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基于校园消费数据分析大学生网络借贷行为:借款倾向、消费变化与违约风险
引用本文:张成洪,肖帅勇,陆天,卢向华,黄丽华.基于校园消费数据分析大学生网络借贷行为:借款倾向、消费变化与违约风险[J].系统工程理论与实践,2021(3):574-586.
作者姓名:张成洪  肖帅勇  陆天  卢向华  黄丽华
作者单位:复旦大学管理学院
基金项目:国家自然科学基金(71971067,91546104,71490721,91746302)。
摘    要:“校园贷”向面临资金困难的大学生提供了缓解困难的途径,但不正规的网络借贷或缺乏约束的学生借贷行为也引发了诸多问题.该研究结合校园“一卡通”数据与学生网贷数据对大学生校园消费与网贷行为的关系展开了实证探究.结果表明:1)借款倾向高的学生校园消费金额和频率更低且更不规律.2)大部分学生在获得借款后校园消费显著提升.3)违约风险高的学生总消费额更不规律,早餐消费频率更低,且获得借款后校园消费无明显变化.本研究增进了对大学生网贷借款倾向、资金用途和违约风险全过程行为的理解,为高校管理者基于校园“大数据”识别资金困难的学生从而采取引导和非债务性帮扶提供了思路.本文在“校园贷”监管方面也具有政策参考价值.

关 键 词:校园消费  网络借贷  "校园贷"  借款倾向  违约风险  大数据

Campus consumptions and microloan behaviors--Exploring college students'loan tendency,loan usage,and repayment performance based on campus consumption data
ZHANG Chenghong,XIAO Shuaiyong,LU Tian,LU Xianghua,HUANG Lihua.Campus consumptions and microloan behaviors--Exploring college students'loan tendency,loan usage,and repayment performance based on campus consumption data[J].Systems Engineering —Theory & Practice,2021(3):574-586.
Authors:ZHANG Chenghong  XIAO Shuaiyong  LU Tian  LU Xianghua  HUANG Lihua
Institution:(School of Management,Fudan University,Shanghai 200433,China)
Abstract:Microloans for college students help them to deal with occasional economic difficulties.However,many problems have raised because of the illegal microloan business or less controlled loan behaviors of students.With a unique data set that combines students'campus"e-card"consumptions and their microloan behaviors,we empirically explored the relations between them.The results indicate that:1)Students who consume less in terms of amount and frequency with higher fluctuations have stronger loan tendency.2)Majority of the students are observed to have significantly enhanced their campus consumptions after obtaining funds from microloans.3)Students who perform higher fluctuations in consumption amounts and have fewer times of breakfast are more likely to default in microloans.Our research contributes to a deep understanding of loan tendency,loan usage and credit risk of college students.The findings suggest college administrators use campus"big data"for identifying students with economic difficulties,thus offering timely guidance and financial aids.The present study also yields insightful suggestions for the regulation of microloans toward college students.
Keywords:campus consumptions  microloan  microloan for college students  loan tendency  financial credit risk  big data
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