Machine learning in banking risk management: A literature review
M Leo, S Sharma, K Maddulety - Risks, 2019 - mdpi.com
There is an increasing influence of machine learning in business applications, with many
solutions already implemented and many more being explored. Since the global financial …
solutions already implemented and many more being explored. Since the global financial …
An empirical comparison of machine-learning methods on bank client credit assessments
L Munkhdalai, T Munkhdalai, OE Namsrai, JY Lee… - Sustainability, 2019 - mdpi.com
Machine learning and artificial intelligence have achieved a human-level performance in
many application domains, including image classification, speech recognition and machine …
many application domains, including image classification, speech recognition and machine …
Does blockchain technology democratize entrepreneurial finance? An empirical comparison of ICOs, venture capital, and REITs
C Fisch, M Meoli, S Vismara - Innovative Behavior of Minorities …, 2022 - taylorfrancis.com
Initial coin offerings (ICOs) are one of the major innovations that characterize the digital
revolution of financial markets. Among the expectations created by the digital revolution is …
revolution of financial markets. Among the expectations created by the digital revolution is …
Estimating the size of undeclared work from partially misclassified survey data via the Expectation–Maximization algorithm
MF Arezzo, G Guagnano, D Vitale - Journal of the Royal …, 2024 - academic.oup.com
Undeclared work (UW) is pervasive in economies. This explains the interest of public
authorities in knowing its size and drivers. Unfortunately, this is a very complex task because …
authorities in knowing its size and drivers. Unfortunately, this is a very complex task because …
A two-part measurement error model to estimate participation in undeclared work and related earnings
MF Arezzo, S Arima, G Guagnano - Statistical Modelling, 2024 - journals.sagepub.com
In undeclared work research, the estimation of the magnitude of the phenomenon (ie, the
amount of income and/or the percentage of workers involved) is of major interest. This has …
amount of income and/or the percentage of workers involved) is of major interest. This has …
[HTML][HTML] A Bayesian sample selection model with a binary outcome for handling residential self-selection in individual car ownership
H Watanabe, T Maruyama - Journal of choice modelling, 2024 - Elsevier
Existing literature has applied the sample selection modeling approach to disentangle the
influence of the built environment (BE) and residential self-selection (RSS) on travel …
influence of the built environment (BE) and residential self-selection (RSS) on travel …
Stable variable ranking and selection in regularized logistic regression for severely imbalanced big binary data
K Nadeem, MA Jabri - PLoS One, 2023 - journals.plos.org
We develop a novel covariate ranking and selection algorithm for regularized ordinary
logistic regression (OLR) models in the presence of severe class-imbalance in high …
logistic regression (OLR) models in the presence of severe class-imbalance in high …
Risk Management in Financial Institutions with Applied Machine Learning
S Natarajan, P Salgotra, MH Krishna… - 2024 International …, 2024 - ieeexplore.ieee.org
In today's business world, technological applications are becoming more important in
management. Among the most prevalent influencers in business applications are machine …
management. Among the most prevalent influencers in business applications are machine …
[图书][B] SIS 2017. Statistics and Data Science: new challenges, new generations: Proceedings of the Conference of the Italian Statistical Society, Florence 28-30 June …
A Petrucci, R Verde - 2017 - library.oapen.org
The 2017 SIS Conference aims to highlight the crucial role of the Statistics in Data Science.
In this new domain of 'meaning'extracted from the data, the increasing amount of produced …
In this new domain of 'meaning'extracted from the data, the increasing amount of produced …
An Empirical Investigation In Anlysing The Critical Factors Of Machine Learning Towards Risk Management In Banks Using Multivariate Analysis Of Variance (Manova …
DB Haralayya - … Management Journal, 0 [10.57030/23364890. cemj …, 2023 - papers.ssrn.com
The management of modern enterprises is increasingly dependent on various forms of
technological assistance. Applications of machine learning, artificial intelligence, and other …
technological assistance. Applications of machine learning, artificial intelligence, and other …