Technical paper/Credit risk
Quantification of margin of conservatism category C: correlations and quantification levels
The author suggests means for margin of conservatism type C quantification of overlapping one-year default rates and approximate the confidence level for MoC C quantification at grade level.
Bank loan credit risk pooling: risk diversification versus the moral hazard problem
Investigating the relationship between liquidity creation and credit risk, with the moderating role of loan concentration: Islamic versus conventional banks in Pakistan and Malaysia
The creation, credit risk and performance of fintech credit: peer-to-peer lending in Canada
A novel budget-based C+SVM model for credit risk prediction
The authors propose a modified support vector machine model based on load budget with which to predict credit risk.
Bridging credit transitions and spread dynamics
A fast-to-calibrate model to simulate a credit rating transition matrix is presented
Credit risk meets insurance risk: a unified framework
Extending the influential CreditRisk+ model for portfolio credit risk modeling, the authors propose adding a continuous-time extension to the model.
The role of personal credit in small business risk assessment: a machine learning approach
The authors investigate how personal credit data can be combined with business-level and tradeline variables in a machine learning framework to enhance default prediction.
A minimum sample size definition for the purpose of loss provision extrapolation in the presence of default correlation
The author applies the Bernoulli distribution to an extrapolation of the capital provision that does not take into account the possible existence of a default correlation.
Did fintech loans default more during the Covid-19 pandemic? Were fintech firms “cream-skimming” the best borrowers?
The authors propose a model which can be used to identify the "invisible prime" consumers from the nonprime pool for fintech loans.
The WWR in the tail: a Monte Carlo framework for CCR stress testing
A methodology to compute stressed exposures based on a Gaussian copula and mixture distributions is introduced
Survival analysis in credit risk management: a review study
This paper offers a systematic literature review of survival analysis in credit risk assessment and suggests potential future avenues for research.
Uncertainty in the macroeconomic environment, corporate tax avoidance and corporate credit financing: evidence from high-tech listed companies in China
Using data from Chinese high-tech enterprises, the authors investigate links between corporate tax avoidance and bank credit financing.
Soft information in financial distress prediction: evidence of textual features in annual reports from Chinese listed companies
The authors use textual data in a model to predict financial distress, demonstrating that this can enhance prediction outcome versus traditional financial data alone.
Relaxing the assumption of conditional independence in an asymptotic single risk factor model
Within the framework of dynamic credit provisioning and stress testing, this paper shows how conditional correlation impacts an asymptotic single risk factor model.
Distributionally robust optimization approaches to credit risk management of corporate loan portfolios
A new approach to manage credit risk in financial institutions - the empirical divergence-based distributionally robust optimization - is proposed and shown to alleviate the challenges of sample sparsity and data uncertainty in credit risk modeling.
A method of classifying imbalanced credit data based on the AC-CTGAN hybrid sampling algorithm
The authors put forward a novel method with which to identify risk in consumer credit data and demonstrate its enhanced generalization ability compared to commonly used methods.
Litigation risk assessment: a novel quantitative recency–frequency–monetary model
The authors assess litigation risk and credit risk of companies and investigate interrelationships between these risks, finding a correlation between them.
Backtesting correlated quantities
A technique to decorrelate samples and reach higher discriminatory power is presented
Consumer credit card payment dynamics over the economic cycle
This papers uses data from 1.8 million credit card accounts to investigate how consumers revolve credit card debt and the impact of this on default risk.
Weighting for leverage
A credit exposure model for leveraged collateralised counterparties is presented
Key indicators for the credit risk evaluation of clients and their changing characteristics
The authors propose a credit risk evaluation model for energy performance contracting projects with debt- paying ability and long-term capital debt ratio as optimal indicators.
Financial distress prediction with optimal decision trees based on the optimal sampling probability
The authors propose and validate a tree-based ensemble model for financial distress prediction which is demonstrated to outperform comparative models.
Default prediction based on a locally weighted dynamic ensemble model for imbalanced data
The authors put forward a locally weighted dynamic ensemble model which can predict financial institutions' default statues five years ahed.