Loss given default (LGD)
Machine learning prediction of loss given default in government-sponsored enterprise residential mortgages
The authors apply machine learning techniques to Loss Given Default estimation, identifying key variables in LGD prediction and evaluating the performance of various models.
Climate capital in the balance as EBA rejects green risk weights
European regulator suggests climate change must be factored into existing risk categories
Can CRE credit risk models cope with hybrid working?
As US office use changes, modellers deploy judgement overlays and alternative data to keep up
Norinchukin’s credit RWAs up 31% on early Basel III opt-in
Bank’s standardised charges surge 19-fold following overhaul of models’ scope and parameters
US credit risk modellers prepare for life after IRB
Stress tests and economic capital calculations may not carry the same weight as Basel ratio
Forecasting the loss given default of bank loans with a hybrid multilayer LGD model by extending multidimensional signals
The authors employ signaling theory and machine learning methods to investigate loss given default predictions of commercial banks and propose a method to improve the accuracy of these predictions.
Data-driven wrong-way risk
A calculation method for regulatory CVA wrong-way risk based on credit and exposure is introduced
Merton’s model with recovery risk
By adding a correlated risk driver to Merton's model for corporate bond pricing, the authors model the empirically observed recovery risk premium.
Nationwide’s IRB charges up 89% on PRA’s parameter curbs
The building society’s strict focus on mortgages meant impact was all-sweeping
Project finance risk methodologies
Federico Tacchetto, senior manager at Prometeia, describes how to calculate risk parameters for project finance exposures. Based on a simulation approach of the cashflows, it is assessed whether the generated net revenue will be sufficient to repay the…
Mind the gap
A default intensity model reveals the risk carried by a highly leveraged counterparty
Model clampdown costs NatWest 157bp of CET1 ratio
Measures to remedy internal model deficiencies added £14.8 billion RWAs overnight
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.
A prudent loss given default estimation for mortgages. II
This paper introduces a prudent methodology to accurately estimates loss given default for mortgage portfolios and to stress test those portfolios effectively.
Weather, or not: is climate risk just part of credit risk?
Practitioners divided on whether climate risk can fit into existing credit risk weights
After bruising EU model review, banks ask: ‘Why bother?’
Post-Trim changes erode capital savings from internal models while raising their running costs
EU banks’ credit risk estimates stabilised at year-end
Weighted average corporate borrower PD across countries climbed to 2.15%
At systemic US banks, corporate default risk ebbed in Q4
Median PD of corporate portfolios down to 1.6% from 1.73%
Beyond the contract: client behavior from origination to default as the new set of the loss given default risk drivers
In this paper, we expand the modeling process by constructing a set of client-behavior-based predictors that can be used to construct more precise models, and we investigate the economic justifications empirically to examine their potential usage.
Modeling loss given default regressions
The authors investigate the puzzle in the literature that various parametric loss given default (LGD) statistical models perform similarly, by comparing their performance in a simulation framework.
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Asia Risk Technology Awards 2020