Research on Application of Gradient Boosting Method in Credit Risk Assessment
This paper develops an advanced machine learning model to estimate credit risk by predicting the likelihood of loan defaults.This model utilizes different datasets and evaluates numerous applicant factors such as annual income,credit history,and age through gradient boosting methods.It can provide robust and stable prediction results and adapt to constantly changing consumer behavior,greatly improving the ability of financial institutions to make wise decisions in the loan process,thereby minimizing financial risks and optimizing risk management strategies.
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