Andres Alonso
Personal Details
First Name: | Andres |
Middle Name: | |
Last Name: | Alonso |
Suffix: | |
RePEc Short-ID: | pal1095 |
[This author has chosen not to make the email address public] | |
https://www.bde.es/investigador/en/menu/people/research_staff_a/alonso-robisco--andres.html | |
Affiliation
Banco de España
Madrid, Spainhttp://www.bde.es/
RePEc:edi:bdegves (more details at EDIRC)
Research output
Jump to: Working papers ArticlesWorking papers
- Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
- Andrés Alonso & José Manuel Carbó, 2021. "Understanding the performance of machine learning models to predict credit default: a novel approach for supervisory evaluation," Working Papers 2105, Banco de España.
- Andrés Alonso & José Manuel Carbó, 2020. "Machine learning in credit risk: measuring the dilemma between prediction and supervisory cost," Working Papers 2032, Banco de España.
- Andrés Alonso & José Manuel Marqués, 2019. "Innovación financiera para una economía sostenible," Occasional Papers 1916, Banco de España.
- Andrés Alonso & José Manuel Marqués, 2019. "Financial innovation for a sustainable economy," Occasional Papers 1916, Banco de España.
Articles
- Alonso-Robisco, Andres & Carbó, José Manuel, 2023. "Analysis of CBDC narrative by central banks using large language models," Finance Research Letters, Elsevier, vol. 58(PC).
- 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.
- Alonso-Robisco, Andrés & Carbó, José Manuel, 2022. "Can machine learning models save capital for banks? Evidence from a Spanish credit portfolio," International Review of Financial Analysis, Elsevier, vol. 84(C).
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Working papers
- Andrés Alonso & José Manuel Carbó, 2021.
"Understanding the performance of machine learning models to predict credit default: a novel approach for supervisory evaluation,"
Working Papers
2105, Banco de España.
Cited by:
- Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2023.
"Revisiting SME default predictors: The Omega Score,"
Journal of Small Business Management, Taylor & Francis Journals, vol. 61(6), pages 2383-2417, November.
- Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2022. "Revisiting SME default predictors: The Omega Score," Working Papers 2022-19, Faculty of Economics and Statistics, Universität Innsbruck.
- Altman, Edward I. & Balzano, Marco & Giannozzi, Alessandro & Srhoj, Stjepan, 2022. "Revisiting SME default predictors: The Omega Score," GLO Discussion Paper Series 1207, Global Labor Organization (GLO).
- Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
- Pedro Guerra & Mauro Castelli, 2021. "Machine Learning Applied to Banking Supervision a Literature Review," Risks, MDPI, vol. 9(7), pages 1-24, July.
- Ryuichiro Hashimoto & Kakeru Miura & Yasunori Yoshizaki, 2023. "Application of Machine Learning to a Credit Rating Classification Model: Techniques for Improving the Explainability of Machine Learning," Bank of Japan Working Paper Series 23-E-6, Bank of Japan.
- 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.
- Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2023.
"Revisiting SME default predictors: The Omega Score,"
Journal of Small Business Management, Taylor & Francis Journals, vol. 61(6), pages 2383-2417, November.
- Andrés Alonso & José Manuel Carbó, 2020.
"Machine learning in credit risk: measuring the dilemma between prediction and supervisory cost,"
Working Papers
2032, Banco de España.
Cited by:
- 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.
- Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
- Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
- Pedro Guerra & Mauro Castelli, 2021. "Machine Learning Applied to Banking Supervision a Literature Review," Risks, MDPI, vol. 9(7), pages 1-24, July.
- Andrés Alonso & José Manuel Carbó, 2021. "Understanding the performance of machine learning models to predict credit default: a novel approach for supervisory evaluation," Working Papers 2105, Banco de España.
- Faraz Ahmed & Kehkashan Nizam & Zubair Sajid & Sunain Qamar & Ahsan, 2024. "Striking a Balance: Evaluating Credit Risk with Traditional and Machine Learning Models," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 13(3), pages 30-35.
- Valter T. Yoshida Jr & Alan de Genaro & Rafael Schiozer & Toni R. E. dos Santos, 2023. "A Novel Credit Model Risk Measure: does more data lead to lower model risk in credit scoring models?," Working Papers Series 582, Central Bank of Brazil, Research Department.
- Giuseppe Cascarino & Mirko Moscatelli & Fabio Parlapiano, 2022. "Explainable Artificial Intelligence: interpreting default forecasting models based on Machine Learning," Questioni di Economia e Finanza (Occasional Papers) 674, Bank of Italy, Economic Research and International Relations Area.
- Zixue Zhao & Tianxiang Cui & Shusheng Ding & Jiawei Li & Anthony Graham Bellotti, 2024. "Resampling Techniques Study on Class Imbalance Problem in Credit Risk Prediction," Mathematics, MDPI, vol. 12(5), pages 1-27, February.
- Dimitrios Nikolaidis & Michalis Doumpos, 2022. "Credit Scoring with Drift Adaptation Using Local Regions of Competence," SN Operations Research Forum, Springer, vol. 3(4), pages 1-28, December.
- Antonietta di Salvatore & Mirko Moscatelli, 2024. "Improving survey information on household debt using granular credit databases," Questioni di Economia e Finanza (Occasional Papers) 839, Bank of Italy, Economic Research and International Relations Area.
- Lisa Crosato & Caterina Liberati & Marco Repetto, 2021. "Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default," Papers 2108.13914, arXiv.org, revised Sep 2021.
- Pedro Guerra & Mauro Castelli & Nadine Côrte-Real, 2022. "Approaching European Supervisory Risk Assessment with SupTech: A Proposal of an Early Warning System," Risks, MDPI, vol. 10(4), pages 1-23, March.
- Andrés Alonso & José Manuel Marqués, 2019.
"Innovación financiera para una economía sostenible,"
Occasional Papers
1916, Banco de España.
Cited by:
- Esther Ortiz-Martínez & Salvador Marín-Hernández, 2020. "European Financial Services SMEs: Language in Their Sustainability Reporting," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
- Andrés Alonso & José Manuel Marqués, 2019.
"Financial innovation for a sustainable economy,"
Occasional Papers
1916, Banco de España.
Cited by:
- Cristina Chueca Vergara & Luis Ferruz Agudo, 2021. "Fintech and Sustainability: Do They Affect Each Other?," Sustainability, MDPI, vol. 13(13), pages 1-19, June.
- Randall E. Duran & Peter Tierney, 2023. "Fintech Data Infrastructure for ESG Disclosure Compliance," JRFM, MDPI, vol. 16(8), pages 1-19, August.
- Ricardo Gimeno & Fernando Sols, 2020. "Incorporating sustainability factors into asset management," Financial Stability Review, Banco de España, issue Autumn.
- Clara Isabel González Martínez, 2021. "Overview of global and European institutional sustainable finances initiatives," Economic Bulletin, Banco de España, issue 3/2021.
- 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.
- Clara Isabel González Martínez, 2021. "The role of central banks in combating climate change and developing sustainable finance," Economic Bulletin, Banco de España, issue 3/2021.
Articles
- 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.
Cited by:
- Faraz Ahmed & Kehkashan Nizam & Zubair Sajid & Sunain Qamar & Ahsan, 2024. "Striking a Balance: Evaluating Credit Risk with Traditional and Machine Learning Models," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 13(3), pages 30-35.
- González, Marta Ramos & Ureña, Antonio Partal & Fernández-Aguado, Pilar Gómez, 2023. "Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 64(C).
- Ryuichiro Hashimoto & Kakeru Miura & Yasunori Yoshizaki, 2023. "Application of Machine Learning to a Credit Rating Classification Model: Techniques for Improving the Explainability of Machine Learning," Bank of Japan Working Paper Series 23-E-6, Bank of Japan.
- Alonso-Robisco, Andrés & Carbó, José Manuel, 2022. "Can machine learning models save capital for banks? Evidence from a Spanish credit portfolio," International Review of Financial Analysis, Elsevier, vol. 84(C).
- Alonso-Robisco, Andrés & Carbó, José Manuel, 2022.
"Can machine learning models save capital for banks? Evidence from a Spanish credit portfolio,"
International Review of Financial Analysis, Elsevier, vol. 84(C).
Cited by:
- Cosma, Simona & Rimo, Giuseppe & Torluccio, Giuseppe, 2023. "Knowledge mapping of model risk in banking," International Review of Financial Analysis, Elsevier, vol. 89(C).
- F. Bolivar & Miguel A. Duran & A. Lozano-Vivas, 2024.
"Business Model Contributions to Bank Profit Performance: A Machine Learning Approach,"
Papers
2401.12334, arXiv.org.
- Bolívar, Fernando & Duran, Miguel A. & Lozano-Vivas, Ana, 2023. "Business model contributions to bank profit performance: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 64(C).
- Zhou, Ying & Shen, Long & Ballester, Laura, 2023. "A two-stage credit scoring model based on random forest: Evidence from Chinese small firms," International Review of Financial Analysis, Elsevier, vol. 89(C).
More information
Research fields, statistics, top rankings, if available.Statistics
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NEP Fields
NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 5 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.- NEP-BIG: Big Data (3) 2020-11-16 2021-03-15 2022-08-29. Author is listed
- NEP-CMP: Computational Economics (3) 2020-11-16 2021-03-15 2022-08-29. Author is listed
- NEP-RMG: Risk Management (3) 2020-11-16 2021-03-15 2021-03-29. Author is listed
- NEP-ENV: Environmental Economics (2) 2019-10-07 2021-03-29. Author is listed
- NEP-PAY: Payment Systems and Financial Technology (2) 2020-11-16 2022-08-29. Author is listed
- NEP-BAN: Banking (1) 2020-11-16
- NEP-FMK: Financial Markets (1) 2020-11-16
- NEP-SBM: Small Business Management (1) 2021-03-29
Corrections
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