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FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk

Citations

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Cited by:

  1. Wosnitza, Jan Henrik, 2022. "Calibration alternatives to logistic regression and their potential for transferring the dispersion of discriminatory power into uncertainties of probabilities of default," Discussion Papers 04/2022, Deutsche Bundesbank.
  2. De Fiore, Fiorella & Gambacorta, Leonardo & Manea, Cristina, 2023. "Big Techs and the Credit Channel of Monetary Policy," CEPR Discussion Papers 18217, C.E.P.R. Discussion Papers.
  3. Leonardo Gambacorta & Yiping Huang & Zhenhua Li & Han Qiu & Shu Chen, 2020. "Data vs collateral," BIS Working Papers 881, Bank for International Settlements.
  4. Md Qamruzzaman, 2023. "Does financial innovation foster financial inclusion in Arab world? examining the nexus between financial innovation, FDI, remittances, trade openness, and gross capital formation," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-28, June.
  5. Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2024. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from the Lasso Regularization and Inferential Techniques," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 144-179, March.
  6. Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021. "Comparing minds and machines: implications for financial stability," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 479-508.
  7. Sourov Ahmed & Marjan Akter Badhon & Mahmudul Hassan Maruf, 2025. "A Survey-Driven Ensemble Approach to Predicting Sovereign Debt Distress in Bangladesh," International Journal of Scientific Research and Modern Technology, Prasu Publications, vol. 4(10), pages 103-114.
  8. Susanna Levantesi & Giulia Zacchia, 2021. "Machine Learning and Financial Literacy: An Exploration of Factors Influencing Financial Knowledge in Italy," JRFM, MDPI, vol. 14(3), pages 1-21, March.
  9. Dmytro Krukovets, 2020. "Data Science Opportunities at Central Banks: Overview," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 249, pages 13-24.
  10. Yang, Zhang & Jianxiong Lin & Yihe Qian & Lianjie Shu, 2025. "Machine learning and financial inclusion: Evidence from credit risk assessment of small-business loans in China," Working Papers 202532, University of Macau, Faculty of Business Administration.
  11. Alfonso-Sánchez, Sherly & Solano, Jesús & Correa-Bahnsen, Alejandro & Sendova, Kristina P. & Bravo, Cristián, 2024. "Optimizing credit limit adjustments under adversarial goals using reinforcement learning," European Journal of Operational Research, Elsevier, vol. 315(2), pages 802-817.
  12. Husam Rjoub & Tomiwa Sunday Adebayo & Dervis Kirikkaleli, 2023. "Blockchain technology-based FinTech banking sector involvement using adaptive neuro-fuzzy-based K-nearest neighbors algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
  13. Zeynep Alraqeb & Peter Knaack & Camille Macaire, 2022. "Does FinTech Promote Entrepreneurship? Evidence from China," Working papers 895, Banque de France.
  14. Bitetto, Alessandro & Cerchiello, Paola & Filomeni, Stefano & Tanda, Alessandra & Tarantino, Barbara, 2023. "Machine learning and credit risk: Empirical evidence from small- and mid-sized businesses," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
  15. Huang, Yiping & Li, Zhenhua & Qiu, Han & Tao, Sun & Wang, Xue & Zhang, Longmei, 2023. "BigTech credit risk assessment for SMEs," China Economic Review, Elsevier, vol. 81(C).
  16. Nartey Menzo, Benjamin Prince & Mogre, Diana & Asuamah Yeboah, Samuel, 2024. "Beyond Income: The Complexities of Credit Risk in Developing Countries," MPRA Paper 122364, University Library of Munich, Germany, revised 20 Sep 2024.
  17. Mansi Yadav & Priyanka Banerji, 2024. "Systematic literature review on Digital Financial Literacy," SN Business & Economics, Springer, vol. 4(11), pages 1-25, November.
  18. Narayanamurthy, Gopalakrishnan & Jayanth, R Sai Shiva & Moser, Roger & Schaefers, Tobias & Nagendra, Narayan Prasad, 2025. "Data-driven digital transformation for uncertainty reduction – Application of satellite imagery analytics in institutional crop credit management," International Journal of Production Economics, Elsevier, vol. 280(C).
  19. Tanja Verster & Erika Fourie, 2023. "The Changing Landscape of Financial Credit Risk Models," IJFS, MDPI, vol. 11(3), pages 1-15, August.
  20. Mirza, Nawazish & Elhoseny, Mohamed & Umar, Muhammad & Metawa, Noura, 2023. "Safeguarding FinTech innovations with machine learning: Comparative assessment of various approaches," Research in International Business and Finance, Elsevier, vol. 66(C).
  21. Sant'Anna, Dário A.L.M. & Figueiredo, Paulo N., 2024. "Fintech innovation: Is it beneficial or detrimental to financial inclusion and financial stability? A systematic literature review and research directions," Emerging Markets Review, Elsevier, vol. 60(C).
  22. Stefanos Balaskas & Maria Koutroumani & Kiriakos Komis & Maria Rigou, 2024. "FinTech Services Adoption in Greece: The Roles of Trust, Government Support, and Technology Acceptance Factors," FinTech, MDPI, vol. 3(1), pages 1-19, January.
  23. Jaewon Park & Minsoo Shin & Wookjae Heo, 2021. "Estimating the BIS Capital Adequacy Ratio for Korean Banks Using Machine Learning: Predicting by Variable Selection Using Random Forest Algorithms," Risks, MDPI, vol. 9(2), pages 1-19, February.
  24. Alessandro Bitetto & Paola Cerchiello & Stefano Filomeni & Alessandra Tanda & Barbara Tarantino, 2021. "Machine Learning and Credit Risk: Empirical Evidence from SMEs," DEM Working Papers Series 201, University of Pavia, Department of Economics and Management.
  25. Seongil Han & Haemin Jung, 2024. "NATE: Non-pArameTric approach for Explainable credit scoring on imbalanced class," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-24, December.
  26. Andrés Alonso Robisco & José Manuel Carbó Martínez, 2022. "Measuring the model risk-adjusted performance of machine learning algorithms in credit default prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-35, December.
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