CPC G06Q 40/03 (2023.01) [G06F 18/24323 (2023.01); G06N 20/00 (2019.01)] | 20 Claims |
1. A method of automated loan application processing using machine learning credit modeling that maximizes predictive accuracy and outcome parity, the method implemented by a modelling system and comprising:
training a first tree-based machine learning model to predict loan repayment probability;
determining an accuracy metric and a fairness metric of the first tree-based machine learning model, the fairness being associated with one or more classes of individuals;
training a second different tree-based machine learning model based on the accuracy and the fairness metrics of the first tree-based machine learning model;
deploying a gradient-boosted machine learning model generated by combining the first and second tree-based machine learning models;
applying the gradient-boosted machine learning model to application data for a loan extracted from a received credit application to generate evaluation data comprising at least a score corresponding to a likelihood that the loan will be repaid; and
automatically providing an electronic lending decision in response to the received credit application, wherein the lending decision is based on the score in the evaluation data.
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