Carroll School of Management Boston College
College of Business, Texas A&M University–Commerce
It is our pleasure to introduce this special issue of The Journal of Credit Risk, which is dedicated to papers presented at the International Risk Management Conference. This special issue includes some of the outstanding papers presented at the 2020 Global Virtual Conference.
We start the issue with “Covid-19 and the credit cycle: 2020 revisited and 2021 outlook” by Edward I. Altman. This paper provides an update on the author’s insightful keynote talk from the 2020 conference, examining the impact of Covid-19 on the US credit cycle as well as the enormous build-up of global debt even before the pandemic commenced. The paper raises important questions regarding the longer-term consequences of government intervention into credit markets, such as that which occurred early in the pandemic. Such an intervention may raise concerns regarding defaults of over-leveraged companies and “zombie” firms once support from governments and central banks is eliminated.
Our first conference paper, “Customer churn prediction for commercial banks using customer-value-weighted machine learning models” by Zongxiao Wu and Zhiyong Li, proposes a framework for addressing the common issue of customer churn prediction by examining customers’ values including recency, frequency, monetary value and asset level. The proposed framework can provide commercial banks with useful methodology to better formulate marketing strategies for different groups of customers, as well as how to analyze attrition in an economic way, rather than as a simple classification problem.
The second conference paper, “Agency problems in multinational banks: does parent complexity affect the risk-taking of subsidiaries?” by Krzysztof Gajewski and Łukasz Kurowski, empirically reviews the relationship between the geographical complexity of parent groups and the risk-taking behavior of subsidiaries using a set of data for Polish domestically owned and foreign-owned banks covering the years 2008–17. The authors detect that parent complexity affects risk-taking at the subsidiary level, yet this relationship depends on which proxy measure is deployed to assess the risk-taking behavior.
Our third conference paper, “Does economic policy uncertainty exacerbate corporate financial distress risk?” by Jie Sun, Fangyuan Yin, Edward Altman and Lewis Makosa, demonstrates a negative relationship between economic policy uncertainty (EPU) and distress risk by using A-share listed companies on the Shanghai and Shenzhen Stock Exchanges. Global EPU has been rising, and this phenomenon is particularly evident in China. The paper discusses the implications for firm-level decisions, eg, when EPU is high, firms can mitigate the impact on distress risk by reducing investment and increasing cash holdings. This work contributes to our understanding of the real consequences of economic policy uncertainty.
The fourth and final conference paper in the issue is “Incorporating small-sample defaults history in loss given default models” by Aneta Ptak-Chmielewska and Paweł Kopciuszewski. It introduces readers to the problem of estimating loss given default with small or limited default sample sizes. The authors show that the distribution of loss given default is bimodal, and they further develop an estimation approach that utilizes a combination of logistic and linear regression to produce more reliable estimates. The methodology is illustrated with a set of loans from a Polish bank – a unique emerging market that is rarely explored.
We believe that both academics and practitioners will find the papers in this special issue of The Journal of Credit Risk to be of great interest. We hope that you will enjoy reading them and find them to be of value.
This study continues the author’s examination and forecasts as to the impact of Covid-19 on the US credit cycle after one and a half years since the pandemic first began.
Customer churn prediction for commercial banks using customer-value-weighted machine learning models
In this paper the authors propose a framework to address the issue of customer churn prediction, and they quantify customer values with the use of an improved customer value model.
Agency problems in multinational banks: does parent complexity affect the risk-taking of subsidiaries?
This paper empirically reviews the relationship between the geographical complexity of parent-groups and the risk-taking behavior of subsidiaries using a panel of data for Polish domestically owned and foreign-owned banks covering the years 2008–17.
This paper adds to the literature on factors driving distress risk and the economic consequences of economic policy uncertainty, and it provides a basis for enterprises to respond to changes in policies.
This paper proposes a methodology for estimating loss given default (LGD) that accounts for small default sample sizes.