System, method and computer program for underwriting and processing of loans using machine learning

A non-transitory computer-readable medium storing computer-executable instructions that, when executed by one or more processors, cause:

• receiving data indicative of a loan application from a loan applicant;
• collecting, based on receiving the data indicative of the loan application, external data related to the loan applicant;
• pre-processing the external data to generate processed external data;
• conducting an automated feature engineering to develop a set of features;
• determining, based on the processed external data, an objective function by calculating values for a plurality of variables representing corresponding business objectives and assigning weights to the plurality of variables;
• creating an ensemble machine learning model from a plurality of machine learning models, wherein at least a portion of the plurality of machine learning models are one or more of trained or selected based on optimizing the objective function;
• varying one or more of the weights over time to account for changes in one or more business conditions;
• updating the ensemble machine learning model based on changes in the objective function corresponding to the varying of the one or more weights;
• determining, based on applying a localized linearity process to the ensemble machine learning model, one or more categories of reasons for rejection mapped to adverse action notices;
• and
• sending, to a computing device associated with the loan application and based on the mapping of the one or more categories to the adverse action notices, an indication of an adverse action notice.