bookmark our website
Favorites | Contributions | Phone turned on
QR code
Mobile client opens this article

Research on Prediction of Personal Credit Default Based on XGBoost

Abstract: With the rapid development of the Internet economy, the scale of personal credit has exploded in recent years. Credit risk control has always been a hot issue for financial institutions. This paper studies the application of ensemble learning algorithm XGBoost to the prediction of personal credit default. By analyzing the existing data, and using the XGBoost algorithm to build a personal credit default prediction model. Experimental results show that XGBoost performs better than logistic regression and random forest algorithms. By using the XGBoost algorithm to measure the importance of features, it helps to quickly and effectively judge personal credit risk.
[Author] : College of Computer Engineering, Hubei University of Arts and Science
[Classification number]: TP181; F832.4

Mobile HowNet App
Chinese Journal Full-text Database Previous 1
1 Tan Chao; Sun Benzhi; Wang Jining ;; Research on Overdue Behavior in P2P Network Lending Platform [J]; Finance and Accounting Newsletter; 2015-05
China Doctoral Dissertations Full-text Database Previous 1
1 Zhao Jingxian; Research on Credit Risk Assessment Method Based on Decision Tree [D]; Tianjin University; 2009
China Papers Previous 1
1 Gao Jian; Research on Nuclear-Based P2P Credit Risk Assessment Model [D]; Huazhong University of Science and Technology; 2013
[Co-cited literature]
China Doctoral Dissertations Full-text Database First 5
1 Zhu You; Research on Credit Risk Evaluation of Small and Medium-sized Enterprises in the Environment of Supply Chain Finance [D]; Hunan University; 2017
2 Zhang Wanjun; Research on personal credit risk assessment model based on big data [D]; University of International Business and Economics; 2016
3 Wang Ying; Research on Asset Securitization Financing Model of Cultural and Creative Industries [D]; Beijing Institute of Technology; 2014
4 Lai Yongwen; Research on Farmers' Credit Evaluation System [D]; Fujian Agriculture and Forestry University; 2012
5 Zhang Chuanxin; Research on Credit Risk Measurement of Chinese Commercial Banks [D]; Suzhou University; 2012
China Papers First 6
1 Jin Jingsong; A Study on the Impact of P2P Loan Prepayment on Investment Yield [D]; Nanjing University; 2016
2 Sun Bin; Comparison and Analysis of P2P Network Lending and Traditional Bank Loan Mechanism [D]; Huazhong Normal University; 2016
3 Sun Bo; Research on the Risk of China's P2P Network Lending Industry [D]; East China University of Science and Technology; 2016
4 Gao Jian; Research on Credit Risk Management of P2P Network Credit [D]; East China Normal University; 2015
5 Zhao Jiqi; Personal credit risk assessment of P2P online lending [D]; Beijing Institute of Technology; 2015
6 Ouyang Jinglun; Research on Risk Management of China's P2P Online Lending Platform [D]; Changsha University of Science and Technology; 2015
[Secondary reference]
Chinese Journal Full-text Database First 4
1 Wang Ziwei; Yuan Zhonghua; Zhong Xin ;; Research on China 's P2P Network Microfinance Operation Model——A Case Study Based on "Paipai Loan" and "Yinong Loan" [J]; New Finance; 2012-02
2 Niu Ming ;; P2P Credit Model of "Grassroots" Finance [J]; Finance Theory and Practice; 2012-02
3 You Ruizhang; Zhang Xiaoxia ;; A Comparative Analysis of Chinese and Foreign P2P Online Lending——Concurrently Enlightenment to China [J]; Finance Development Review; 2010-03
4 Xin Xian ;; Discussion on P2P operation mode [J]; Shopping Mall Modernization; 2009-21
China Doctoral Dissertations Full-text Database First 3
1 Feng Zheng; Research on the Application of Data Mining in Financial Early Warning [D]; Tianjin University; 2007
2 Huang Fu Xiuyan; Research on Identification and Evaluation of Credit Risk of Chinese Commercial Banks [D]; Xiamen University; 2006
3 Wang Zhenmin; Loan Risk Analysis of Chinese Commercial Banks [D]; Tianjin University; 2005
China Papers First 2
1 Zhang Na; Research on P2P Internet Credit Behavior [D]; Southwestern University of Finance and Economics; 2011
2 Chen Qingshan; Research on Personal Credit Scoring Model Based on Data Mining [D]; Xiamen University; 2008
【similar article】
Chinese Journal Full-text Database Before 10
1 Ye Qianyi; Rao Hong; Ji Mingshu ;; Forecast of Commercial Sales Based on Xgboost [J]; Journal of Nanchang University (Science Edition); 2017-03
2 Zhu Ming; Wang Chunmei; Gao Xiang; Wang Jing ;; Application of XGBoost in Coordination Situation Prediction of Satellite Networks [J]; Small Micro Computer System; 2019-12
3 Yang Can ;; Extraction of Road Networks in Remote Sensing Images Based on XGBoost [J]; Microcomputer and Applications; 2017-24
4 Wang Hong'ai ; Research on Railway Passenger Refund Rate Forecast Based on XGBoost Algorithm [J]; Journal of the China Railway Society; 2019-12
5 Sun Yifei; Yuan Decheng; Wang Jianlong; Bai Yang ;; Prediction of wine quality based on XGBoost method [J]; Journal of Shenyang University of Chemical Technology; 2018-04
6 Li Xiaofeng; Ma Jing; Li Chi; Zhu Hengmin ;; Research on E-commerce Product Name Recognition Algorithm Based on XGBoost Model [J]; Data Analysis and Knowledge Discovery; 2019-07
7 Yu Gao ;; Design of Case Typing System Based on XGBoost Algorithm [J]; China Digital Medicine; 2018-03
8 Zhang Yang; Yao Yuangang ;; Research on Network Intrusion Detection Based on Xgboost Algorithm [J]; Information Network Security; 2018-09
9 Qu Wenlong; Li Yiyi; Zhou Lei ;; Application of XGBoost Algorithm in Prediction of Diabetes Glucose [J]; Journal of Jilin Normal University (Natural Science Edition); 2019-04
10 Su Tianpei ;; Prediction of Diabetes Risk Based on XGBoost [J]; Science & Technology; 2019-02
China Conference Papers Full-text Database Previous 1
1 Wang Yi; Tao Yi ;; Identify different species of dolphins based on Xgboost method [A]; [C]; 2019
China Papers First 2
1 Lian Keqiang; Research and Analysis of Integrated Tree Algorithm Based on Boosting [D]; China University of Geosciences (Beijing); 2018
2 Yue Shibin; Research, Design and Implementation of Intelligent Supermarket Management System Based on RFID and Machine Learning [D]; Guangxi University; 2017