Dr. Jian Chen is the founder and CEO of CreditWise Technologies, Co. Ltd. He also serves as the senior advisor of Caixin Insight Group, a prestigious think tank in China. He previously held the positions of Managing Partner of RQuest Financial Services Group, Managing Director in IFE Group, Risk Modeling Director in Freddie Mac, Director of Credit Risk Management in Fannie Mae. He recently created the COVID-19 Global Risk Index (http://covid19-risk-index.com/) to assess the risk of each country in the pandemic, together with Dr. Zhang, Wenhong of Huashan Hospital.
Dr. Chen currently holds the academic position of adjunct professor of real estate finance at Fudan university, a senior research fellow at Shanghai Institute of Advanced Finance (SAIF). He also serves as the visiting professor of PKU-Fordham joint PhD program. He previously served as an adjunct professor at Johns Hopkins Carey Business School, where he taught MBA-level finance courses. Dr. Chen’s academic research interests include discrete event modeling, real estate finance and economics, fixed income securities pricing & hedging, consumer behavior modeling, and quantitative risk management.
Dr. Chen writes column articles for several prominent Chinese newspaper and periodicals, including Wenhui Bao, South Reviews Magazine, CAIXIN Media. Dr. Chen has his BS in EE from Xi’an Jiaotong University, his MS in EE from Shanghai Jiaotong University, and his Ph.D. in Management Science with concentration on Computational Finance, from Robert H. Smith School of Business, University of Maryland at College Park.
Dr. Chen recently applied the quantitative model of credit risk analysis for the prediction of COVID-19 outbreaks. This approach is proven to be more robust, flexible, and accurate than most traditional epidemiological models. This new approach applies state transition matrix techniques in coronavirus infection and treatment predictions. The key innovation is trifold: 1. It is a flexible model which can predict the intermediate states; 2. It doesn't need too much parameter estimation and is mainly driven by empirical probabilities; 3. It treats all the government preventive measures as embedded in the observed probabilities. Thus, this model greatly improves the predictive power.