Method and system for artificial intelligence based enhancement of sale processes

A computing apparatus for automatically formatting communications into a structured format, the computing apparatus comprising:

• a processor;
• a memory;
• a display;
• and
• a communication interface coupled to each of the processor, the memory, and the display,
• wherein the processor is configured to:
• receive, via the communication interface and a front-end application, a communication that relates to a request for a price quote for at least one equity derivative product, wherein the front-end application contains logic for recording and logging a user action associated with the request for the price quote;
• transmit the communication from the front-end application to a natural-language-processing (NLP) machine-learning (ML) model;
• mediate, via a central parsing service, the transmitting of the communication, wherein the mediating includes recording and logging information during the transmitting of the communication, wherein the central parsing service includes natural language understanding (NLU) components for template request generation, and wherein the central parsing service contains logic for transforming the communication into a shorthand template;
• extract, via the NLP-ML model from the shorthand template, attributes of the requested price quote for the at least one equity derivative product;
• perform, via the NLP-ML model, at least one verification operation on the extracted attributes;
• transmit the extracted attributes to the central parsing service;
• generate, via the central parsing service, a template request based on the extracted attributes, wherein the template request has a predetermined format for each of the at least one equity derivative product, and wherein the central parsing service automatically fills in for missing attributes during the generating of the template request;
• transmit the template request from the central parsing service to the front-end application;
• simplify, via the front-end application, the template request by applying parameters to the request for the price quote;
• display, by the display via a graphical user interface (GUI) of the front-end application, each simplified template request for review by a user, wherein the GUI includes an input mechanism for at least one from among accepting and modifying each template request;
• transmit information received by the input mechanism to a feedback application programming interface (API) for implementing improvements for automatically formatting communications into a structured format;
• transmit, via the communication interface, each reviewed template request to a pricing system;
• receive, via the communication interface and the front-end application from the pricing system, a price quote for each of the at least one equity derivative product;
• and
• display, by the display via the GUI, the price quote.

A non-transitory computer readable storage medium storing instructions for automatically formatting communications into a structured format, the storage medium comprising executable code which, when executed by a processor, causes the processor to:

• receive, via a front-end application, a communication that relates to a request for a price quote for at least one equity derivative product, wherein the front-end application contains logic for recording and logging a user action associated with the request for the price quote;
• transmit the communication from the front-end application to a natural-language-processing (NLP) machine-learning (ML) model;
• mediate, via a central parsing service, the transmitting of the communication, wherein the mediating includes recording and logging information during the transmitting of the communication, wherein the central parsing service includes natural language understanding (NLU) components for template request generation, and wherein the central parsing service contains logic for transforming the communication into a shorthand template;
• extract, via the NLP-ML model from the communication, attributes of the requested price quote for the at least one equity derivative product;
• perform, via the NLP-ML model, at least one verification operation on the extracted attributes;
• transmit the extracted attributes to the central parsing service;
• generate, via the central parsing service, a template request based on the extracted attributes, wherein the template request has a predetermined format for each of the at least one equity derivative product, and wherein the central parsing service automatically fills in for missing attributes during the generating of the template request;
• transmit the template request from the central parsing service to the front-end application;
• simplify, via the front-end application, the template request by applying parameters to the request for the price quote;
• display, by the display via a graphical user interface (GUI) of the front-end application, each simplified template request for review by a user, wherein the GUI includes an input mechanism for at least one from among accepting and modifying each template request;
• transmit each reviewed template request to a pricing system;
• transmit information received by the input mechanism to a feedback application programming interface (API) for implementing improvements for automatically formatting communications into a structured format;
• receive, via the front-end application from the pricing system, a price quote for each of the at least one equity derivative product;
• and
• display, by the display via the GUI, the price quote.