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Ognjen Radovic,Srdan Marinkovic,Jelena Radojicic
Credit scoring attracts special attention of financial institutions. In recent years, deep learning methods have been particularly interesting. In this paper, we compare the performance of ensemble deep learning methods based on decision trees with the b...
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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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Yao Zou and Changchun Gao
Credit scoring is an effective tool for banks and lending companies to manage the potential credit risk of borrowers. Machine learning algorithms have made grand progress in automatic and accurate discrimination of good and bad borrowers. Notably, ensemb...
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João A. Bastos
Credit scoring models help lenders decide whether to grant or reject credit to applicants. This paper proposes a credit scoring model based on boosted decision trees, a powerful learning technique that aggregates several decision trees to form a classifi...
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Naomi Simumba, Suguru Okami, Akira Kodaka and Naohiko Kohtake
Feature selection is crucial to the credit-scoring process, allowing for the removal of irrelevant variables with low predictive power. Conventional credit-scoring techniques treat this as a separate process wherein features are selected based on improvi...
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Lkhagvadorj Munkhdalai, Keun Ho Ryu, Oyun-Erdene Namsrai and Nipon Theera-Umpon
Credit scoring is a process of determining whether a borrower is successful or unsuccessful in repaying a loan using borrowers? qualitative and quantitative characteristics. In recent years, machine learning algorithms have become widely studied in the d...
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Wenjiang Jiao, Xingwei Hao and Chao Qin
CNN is particularly effective in extracting spatial features. However, the single-layer classifier constructed by activation function in CNN is easily interfered by image noise, resulting in reduced classification accuracy. To solve the problem, the adva...
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Ekaterina V. Orlova
Credit operations are fundamental in the banks? activities and provide a significant share of their income. Under an increased demand for credit resources, credit risks are growth. It keeps the importance of the problem of an increase in the efficiency o...
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Ilyes Abidi,Mariem Nsaibi,Boutheina Regaieg
Pág. 69 - 79
The aim of this paper is to study the stability of insurance companies. The majority of works on this topic has focused on the determinants of financial stability. Therefore, they interested in the Z-score, focused on the ROA, as well as the panel method...
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Beibei Niu, Jinzheng Ren and Xiaotao Li
Financial institutions use credit scoring to evaluate potential loan default risks. However, insufficient credit information limits the peer-to-peer (P2P) lending platform?s capacity to build effective credit scoring. In recent years, many types of data ...
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