Journal of Credit Risk
ISSN:
1744-6619 (print)
1755-9723 (online)
Editor-in-chief: Linda Allen and Jens Hilscher
About this journal
With the adoption of machine learning and artificial intelligence in financial institutions, credit analysis methodologies and applications are rapidly evolving.
The Journal of Credit Risk is at the forefront in tackling the many issues and challenges posed by these novel technologies both in and out of periods of financial crisis. Topics include fintech, liquidity risk and the connection to credit risk, the valuation and hedging of credit products, and the promotion of 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 reports on, but not limited to, the following topics.
- Modeling 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.
- The pricing and hedging of credit derivatives.
- Structured credit products and securitizations, eg, collateralized debt obligations, synthetic securitizations, credit baskets, etc.
- Machine learning and artificial intelligence.
- Credit risk implications of blockchain, crypto currencies and fintech firms.
- Measuring, managing and hedging counterparty credit risk.
- Credit risk transfer techniques.
- Liquidity risk and extreme credit events.
- Regulatory issues, such as Basel II and III, 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
Journal Metrics:
Journal Impact Factor: 0.880
5-Year Impact Factor: 1.045
CiteScore: 1.6
Latest papers
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.
Does economic policy uncertainty exacerbate corporate financial distress risk?
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.
Incorporating small-sample defaults history in loss given default models
This paper proposes a methodology for estimating loss given default (LGD) that accounts for small default sample sizes.
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.
Forecasting consumer credit recovery failure: classification approaches
This study proposes an advanced credit evaluation method for nonperforming consumer loans, which may serve as a new investment opportunity in the post-pandemic era.
A survey of machine learning in credit risk
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.
Explaining credit ratings through a perpetual-debt structural model
This paper calibrates a perpetual-debt structural model (PDSM) by using Moody’s historical credit ratings.
Ensemble methods for credit scoring of Chinese peer-to-peer loans
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.
Bankcard performance during the Great Recession: a consumer-level analysis
This paper investigates factors associated with high credit card loss rates during the period 2008–11 associated with the Great Recession.
Supervisory bank risk early warning modeling: an examiner’s first line of defense
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…
The impact of data aggregation and risk attributes on stress testing models of mortgage default
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.
Stress testing household debt
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…