Patent ID: 11972338
Assignee: ZESTFINANCE, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 14:
15. One or more non-transitory computer storage media storing instructions that, when executed by one or more processors, cause the one or more processors to:
train a machine learning model by applying a subset of credit data as training input to the machine learning model, thereby providing a first trained machine learning, wherein the subset of the credit data is selected from a credit data sample based on sampling the credit data sample according to first user input data characterizing a product or service and the credit data sample comprises third party data;
present a user interface comprising an indication of a contribution to the first trained machine learning model of each of a plurality of features;
re-train the first trained machine learning model in response to a received selection via the user interface of one of the plurality of features for removal and by applying at least second user input data as training input to the first trained machine learning model, thereby generating a second trained machine learning model, wherein the second user input data is obtained based on sampling criteria and comprises first party data comprising credit reports or applications of actual customers associated with the product or service;
ensemble the first and the second trained machine learning models to thereby combine the first and second trained machine learning models into a refined version of the first machine learning model;
deploy the refined version of the first trained machine learning model in a computing environment as a web service having an associated application programming interface (API) endpoint; and
execute the refined version of the first machine learning model to generate and return credit scores or decisions with respect to the product or service based on input client data received via the API endpoint from a loan origination system.