Journal of Credit Risk

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

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