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A new methodology to derive IFRS 9 PiT PDs is proposed. The methodology first derives a PiT term structure with accompanying segmented term structures. Secondly, the calibration of credit scores using the Lorenz curve approach is used to create account-specific PD term structures. The PiT term...
Persistent link: https://www.econbiz.de/10012704964
Survival analysis is one of the techniques that could be used to predict loss given default (LGD) for regulatory capital (Basel) purposes. When using survival analysis to model LGD, a proposed methodology is the default weighted survival analysis (DWSA) method. This paper is aimed at adapting...
Persistent link: https://www.econbiz.de/10012597134
The International Financial Reporting Standard (IFRS) 9 relates to the recognition of an entity’s financial asset/liability in its financial statement, and includes an expected credit loss (ECL) framework for recognising impairment. The quantification of ECL is often broken down into its three...
Persistent link: https://www.econbiz.de/10014303642
This paper proposes a methodology that utilises model performance as a metric to assess the representativeness of external or pooled data when it is used by banks in regulatory model development and calibration. There is currently no formal methodology to assess representativeness. The paper...
Persistent link: https://www.econbiz.de/10012704644
The key criteria for making business decisions is profit, so when making credit limit-setting strategy decisions, profitability will be the most important driver. The profitability of a credit limit-setting strategy is dependent on the customer’s utilisation of the limits set by the strategy....
Persistent link: https://www.econbiz.de/10013460274
Logistic regression is a very popular binary classification technique in many industries, particularly in the financial service industry. It has been used to build credit scorecards, estimate the probability of default or churn, identify the next best product in marketing, and many more...
Persistent link: https://www.econbiz.de/10014246272
The landscape of financial credit risk models is changing rapidly. This study takes a brief look into the future of predictive modelling by considering some factors that influence financial credit risk modelling. The first factor is machine learning. As machine learning expands, it becomes...
Persistent link: https://www.econbiz.de/10014419408