Modifying word structure based on reading comprehension levels using machine learning

A method comprising:

• determining, by a processor, a first reading comprehension level for a set of financial literacy content, the set of financial literacy content comprising a plurality of sentences;
• inputting, by the processor, the plurality of sentences into a trained machine learning model;
• receiving, by the processor, one or more updates to the plurality of sentences from the trained machine learning model;
• generating, by the processor, an updated set of financial literacy content based on the one or more updates to the plurality of sentences, the one or more updates having a second reading comprehension level that is different than the first reading comprehension level;
• and
• outputting, by the processor, the updated set of financial literacy content as a graphical user interface to a user device associated with a user account.

A non-transitory computer-readable medium comprising program code that is executable by a processor for causing the processor to:

• determine a first reading comprehension level for a set of financial literacy content, the set of financial literacy content comprising a plurality of sentences;
• input the plurality of sentences into a trained machine learning model;
• receive, from the trained machine learning model, one or more updates to the plurality of sentences;
• generate an updated set of financial literacy content based on the one or more updates to the plurality of sentences, the one or more updates having a second reading comprehension level that is different than the first reading comprehension level;
• and
• output, to a user device associated with a user account, the updated set of financial literacy content as a graphical user interface.