Parsing data structure ontologies in database environments to identify, organize and index data files

A system for parsing data structure ontologies in a database environment to identify, organize and index data files, the system comprising:

• a processor;
• a non-transitory memory operably connected to the processor;
• a targeted actions application stored in the memory and including executable instructions that, when executed, causes the processor to:
• assemble data associated with financial accounts of a user, the data being stored in a database in the memory and including account transactions, fees charged and benefits received;
• identify rules associated with the user financial accounts stored in the memory, the rules including all charges, benefits and promotions that apply to the user financial accounts;
• use artificial intelligence machine learning to analyze the data using a pattern recognition algorithm and detect patterns in the account transactions;
• apply the rules to at least one of the detected patterns to generate a targeted action that the user can take to improve a financial performance of at least one of the user financial accounts;
• assign ranks to the targeted actions and select a one of the targeted actions having a highest rank;
• generate a message including the selected targeted action;
• and
• send the message to a user device of the user.

A method for parsing data structure ontologies in a database environment to identify, organize and index data files, the method comprising steps of:

• providing a processor;
• providing a non-transitory memory operably connected to the processor;
• providing a targeted actions application stored in the memory and including executable instructions that executed by the processor causing the processor to:
• assemble data associated with financial accounts of a user, the data being stored in a database in the memory and including account transactions, fees charged and benefits received;
• identify rules associated with the user financial accounts stored in the memory, the rules including all charges, benefits and promotions that apply to the user financial accounts;
• use artificial intelligence machine learning to analyze the data using a pattern recognition algorithm and detect patterns in the account transactions;
• apply the rules to the detected patterns to generate a targeted actions that the user can take to improve a financial performance of the user financial accounts;
• assign ranks to the targeted actions and select a one of the targeted actions having a highest rank;
• generate a message including the selected targeted action;
• and
• send the message to a user device of the user.