Artificial intelligence-based methods and systems for generating account-related summaries

A server system, comprising:

• a memory configured to store instructions;
• a communication interface;
• and
• a processor in communication with the memory and the communication interface, the processor configured to execute the instructions stored in the memory and thereby cause the server system to perform, at least in part, to:
• access a rule generator file and historical transaction data corresponding to an account holder from a database associated with the server system;
• generate a set of transaction features based, at least in part, on the rule generator file;
• extract via a first machine learning model, a subset of relevant transaction features from the set of transaction features based, at least in part, on the historical transaction data;
• generate via second machine learning, a structured report template based, at least in part, on the subset of relevant transaction features, wherein the structured template report comprises a plurality of natural language sentences embedded with the subset of relevant transaction features;
• and
• generate an account-related summary for the account holder by substituting each of the subset of relevant transaction features embedded in the plurality of natural language sentences with a corresponding feature value from the historical transaction data.

A non-transitory computer-readable storage medium comprising computer-executable instructions that, when executed by at least a processor of a server system, cause the server system to perform a method comprising:

• accessing a rule generator file and historical transaction data corresponding to an account holder from a database associated with the server system;
• generating a set of transaction features based, at least in part, on the rule generator file;
• extracting via a first machine learning model, a subset of relevant transaction features from the set of transaction features based, at least in part, on the historical transaction data;
• generating via second machine learning, a structured report template based, at least in part, on the subset of relevant transaction features, wherein the structured template report comprises a plurality of natural language sentences embedded with the subset of relevant transaction features;
• and
• generating an account-related summary for the account holder by substituting each of the subset of relevant transaction features embedded in the plurality of natural language sentences with a corresponding feature value from the historical transaction data.