and compiling a data input package comprising user data associated with the user and financial data;
• process the data input package by machine learning algorithms running as trained machine learning models on one or more machine learning servers;
• generate, as an output of the machine learning models, individual suggestions for changing the structure or content of the hierarchical portfolio subject to constraints or conditions related to the user data;
• determine location data for the individual suggestions, the location data including structural positions of portfolio items within the hierarchical portfolio;
• assemble a first type of view of the hierarchical portfolio based on the first type of request, the first type of view including the individual suggestions and the location data for the individual suggestions;
• transmit the first type of view to the client device for overlay of the first type of view upon a depiction of the hierarchical portfolio wherein the individual suggestions are displayed at locations corresponding to the portfolio items to which they refer;
• and
• transform the hierarchical portfolio to a revised hierarchical portfolio, create a snapshot of the hierarchical portfolio and a snapshot of the revised hierarchical portfolio, update the first type of view to include references to the snapshots, and record the updated first type of view on a private or public blockchain.

A computer-implemented method of providing personalized, context-specific financial advice based on stored information for a hierarchical portfolio of assets owned by a user, the assets being organized based on a set of one or more hierarchical dimensions, the method comprising:

• receiving, at a computer system, a first type of request, from a client device, regarding the hierarchical portfolio owned by the user;
• processing, by the computer system, the first type of request, including determining structural positions of portfolio items within the hierarchical portfolio;
• enriching, by the computer system, the hierarchical portfolio with additional data attributes and values;
• processing the hierarchical portfolio by machine learning algorithms running as trained machine learning models on one or more machine learning servers;
• generating, as an output of the machine learning models, individual artificial intelligence suggestions for changing the structure or content of the hierarchical portfolio to optimize the portfolio;
• determining, by the computer system, location data for the individual Al suggestions, including mapping the individual Al suggestions to specific structural positions of portfolio items in the hierarchical portfolio;
• assembling, by the computer system, a first type of view of the hierarchical portfolio based on the first type of request, the first type of view including the individual Al suggestions and the location data for the individual Al suggestions;
• transmitting, from the computer system, the first type of view to the client device for overlay of the first type of view upon a depiction of the hierarchical portfolio wherein the individual Al suggestions are mapped to locations corresponding to the portfolio items to which they refer;
• and
• transforming, by the computer system, the hierarchical portfolio to a revised hierarchical portfolio, creating a snapshot of the hierarchical portfolio and a snapshot of the revised hierarchical portfolio, updating the first type of view to include references to the snapshots, and recording the updated first type of view on a private or public blockchain.