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【Lecture on Economics and Busness】Prof.Duan Jinquan's Lecture Notice

Publish Date: 2017/07/06 13:43:34    Hits:

Title:From Big to Smart and on to Actionable Data — A New Credit Risk Analytics Paradigm

Lecturer:Prof. Jin-Chuan Duan(段锦泉),National University of Singapore

Host:Prof.Fan Ying


Location:Beihang New Main BuildingA212

Abstract:To unleash the power of Big Data, it is better to first transform Big Data into Smart Data so that with further and simple processing, Actionable Data can emerge to assist decision making. The Credit Research Initiative (CRI) launched at the National University of Singapore in 2009 was a concrete “public good” response to the need for credit rating reform post the 2008 global financial crisis, and the CRI research/service infrastructure showcases such a Smart Data paradigm in action. The Smart Data are the daily updated probabilities of default (PDs) and actuarial spreads (ASes), a CDS-like credit risk measure, on all exchange-traded firms globally, including around 35,000 currently active companies in 120 economies and over 20 years of historical time series on more than 60,000 companies inclusive of those inactive ones due to bankruptcies, M&As or other reasons. These freely accessible PDs and ASes are products of scientific research conducted by the CRI researchers with contributions from both researchers and practitioners globally, and the development and maintenance of the live CRI platform is staffed by a team of 40 plus dedicated members (rmicri.org).

The CRI Smart Data platform has created a new possibility for scientific research; for example, researchers can develop and/or test their credit solutions/ideas on live data which typically present a different level of challenges. Through real-world applications of its deep credit analytics, the CRI has also demonstrated new possibilities of creating Actionable Data via Smart Data in FinTech. As an example, the CRI has, in collaboration with the International Monetary Fund, developed a Bottom-up Default Analysis (BuDA) toolkit currently used by the IMF staff to translate the live CRI-PDs under presumed economic scenarios into impacts on the credit risk profile of a target group of financial institutions or nonfinancial corporates (i.e., stress testing) in a timely fashion.

About the Lecturer:Duan is the Cycle & Carriage Professor of Finance in the Business School of National University of Singapore (NUS). Previously, he served as the Director of the NUS Risk Management Institute from July 2007 to June 2014. During that tenure, he pioneered the “public good” Credit Research Initiative (CRI) in March 2009 and continues to lead the CRI team of 40 strong to this day. In 2017, Duan co-founded a FinTech startup, CriAT, specializing in deep credit analytics. Duan was elected in 2008 an Academician of the Academia Sinica for his scholarly contributions, and also became a fellow of the Society for Financial Econometrics in 2013. Duan completed his undergraduate education at the National Taiwan University, an MBA from the State University of New York at Albany and a PhD in Finance from the University of Wisconsin-Madison. Duan’s research expertise is in financial engineering and risk management, and is known for his earlier work on developing the GARCH option pricing model and more recent corporate default research in connection with the CRI. In addition to numerous scholarly publications on derivative securities, financial time series and risk management, he has written a book and occasional media commentaries on current financial/economic events. Before joining NUS, Duan held the Manulife Chair Professorship at the Rotman School of Management, University of Toronto, and also once taught at the Hong Kong University Science and Technology and McGill University.