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 …

MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare …

F Ecer, D Pamucar - Applied Soft Computing, 2021 - pmc.ncbi.nlm.nih.gov
Assessing and ranking private health insurance companies provides insurance agencies,
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

E Borgonovo, E Plischke, G Rabitti - European Journal of Operational …, 2024 - Elsevier
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 …

Failure prediction of Indian Banks using SMOTE, Lasso regression, bagging and boosting

S Shrivastava, PM Jeyanthi, S Singh - Cogent Economics & …, 2020 - Taylor & Francis
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 …

[KÖNYV][B] Enterprise risk management in supply chains

DL Olson, DD Wu, DL Olson, DD Wu - 2017 - Springer
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 …

Performance determinants of non-life insurance firms: a systematic review of the literature

T Zinyoro, MJ Aziakpono - Cogent Business & Management, 2024 - Taylor & Francis
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 …

Machine learning models and cost-sensitive decision trees for bond rating prediction

SB Jabeur, A Sadaaoui, A Sghaier… - Journal of the …, 2020 - Taylor & Francis
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 …

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 …

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 …

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 …