Machine learning based authentication and real time data access with disparate communication networks

A system comprising:

• at least one processor;
• and
• a memory storing instructions that, when executed by the at least one processor, cause the system to perform operations comprising:
• obtaining formatted account data maintained by an entity and associated with an account of a user;
• accessing in real time account data associated with the account from an institution after the entity has facilitated authentication of the user with the institution;
• and
• based on a machine learning model, generating synchronized data that reflects selection of a data field of a data type from the formatted account data maintained by the entity or a data field of the data type from the account data from the institution, wherein the machine learning model is a large language model, the generating synchronized data comprising:
• generating a first example of training data comprising i) account data from an institution including a data field associated with a first data type and account data from formatted data including a data field associated with the first data type and ii) synchronized data including the data field in the account data from the institution and excluding the data field in the account data from the formatted data,
• generating a second example of training data comprising i) account data from an institution including a data field associated with a second data type and account data from formatted data including a data field associated with the second data type and ii) synchronized data including the data field in the account data from the formatted data and excluding the data field in the account data from the institution, and
• fine tuning the large language model based on training data comprising the first example of training data and the second example of training data.

A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations comprising:

• obtaining formatted account data maintained by an entity and associated with an account of a user;
• accessing in real time account data associated with the account from an institution after the entity has facilitated authentication of the user with the institution;
• and
• based on a machine learning model, generating synchronized data that reflects selection of a data field of a data type from the formatted account data maintained by the entity or a data field of the data type from the account data from the institution, wherein the machine learning model is a large language model, the generating synchronized data comprising:
• generating a first example of training data comprising i) account data from an institution including a data field associated with a first data type and account data from formatted data including a data field associated with the first data type and ii) synchronized data including the data field in the account data from the institution and excluding the data field in the account data from the formatted data,
• generating a second example of training data comprising i) account data from an institution including a data field associated with a second data type and account data from formatted data including a data field associated with the second data type and ii) synchronized data including the data field in the account data from the formatted data and excluding the data field in the account data from the institution, and
• fine tuning the large language model based on training data comprising the first example of training data and the second example of training data.