With the re-writing of the Basel accords in international banking and their ensuing application, interest in credit risk has never been greater. The Journal of Credit Risk focuses on the measurement and management of credit risk, the valuation and hedging of credit products, and aims to promote a greater understanding in the area of credit risk theory and practice.
The Journal of Credit Risk considers submissions in the form of research papers and technical papers, on topics including, but not limited to:
- Modelling and management of portfolio credit risk
- Recent advances in parameterizing credit risk models: default probability estimation, copulas and credit risk correlation, recoveries and loss given default, collateral valuation, loss distributions and extreme events
- Pricing and hedging of credit derivatives
- Structured credit products and securitizations e.g. collateralized debt obligations, synthetic securitizations, credit baskets, etc.
- Measuring managing and hedging counterparty credit risk
- Credit risk transfer techniques
- Liquidity risk and extreme credit events
- Regulatory issues, such as Basel II, internal ratings systems, credit-scoring techniques and credit risk capital adequacy
Abstracting and Indexing: Scopus; Web of Science - Social Science Index; EconLit; Excellence Research Australia; Econbiz; and Cabell’s Directory
Impact Factor: 0.226
5-Year Impact Factor: 0.354
This paper surveys the impressively broad range of machine learning methods and application areas for credit risk.
Review of credit risk and credit scoring models based on computing paradigms in financial institutions
This paper provides an overview of some prominent credit scoring models used in financial institutions and provides an insight into how the use and integration of popular computing paradigms based on NNs, machine learning, game theory and BDA in credit…
An interpretable Comprehensive Capital Analysis and Review (CCAR) neural network model for portfolio loss forecasting and stress testing
This paper proposes an interpretable nonlinear neural network model that translates business regulatory requirements into model constraints.
Three ways to improve the systemic risk analysis of the Central and Eastern European region using SRISK and CoVaR
This paper proposes three modifications to two well-established measures of systemic risk, SRISK and CoVaR.
This paper calibrates a perpetual-debt structural model (PDSM) by using Moody’s historical credit ratings.
This study aims to conduct credit scoring by focusing on a Chinese P2P lending platform and selecting the optimal subset of features in order to find the best overall ensemble model.
Small and medium-sized enterprises that borrow from "alternative" lenders in the United Kingdom: who are they?
This study provides a general overview of the external financing landscape for the UK SMEs and an exploratory analysis of the SME portfolio of one of the alternative lenders in the United Kingdom.
From incurred loss to current expected credit loss: a forensic analysis of the allowance for loan losses in unconditionally cancelable credit card portfolios
The authors analyze the performance of the CECL framework under plausible assumptions about allocations of future payments to existing credit card loans, a key implementation element.
The effects of customer segmentation, borrower behaviors and analytical methods on the performance of credit scoring models in the agribusiness sector
The main aim of this study is to analyze the joint effects of customer segmentation, borrower characteristics and modeling techniques on the classification accuracy of a scoring model for agribusinesses.
The economics of debt collection, with attention to the issue of salience of collections at the time credit is granted
This paper considers the role of policies that protect consumers from aggressive debt collection tactics.
This paper investigates factors associated with high credit card loss rates during the period 2008–11 associated with the Great Recession.
The results of this paper show that robust forward-looking statistical models are superior to backward-looking assessments of supervisory compliance, which could lead to less regulatory burden when integrated into the examination process, particularly at…
In this paper, the authors investigate how data aggregation and risk attributes affect the development and performance of stress testing models by studying residential mortgage loan defaults.
The authors estimate a county-level model of household delinquency and use it to conduct “stress tests” of household debt.
Credit exposure under the new standardized approach for counterparty credit risk: fixing the treatment of equity options
The new standardized approach for measuring counterparty credit risk exposures (SA-CCR) will replace the existing regulatory standard methods for exposure quantification. This paper provides empirical evidence that the SA-CCR parameters are not aligned…
Corporate default risk modeling under distressed economic and financial conditions in a developing economy
The authors create stepwise logistic regression models to predict the probability of default for private nonfinancial firms under distressed financial and economic conditions in a developing economy. Their main aim is to identify and interpret the…
The authors propose a novel framework for credit risk modeling, where default or failure information and rating or expert information are jointly incorporated in the model.
Elliptical and Archimedean copula models: an application to the price estimation of portfolio credit derivatives
This paper explores the impact of elliptical and Archimedean copula models on the valuation of basket default swaps.
This paper presents an International Financial Reporting Standard 9 (IFRS 9) compliant solution related to expected credit loss modeling.
The Covid-19 health crisis has dramatically affected just about every aspect of the economy, including the transition from a record long benign credit cycle to a stressed one, with still uncertain dimensions. This paper seeks to assess the credit climate…