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Niwan Wattanakitrungroj, Pimchanok Wijitkajee, Saichon Jaiyen, Sunisa Sathapornvajana and Sasiporn Tongman
For the financial health of lenders and institutions, one important risk assessment called credit risk is about correctly deciding whether or not a borrower will fail to repay a loan. It not only helps in the approval or denial of loan applications but a...
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Maryam Badar and Marco Fisichella
Fairness-aware mining of data streams is a challenging concern in the contemporary domain of machine learning. Many stream learning algorithms are used to replace humans in critical decision-making processes, e.g., hiring staff, assessing credit risk, et...
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John E. Marthinsen and Steven R. Gordon
The failure of major banks in 2023, such as Silicon Valley Bank (SVB), Signature Bank, First Republic Bank, and Credit Suisse, points to the continuing need for financial institutions to price liquidity risk properly and for financial systems to find alt...
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Rasha Istaiteyeh, Maysa?a Munir Milhem, Farah Najem and Ahmed Elsayed
This paper presents a comprehensive analysis of key financial indicators influencing the operational efficiency of banks in Jordan over the period 2006 to 2021. The study, focusing on fifteen commercial banks, employs seven regression models to assess th...
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Tanja Verster and Erika Fourie
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 ...
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Muhamad Jumaa, Mohammed Saqib, Arif Attar
Pág. 85 - 92
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Eren Duman, Mehmet S. Aktas and Ezgi Yahsi
In today?s financial landscape, traditional banking institutions rely extensively on customers? historical financial data to evaluate their eligibility for loan approvals. While these decision support systems offer predictive accuracy for established cus...
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Dean Fantazzini
In this paper, we analyzed a dataset of over 2000 crypto-assets to assess their credit risk by computing their probability of death using the daily range. Unlike conventional low-frequency volatility models that only utilize close-to-close prices, the da...
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Endang Sri Apriani,Silvie Eka Putri,Ramli Ramli
Pág. 63 - 76
This study has the aim of knowing the Effects of Credit Risk, Liquidity Risk and Operational Risk on Profitability at Conventional Banks listed on the Indonesia Stock Exchange (IDX) for the 2019-2021 period. The data source used is financial data in each...
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Khalil Alnabulsi, Emira Kozarevic and Abdelaziz Hakimi
This paper analyzes the linear and non-linear relationship between non-performing loans and bank profitability measured by the Net Interest Margin for a sample of 74 Middle Eastern and North African banks over the period of 2005?2020. We used the System ...
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