The Usage of Machine Learning Algorithms in Credit Evaluation Model

Credit scoring models are important tools for evaluating the credit status of individuals or businesses and play a significant role in the financial field. This study aims to suggest a prediction framework for credit evaluation model based on machine learning (ML) algorithms and explore the application principles and steps of combining credit scoring models, then provide an practical example to show the method for applying the model.In addition, the article also analyzes the issues that credit evaluation models should pay attention to in production practice at the end.

Authors

Publication Details

Journal
Frontiers in Business Economics and Management
Published
2024-11-07
DOI
https://doi.org/10.54097/8yyhbc96
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
Field-Weighted Citation Impact
0.00
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article

The Usage of Machine Learning Algorithms in Credit Evaluation Model

Xiaoliang Ji
Frontiers in Business Economics and Management
Financial Distress and Bankruptcy Prediction
article

The Usage of Machine Learning Algorithms in Credit Evaluation Model

Xiaoliang Ji
article en

Abstract

Credit scoring models are important tools for evaluating the credit status of individuals or businesses and play a significant role in the financial field. This study aims to suggest a prediction framework for credit evaluation model based on machine learning (ML) algorithms and explore the application principles and steps of combining credit scoring models, then provide an practical example to show the method for applying the model.In addition, the article also analyzes the issues that credit evaluation models should pay attention to in production practice at the end.

Frontiers in Business Economics and ManagementVol. 17(1)
Decent work and economic growth
Openalex Percentile: Top 67%
Financial Distress and Bankruptcy Prediction
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The Usage of Machine Learning Algorithms in Credit Evaluation Model — Xiaoliang Ji · Frontiers in Business Economics and Management (2024) | TGRS Research Map | TGRS