Method and system for automated request-for-quote (rfq) services with automated margin optimization

A computer system comprising:

• one or more processor units, and a memory device comprising memory space with computer-executable instructions;
• a data preparation module comprising computer-executable instructions configured to aggregate raw data and normalize the raw data to generate at least one structured dataset;
• a pricing module comprising computer-executable instructions configured to determine a first set of features from the at least one structured dataset, the pricing module applying a machine learning architecture to train a set of predictive pricing models to generate an indication in electronic form representing at least one optimal pricing of at least one financial instrument;
• a margin optimization module comprising computer-executable instructions configured to determine a second set of features from the at least one structured dataset, the margin optimization module applying the architecture machine learning architecture to train a set of predictive models to minimize a transaction margin for the at least one financial instrument based on one of the at least one of the second set of features and at least one optimal pricing of at least one financial instrument;
• and
• wherein the one or more processor units, and the memory device are configured to write an indication to the memory space to at least communicate the at least one optimal pricing and the transaction margin of the at least one financial instrument via a communication network and/or generate a visual indicator related to and based at least in part on the generated indication on a graphical user interface.