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Impact of mortgage soft information in loan pricing on default prediction using machine learning
Luong, Thi Mai; Scheule, Harald; Wanzare, Nitya - In: International review of finance : the official journal … 23 (2023) 1, pp. 158-186
Persistent link: https://www.econbiz.de/10014251350
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Bankruptcy prediction with a doubly stochastic poisson forward intensity model and low-quality data
Berent, Tomasz; Rejman, Radosław - In: Risks : open access journal 9 (2021) 12, pp. 1-24
With the record high leverage across all segments of the (global) economy, default prediction has never been more … defaulters, we model default probability using a doubly stochastic Poisson process. Our paper is unique in that it uses a large … 76%, one and three years prior to default, respectively. What we lose in (data) quality, we regain in (data) quantity …
Persistent link: https://www.econbiz.de/10012794088
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Impact of soft information in loan pricing on default prediction using machine learning
Luong, Thi Mai; Scheule, Harald; Wanzare, Nitya - 2023
Persistent link: https://www.econbiz.de/10014470089
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Net flow rates versus roll rates as non-performing consumer loans forecasting methodologies
De Ribera Martin, Francisco de Asis - In: Revista de métodos cuantitativos para la economía y … 34 (2022), pp. 37-59
Roll rates and net flow rates can be seen as the evolution of ageing of accounts receivable and Markov chains. They are accepted methodologies to model the behavior of non-performing consumer loans by buckets and to predict losses, but we find that quite often they are wrongly used as...
Persistent link: https://www.econbiz.de/10013485817
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The Use of Financial Information Systems to Predict Failure of Repaying Banks Loans
Mohd Ali, Badruldeen - 2020
From year to year, strong attention has been paid to the study of the problems of predicting firms' bankruptcy. Bankruptcy prediction is an essential issue in finance especially in emerging economics. Business information systems like Financial Information Systems (FIS) converts and store the...
Persistent link: https://www.econbiz.de/10012822710
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Using cutting-edge tree-based stochastic models to predict credit risk
Halteh, Khaled; Kumar, Kuldeep; Gepp, Adrian - In: Risks : open access journal 6 (2018) 2, pp. 1-13
Credit risk is a critical issue that affects banks and companies on a global scale. Possessing the ability to accurately predict the level of credit risk has the potential to help the lender and borrower. This is achieved by alleviating the number of loans provided to borrowers with poor...
Persistent link: https://www.econbiz.de/10011867384
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The role of financial constraint factors in predicting SME default
Karas, Michal; Režňáková, Mária - In: Equilibrium : quarterly journal of economics and … 16 (2021) 4, pp. 859-883
Persistent link: https://www.econbiz.de/10012798670
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Short interest, stock returns and credit ratings
Guo, Xu; Wu, Chunchi - In: Journal of banking & finance 108 (2019), pp. 1-14
Persistent link: https://www.econbiz.de/10012224662
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Impact of Mortgage Soft Information in Loan Pricing on Default Prediction using Machine Learning
Luong, Mai; Scheule, Harald (Harry); Wanzare, Nitya - 2022
We analyse the impact of soft information on US mortgages for default prediction and provide a new measure for lender … and soft information provide for a variation in annual default probabilities of approximately 3%. Soft information has a …
Persistent link: https://www.econbiz.de/10014236050
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Credit scoring and default risk prediction : a comparative study between discriminant analysis & logistic regression
Khemais, Zaghdoudi; Nesrine, Djebali; Mohamed, Mezni - In: International journal of economics and finance 8 (2016) 4, pp. 39-53
Persistent link: https://www.econbiz.de/10011456360