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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Interpretable selective learning in credit risk
Dangxing Chen, Jiahui Ye, Weicheng Ye
Research in International Business and Finance (2023) Vol. 65, pp. 101940-101940
Open Access | Times Cited: 16

Showing 16 citing articles:

Safeguarding FinTech innovations with machine learning: Comparative assessment of various approaches
Nawazish Mirza, Mohamed Elhoseny, Muhammad Umar, et al.
Research in International Business and Finance (2023) Vol. 66, pp. 102009-102009
Closed Access | Times Cited: 24
Interpretability Research of Deep Learning: A Literature Survey
Biao Xu, Guanci Yang
Information Fusion (2024) Vol. 115, pp. 102721-102721
Closed Access | Times Cited: 11
Uncovering Research Trends on Artificial Intelligence Risk Assessment in Businesses: A State-of-the-Art Perspective Using Bibliometric Analysis
Juan Carlos Muria-Tarazón, Juan Vicente Oltra Gutiérrez, Raúl Oltra-Badenes, et al.
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1412-1412
Open Access
Artificial Intelligence in banking services. A bibliometric review
Sergio Gerardo Padilla Hernández
Región Científica (2024)
Open Access | Times Cited: 4
Explainable Artificial Intelligence (XAI): A Systematic Literature Review on Taxonomies and Applications in Finance
Tiago Martins, Ana de Almeida, Elsa Cardoso, et al.
IEEE Access (2023) Vol. 12, pp. 618-629
Open Access | Times Cited: 10
Novel embedding model predicting the credit card's default using neural network optimized by harmony search algorithm and vortex search algorithm
Tianpei Xu, Min Qu
Heliyon (2024) Vol. 10, Iss. 9, pp. e30134-e30134
Open Access | Times Cited: 1
Improvements in the Characterisation of Permeability and Inertial Factor of Insect-Proof Screens through Pressure Drop Coefficients
Francisco-Javier Granados-Ortiz, A. López, F.D. Molina-Aiz, et al.
Agronomy (2023) Vol. 13, Iss. 2, pp. 602-602
Open Access | Times Cited: 2
Financial Time Series Modelling Using Fractal Interpolation Functions
Polychronis Manousopoulos, Vasileios Drakopoulos, Efstathios Polyzos
AppliedMath (2023) Vol. 3, Iss. 3, pp. 510-524
Open Access | Times Cited: 2
Prediction and assessment of credit risk using an adaptive Binarized spiking marine predators’ neural network in financial sector
Vadipina Amarnadh, Nageswara Rao Moparthi
Multimedia Tools and Applications (2023) Vol. 83, Iss. 16, pp. 48761-48797
Closed Access | Times Cited: 2
How can Consumers Without Credit History Benefit from the Use of Information Processing and Machine Learning Tools by Financial Institutions?
Marcos Machado, Joerg Osterrieder, Bjoern van Braak
SSRN Electronic Journal (2024)
Closed Access
A novel framework for enhancing transparency in credit scoring: Leveraging Shapley values for interpretable credit scorecards
Rivalani Hlongwane, Kutlwano Ramabao, Wilson Tsakane Mongwe
PLoS ONE (2024) Vol. 19, Iss. 8, pp. e0308718-e0308718
Open Access
Class Imbalance Bayesian Model Averaging for Consumer Loan Default Prediction: The Role of Soft Credit Information
Futian Weng, Miao Zhu, Mike Buckle, et al.
Research in International Business and Finance (2024), pp. 102722-102722
Open Access
SAFENet: Towards a Robust Suicide Assessment in Social Media Using Selective Prediction Framework
Surendrabikram Thapa, Mohammad Salman, Siddhant Bikram Shah, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 660-669
Closed Access
How Can Credit Scoring Benefit from Machine Learning? SWOT Analysis
Oussama Bentounsi, Hajar Mouatassim Lahmini
Lecture notes in networks and systems (2024), pp. 156-165
Closed Access
How can consumers without credit history benefit from the use of information processing and machine learning tools by financial institutions?
Bjorn van Braak, Joerg Osterrieder, Marcos Machado
Information Processing & Management (2024) Vol. 62, Iss. 2, pp. 103972-103972
Open Access
Credit Risk Assessment System Based on Deep Learning: A Systematic Literature Review
Sandra Paola Hoyos Gutiérrez, Félix Melchor Santos López
Lecture notes in networks and systems (2024), pp. 395-413
Closed Access
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