2015年中国个人征信行业正式开启市场化进程，芝麻信用等互联网征信模式不断受到社会关注。美国金融科技公司ZestFinance将大数据分析和机器学习技术应用于个人征信领域，引起了国内互联网金融和征信领域的热捧与讨论。首先，本文简单梳理ZestFinance的发展历程，详细介绍ZestFinance的普惠金融理念和对于大数据的理解，并且对ZestFinance的数据挖掘技术和信用评分原理进行了详细分析。其次，本文概述以FICO为代表的传统个人征信模式，通过FICO与ZestFinance的多角度对比，阐释两者的关系以及ZestFinance的长期发展优势，讨论了ZestFinance取代FICO评分的可能性。再次，本文分析了ZestFinance与京东的合作基础，对双方的合作从积极意义、潜在问题和面临的挑战等方面进行探讨，展望ZestFinance的国际化进程。最后，本文总结了ZestFinance大数据征信实践和应用前景对我国个人征信领域的借鉴意义以及带来的问题思考

In 2015，China Personal Credit Industry started its market process，and Sesame and other Internet credit models gradually gained extensive attention. ZestFinance, a financial services technology company that uses machine learning and data science to help companies make more accurate financial decisions, has aroused heated discussions among domestic Internet financial  services companies and personal credit fields. Firstly, the thesis briefly reviews the development of ZestFinance，details its business ideas about underwriting industry and its understanding for big data, and also analyzes its high-dimensional machine learning search algorithms. Secondly, the thesis outlines traditional collection models represented by FICO, contrasts traditional credit rating systems and big-data credit analyzing models in different aspects，defines the relationship between FICO and ZestFinance and also explains several comparative advantages of ZestFinance in the long-term development. Thirdly, the thesis discusses the basis and significance for the cooperation between ZestFinance and JD as well as potential problems and challenges for both sides, and also looks ahead to the future of international development of ZestFinance. Lastly，the thesis provides recommendations and in-deep thinking on the development of Personal Credit Industry in China. 

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