李志勇 

个人信息

• 个人网站：www.zhiyongli；www.credit.li
• 电子邮件：liz@swufe.edu.cn；li@credit.li
• 办公地址： 中国四川省成都市温江区柳台大道555号格致大厦521室

担任职务

• 2022至今，西南财经大学金融学院信用管理专业负责人、教授
• 2019-2022， 西南财经大学金融学院信用管理系主任、教授
• 2015-2018，西南财经大学金融学院信用管理系副主任，副教授
• 2014-2015，西南财经大学金融学院信用管理系副主任、讲师

社会兼职

• 2020至今，China Society of Credit Research秘书长
• 2017至今，管理科学与工程学会金融计量与风险管理研究会理事
• 2017至今，四川省金融学会金融科技专业委员会学术委员
• 2019至今，西南财经大学普惠金融与智能金融研究中心副主任
• 2016-2022，西南财经大学中国金融研究院金融科技与监管科技实验室主任
• 2014-2017，英国爱丁堡大学商学院研究员

教育背景

• 2009 至 2014 英国爱丁堡大学商学院信用研究中心，信用风险管理博士（PhD），导师：Jonathan Crook & Galina Andreeva
• 2007 至 2008 英国爱丁堡大学数学学院，运筹学与金融风险硕士（MSc），导师：Galina Andreeva
• 2005 至 2007 北京航空航天大学理学院，应用数学学士（BSc），导师：李尚志
• 2003 至 2007 北京航空航天大学航空科学与工程学院，飞行器设计和工程学士（BEng），导师：郭辉

研究方向

• 研究巴塞尔协议、信用评分、信用评级、信贷组合风险管理、商业银行压力测试等，
• 关注财务危机与不良资产、金融科技与监管科技、消费金融与绿色金融、未来银行与开放银行、社会信用体系与征信等

学术兼职

• Journal of Chinese Economic and Business Studies，牛津大学TMCD研究院主办，ESCI，客座编辑，2023-
• British Accounting Review, 英国财务与会计协会（British Accounting and Finance Association）主办，SSCI，JCR Q1，客座编辑，2022-
• China Finance Review International，上海交通大学安泰管理学院主办，ESCI，青年编委，2022-
• Journal of Credit Risk，SSCI，客座编辑，2022-
• International Journal of Financial Engineering, 中山大学管理学院主办，ESCI，副主编，2020-
• International Journal of Forecasting, 国际预测学会（International Institute of Forecasters）主办，SSCI，JCR Q1，客座编辑，2020-2022
• 《金融发展评论》，中国金融学会、新疆金融学会主办，全国性刊物，执行主编，2020-2021

科研成果

一作论文

1. Li Z, Li A, Bellotti A & Yao X. (2023). The profitability of online loans: a competing risks analysis on default and prepayment. European Journal of Operational Research. 306(2): 968-985. (ABS 4, JCR Q1). DOI/PDF. (Cites: 2)
2. Li Z, Feng C & Tang Y. (2022). Bank efficiency and failure prediction: A nonparametric and dynamic model based on data envelopment analysis. Annals of Operations Research. 315: 279–315 (ABS 3, JCR Q1). DOI/PDF. (Cites: 12)
3. Li Z, Zhang J, Yao X & Kou G. (2021). How to identify early defaults in online lending: A cost-sensitive multi-layer learning framework. Knowledge-Based Systems. 221. 106963. (JCR Q1). DOI/PDF. (Cites: 20)
4. Li Z, Crook J, Andreeva G & Tang Y. (2021). Predicting the Risk of Financial Distress using Corporate Governance Measures. Pacific-Basin Finance Journal. 68, 101334. (ABS 2, JCR Q1). DOI/PDF. (Cites: 115)
5. Li Z, Hu X, Li K, Zhou F & Shen F. (2020). Inferring the Outcomes of Rejected Loans: an Application of Semi-supervised Clustering Algorithms. Journal of the Royal Statistical Society: Series A (Statistics in Society). 183(2):631-654. (ABS 3, JCR Q1). DOI/PDF. (Cites: 5)
6. Li Z, Tang Y, Wu J, Zhang J & Lv Q. (2020). The interest costs of green bonds: credit ratings, corporate social responsibility, and certification. Emerging Markets Finance and Trade. 56(12):2679-2692. (ABS 2, JCR Q3). DOI/PDF. (Cites: 109)
7. Li Z, Li K, Yao X & Wen Q. (2019). Predicting prepayment and default risks of unsecured consumer loans in online lending. Emerging Markets Finance and Trade. 55(1):118-132. (ABS 2, JCR Q3). DOI/PDF.(Cites: 24)
8. Li Z, Crook J & Andreeva G. (2017). Dynamic prediction of financial distress using Malmquist DEA. Expert Systems with Applications. 80:94-106. (ABS 1, JCR Q1). DOI/PDF. (Cites: 112)
9. Li Z, Tian Y, Li K, Zhou F & Yang W. (2017). Reject inference in credit scoring using Semi-supervised Support Vector Machines. Expert Systems with Applications. 74:105-114. (ABS 1, JCR Q1). DOI/PDF.(Cites: 128)
10. Li Z, Crook J & Andreeva G. (2014). Chinese Companies Distress Prediction: An Application of Data Envelopment Analysis. Journal of the Operational Research Society. 65(3):466-479. (ABS 3, JCR Q2). DOI/PDF.(Cites: 72)

（注：被引数据取自谷歌学术2023年9月）

合作论文

1. Tang Y, Wang B, Pan N & Li Z. (2023). The impact of environmental information disclosure on the cost of green bond: Evidence from China. Energy Economics. 126. 107008. (ABS 3, JCR Q1). DOI/PDF.
2. Yao X, Wu D, Li Z, Xu H. (2023). On the Prediction of Stock Price Crash Risk Using Textual Sentiment of Management Statement. China Finance Review International. forthcoming. (ESCI). DOI/PDF.
3. Zhang X, Li Z, Zhao Y, & Wang L. (2023). Carbon trading and COVID-19: a hybrid machine learning approach for international carbon price forecasting. Annals of Operations Research. forthcoming. (ABS 3, JCR Q1). DOI/PDF.
4. Li A, Li Z, & Bellotti A. (2023). Predicting loss given default of unsecured consumer loans with time-varying survival scores. Pacific-Basin Finance Journal. 78. 101949. (ABS 2, JCR Q1). DOI/PDF.
5. Zhou F, Fu L, Li Z & Xu J. (2022) The Recurrence of Financial Distress: A Survival Analysis. International Journal of Forecasting. 38(3): 1100-1115. (ABS3, JCR Q1). DOI/PDF.
6. Zeng X, Li Z, Yang W & Huang Z. (2022) The risk interdependence of cryptocurrencies: Before and during the COVID-19 pandemic. International Journal of Financial Engineering. 9(4). 2150044. (ESCI). DOI/PDF.
7. Wu Z & Li Z. (2021). Customer Churn Prediction for Commercial Banks Using Customer Value Weighted Machine Learning Models. Journal of Credit Risk. 17(4): 15-42. (ABS 1, JCR Q4). DOI/PDF.
8. Li K, Zhou F, Li Z, Li W & Shen F. (2021). A semi-parametric ensemble model for profit evaluation and investment decisions in online consumer loans with prepayments. Applied Soft Computing. 107. 107485. (JCR Q1). DOI/PDF.
9. Li K, Zhou F, Li Z, Yao X & Zhang Y. (2021). Predicting loss given default using post-default information, Knowledge-Based Systems. 224. 107068. (JCR Q1). DOI/PDF.
10. Tang Y, Li Z, Chen J & Deng C. (2021). Liquidity creation cyclicality, capital regulation and interbank credit: Evidence from Chinese commercial banks. Pacific-Basin Finance Journal. 101523. (ABS 2, JCR Q1). DOI/PDF.
11. Shen F, Zhao X, Li Z, Li K & Meng Z. (2019). A novel ensemble classification model based on neural networks and a classifier optimisation technique for imbalanced credit risk evaluation. Physica A: Statistical Mechanics and its Applications. 526. 121073. (JCR Q2). DOI/PDF.
12. Tang Y, Moro A, Sozzo S & Li Z. (2018). Modelling trust evolution within small business lending relationships. Financial Innovation. 4:1-19. (JCR Q1). DOI/PDF.
13. Shen F, Ma X, Li Z, Xu Z & Cai D. (2018). An extended intuitionistic fuzzy TOPSIS method based on a new distance measure with an application to credit risk evaluation. Information Sciences. 428:105-119. (JCR Q1). DOI/PDF.
14. Tian Y, Li K, Yang W & Li Z. (2017). A new effective branch-and-bound algorithm to the high order MIMO detection problem. Journal of Combinatorial Optimization. 33(4):1395-1410. (ABS 2, JCR Q3). DOI/PDF.

专著译作

1. 《信用评分应用》，托马斯 等（著），李志勇（译），中国金融出版社，2020，ISBN：9787522005560
2. 《信用评级原理与实务》，冯光华 等（编著），李志勇（参编），中国金融出版社，2019，ISBN：9787504998491
3. 《中国金融科技运行报告2018》，杨涛、贲圣林（主编），李志勇（参编），社会科学文献出版社，2018，ISBN：9787520128612
4. 《信用评分工具：自动化信用管理的理论与实践》，安德森（著），李志勇（译），中国金融出版社，2017，ISBN：9787504990334
5. 《消费信用模型：定价、利润与组合》，托马斯（著），李志勇（译），中国金融出版社，2016，ISBN：9787504984111

会议论文

1. Tang Y, Moro A, Sozzo S & Li Z. (2019) A Spiral Model of Trust Evolution. In Proceedings of the Twelfth International Conference on Management Science and Engineering Management. Part 3:515-526. Springer, Cham
2. Shen F, Liu Y, Lan D, Li Z. (2019) A Dynamic Financial Distress Forecast Model with Time-Weighting Based on Random Forest. In: Xu J., Cooke F., Gen M., Ahmed S. (eds) Proceedings of the Twelfth International Conference on Management Science and Engineering Management. ICMSEM 2018. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham
3. Shen F, Lan D & Li Z. (2017). An Intuitionistic Fuzzy ELECTRE-III Method for Credit Risk Assessment. In Proceedings of the Tenth International Conference on Management Science and Engineering Management, 502:289-296. Springer Singapore.

中文论文

1. 袁先智，李志勇等. 财务欺诈风险特征筛选框架的建立和应用. 《中国管理科学》. 2022年第3期. 43-54页. (CSSCI).
2. 袁先智，李志勇等. 在金融科技中基于人工智能算法的风险特征因子筛选框架的建立和在期货价格趋势预测相关的特征因子刻画的应用.《安徽工程大学学报》. 2020年第4期. (CA)
3. 程功，文晴，李志勇. (2017) .基于时变参数模型的银行信用风险与宏观经济形势的动态关系研究.《金融监管研究》. 2017年第3期. 51-72页. (CSSCI扩展)
4. 李志勇，杨维，曾嵘. 利用期货市场设计农业保险产品对冲价格风险.《中国期货》. 2016年第1期。
5. 郭辉，彭艺，李志勇等. 逆压梯度转捩边界层流动结构显示，《实验流体力学》，2008年第2期. 68-73页. (CA)

参会研讨

• Credit Scoring and Credit Rating (2020 Chengdu; 2022 Ningbo)
• Credit Scoring and Credit Control (2009, 2011, 2013, 2015, 2017, 2019, 2021, 2023 Edinburgh)
• China International Risk Forum (2016, Shanghai; 2019 Tianjin; 2020 Shanghai; 2021 Chengdu; 2022 Dalian; 2023 Shanghai)
• International Risk Management Conference (2015, Luxembourg; 2016, Jerusalem; 2017, Florence; 2020, Online; 2021 Online; 2022 Online)
• Asian Finance Association Annual Conference (2023 Ho Chi Minh City)
• Chinese Finance Annual Meeting (2022 Shanghai)
• WRDS Advanced Research Scholar Program at the Wharton School of UPenn (2018, Philadelphia; 2019 Beijing)
• International Conference on Internet Finance (2019, Hangzhou)
• Workshop on Banking and Financial Stability at Deakin Business School (2019, Melbourne)
• Sino-US Economist Fintech Innovation Forum (2018, Stanford)
• International Conference on Corporate Governance in Emerging Markets (2018, Amsterdam)
• International Conference on Energy Finance (2018, Beijing)
• International Conference on Financial Markets and Institutions (2017, Chengdu)
• International Finance and Banking Society (IFABS) Asia Conference (2017, Ningbo)
• International Conference on Asian Financial Markets and Economic Development (2017, Nagasaki)
• European Conference on Operational Research (2012, Vilnius, 2013, Rome; 2016, Poznan)
• Joint Meeting of the Financial Education Alliance and the Central Taiwan Finance Association (2016, Taiwan; 2017 Jiangxi)
• China-UK Microfinance and Rural Finance Conference (2015, Chengdu),
• OR Annual Conference (2012, Edinburgh; 2013, Exeter)
• YoungOR Conference (2011, Nottingham)

指导学生

• 金融学博士（PhD in Finance）：李爱民（2018-2022）、冯晨（2019-）、宣权圣（2020-）、付丽君（2021-）、刘美琦（2022-）
• 工商管理博士（Doctor in Business Administration）：唐晓棠（2019-2022）、孙浩（2019-2022）、薛曾毅（2021-）、欧阳洁（2022-）、吴婷婷（2023-）
• 金融学/金融工程/信用管理硕士（MSc&MF）：63名
• 工商管理硕士（MBA&EMBA）：24名
• 同等学力金融学硕士（MSc）：11名