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 analyzes how soaring demand in the lending market shortly before a financial crisis can affect one of the main parameters in the internal ratings-based approach: the asset correlation.
In this paper, a theoretical method is empirically illustrated in finding the best time to forsake a loan such that the overall credit loss is minimized.
In this paper the authors propose a framework for granular-level stressed net interest income calculation and profit-and-loss risk attribution.
This paper proposes a credit risk model based on purchase order information to address the deficiencies of monitoring methods that use only financial statements.
This study explores banks’ internal credit risk estimates and the associated banksourced transition matrixes.
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.
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.
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 study proposes an advanced credit evaluation method for nonperforming consumer loans, which may serve as a new investment opportunity in the post-pandemic era.
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.