Technical paper/Default risk
Bridging credit transitions and spread dynamics
A fast-to-calibrate model to simulate a credit rating transition matrix is presented
Quantum path integrals for default intensity models
A method to price credit derivatives via default intensity approximation is presented
Enhancing default prediction in alternative lending: leveraging credit bureau data and machine learning
The authors apply machine learning techniques to credit bureau data and loan-specific variables to improve default prediction in the alternative lending sector.
How magic a bullet is machine learning for credit analysis? An exploration with fintech lending data
The authors apply machine learning techniques to consumer fintech loan data to assess how such techniques can improve out-of-sample default prediction.
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.
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.
Default risk in the era of environmental, social and governance ratings: a comparative analysis of divergence
The authors investigate links between ESG ratings divergence and default risk, finding firms demonstrating better ESG performance show lower default risk.
A model combining Optuna and the light gradient-boosting machine algorithm for credit default forecasting
The authors put forward a default prediction model designed to make the analysis of complex, highly dimensional and imbalanced real-world bank data easier.
Weighting for leverage
A credit exposure model for leveraged collateralised counterparties is presented
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.
Characteristics of student loan credit recovery: evidence from a micro-level data set
The authors investigate delinquent student loans, identifying factors which influence the likelihood of recovery and proposing means to improve student loan credit recovery rates.
Forecasting the default risk of Chinese listed companies using a gradient-boosted decision tree based on the undersampling technique
The authors put forward a model for default prediction designed to minimise the impact of imbalanced classification, verifying its effectiveness with real world data from Chinese listed companies.
Credit contagion risk in German auto loans
The authors employ a data set of over 5 million German auto loans to investigate credit contagion risk and show that defaults cannot be attributed to single factors.
Leveraged wrong-way risk
A model to assess the exposure to leveraged and collateralised counterparties is presented
Default forecasting based on a novel group feature selection method for imbalanced data
The authors construct a group feature selection method which combines optimal instance selection with weighted comprehensive precision in an effort to improve the performance of prediction models in relation to defaulting firms.
Small and medium-sized enterprises’ time to default: an analysis using an improved mixture cure model with time-varying covariates
The authors put forward a method using a support vector machine to enhance the exploration of nonlinear covariate effects if SMEs never default while also considering time-varying and fixed covariates for the incidence and latency of an event.
Banking on personality: psychometrics and consumer creditworthiness
This paper uses empirical methods to investigate how psychometric data can be used to augment traditional credit models.
Collateralised exposure modelling: bridging the gap risk
Concentration, leverage and correlations may affect a collateralised equity swap portfolio
Assessing systemic fragility: a probabilistic perspective
Using new measure of systemic fragility, the author ranks euro area banks and sovereigns and according to their systemic risk contribution.
Sovereign probabilities of default in the euro area
This paper decomposes credit default swap spreads of euro area members into their risk premium and default risk elements and forecast one year probabilities of default.
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.