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A brief review of machine learning and its application
H Wang, C Ma, L Zhou - 2009 international conference on …, 2009 - ieeexplore.ieee.org
With the popularization of information and the establishment of the databases in great
number, and how to extract data from the useful information is the urgent problem to be …
number, and how to extract data from the useful information is the urgent problem to be …
MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare …
Assessing and ranking private health insurance companies provides insurance agencies,
insurance customers, and authorities with a reliable instrument for the insurance decision …
insurance customers, and authorities with a reliable instrument for the insurance decision …
[HTML][HTML] The many Shapley values for explainable artificial intelligence: A sensitivity analysis perspective
Predictive models are increasingly used for managerial and operational decision-making.
The use of complex machine learning algorithms, the growth in computing power, and the …
The use of complex machine learning algorithms, the growth in computing power, and the …
Failure prediction of Indian Banks using SMOTE, Lasso regression, bagging and boosting
Banks have a vital role in the financial system and its survival is crucial for the stability of the
economy. This research paper attempts to create an efficient and appropriate predictive …
economy. This research paper attempts to create an efficient and appropriate predictive …
[KÖNYV][B] Enterprise risk management in supply chains
Enterprise risk management began focusing on financial factors. After the corporate
scandals in the US in the early 2000s, accounting aspects grew in importance. This chapter …
scandals in the US in the early 2000s, accounting aspects grew in importance. This chapter …
Performance determinants of non-life insurance firms: a systematic review of the literature
The performance of non-life insurers is essential to the economy because of their role in
mitigating the risks firms and households face. This study provides a comprehensive …
mitigating the risks firms and households face. This study provides a comprehensive …
Machine learning models and cost-sensitive decision trees for bond rating prediction
Since the outbreak of the financial crisis, the major global credit rating agencies have
implemented significant changes to their methodologies to assess the sovereign credit risk …
implemented significant changes to their methodologies to assess the sovereign credit risk …
A multicriteria approach for modeling small enterprise credit rating: evidence from China
N Chai, B Wu, W Yang, B Shi - Emerging Markets Finance and …, 2019 - Taylor & Francis
As the engine of China's economy, small enterprises have been the central to the country's
economic development. However, given the characteristics of the small enterprises loan (ie …
economic development. However, given the characteristics of the small enterprises loan (ie …
Hybrid models based on rough set classifiers for setting credit rating decision rules in the global banking industry
YS Chen, CH Cheng - Knowledge-Based Systems, 2013 - Elsevier
Banks are important to national, and even global, economic stability. Banking panics that
follow bank insolvency or bankruptcy, especially of large banks, can severely jeopardize …
follow bank insolvency or bankruptcy, especially of large banks, can severely jeopardize …
Credit rating and microfinance lending decisions based on loss given default (LGD)
B Shi, X Zhao, B Wu, Y Dong - Finance Research Letters, 2019 - Elsevier
This paper proposes a credit rating model that considers the impact of key macroeconomic
variables on commercial banks' credit decisions and loss given default (LGD). The findings …
variables on commercial banks' credit decisions and loss given default (LGD). The findings …