IDEAS home Printed from https://ideas.repec.org/f/pal1095.html
   My authors  Follow this author

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, Spain
http://www.bde.es/
RePEc:edi:bdegves (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Andrés Alonso-Robisco & José Manuel Carbó & Pedro Jesús Cuadros-Solas & Jara Quintanero, 2025. "The effects of open banking on fintech providers: evidence using microdata from Spain," Working Papers 2514, Banco de España.
  2. Andrés Alonso-Robisco & Andrés Azqueta-Gavaldón & José Manuel Carbó & José Luis González & Ana Isabel Hernáez & José Luis Herrera & Jorge Quintana & Javier Tarancón, 2025. "Empowering financial supervision: a SupTech experiment using machine learning in an early warning system," Occasional Papers 2504, Banco de España.
  3. Andres Alonso-Robisco & Jose Manuel Carbo & Emily Kormanyos & Elena Triebskorn, 2024. "Houston, we have a problem: can satellite information bridge the climate-related data gap?," Occasional Papers 2428, Banco de España.
  4. Andrés Alonso-Robisco & José Manuel Carbó & José Manuel Marqués, 2023. "Machine Learning methods in climate finance: a systematic review," Working Papers 2310, Banco de España.
  5. Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
  6. 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.
  7. 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.
  8. Andrés Alonso & José Manuel Marqués, 2019. "Financial innovation for a sustainable economy," Occasional Papers 1916, Banco de España.
  9. Andrés Alonso & José Manuel Marqués, 2019. "Innovación financiera para una economía sostenible," Occasional Papers 1916, Banco de España.

Articles

  1. Andres Alonso-Robisco & Javier Bas & Jose Manuel Carbo & Aranzazu de Juan & Jose Manuel Marques, 2025. "Where and how machine learning plays a role in climate finance research," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 15(2), pages 456-497, April.
  2. 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).
  3. 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).
  4. 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.

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

  1. Andres Alonso-Robisco & Jose Manuel Carbo & Emily Kormanyos & Elena Triebskorn, 2024. "Houston, we have a problem: can satellite information bridge the climate-related data gap?," Occasional Papers 2428, Banco de España.

    Cited by:

    1. David Nefzi & Jolien Noels & Romana Peronaci & Christian Schmieder & Ünal Seven & Ömer K Seyhun & Bruno Tissot & Elena Triebskorn, 2025. "Addressing climate change data needs: the global debate and central banks' contribution," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Addressing climate change data needs: the central banks' contribution, volume 63, Bank for International Settlements.

  2. 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:

    1. Yoshida, Valter T. & Schiozer, Rafael & de Genaro, Alan & dos Santos, Toni R.E., 2025. "A novel credit model risk measure: Do more data lead to lower model risk?," The Quarterly Review of Economics and Finance, Elsevier, vol. 100(C).
    2. 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).
    3. 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.
    4. Pedro Guerra & Mauro Castelli, 2021. "Machine Learning Applied to Banking Supervision a Literature Review," Risks, MDPI, vol. 9(7), pages 1-24, July.
    5. 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.
    6. Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
    7. 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.

  3. 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:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    7. 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.
    8. Pedro Guerra & Mauro Castelli, 2021. "Machine Learning Applied to Banking Supervision a Literature Review," Risks, MDPI, vol. 9(7), pages 1-24, July.
    9. 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.
    10. 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.
    11. Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
    12. 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.
    13. 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.

  4. Andrés Alonso & José Manuel Marqués, 2019. "Financial innovation for a sustainable economy," Occasional Papers 1916, Banco de España.

    Cited by:

    1. Clara Isabel González Martínez, 2021. "Overview of global and European institutional sustainable finances initiatives," Economic Bulletin, Banco de España, issue 3/2021.
    2. Cristina Chueca Vergara & Luis Ferruz Agudo, 2021. "Fintech and Sustainability: Do They Affect Each Other?," Sustainability, MDPI, vol. 13(13), pages 1-19, June.
    3. Randall E. Duran & Peter Tierney, 2023. "Fintech Data Infrastructure for ESG Disclosure Compliance," JRFM, MDPI, vol. 16(8), pages 1-19, August.
    4. Ricardo Gimeno & Fernando Sols, 2020. "Incorporating sustainability factors into asset management," Financial Stability Review, Banco de España, issue Autumn.
    5. 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.
    6. Ul-Durar, Shajara & Bakkar, Yassine & Arshed, Noman & Naveed, Shabana & Zhang, Beifan, 2025. "FinTech and economic readiness: Institutional navigation amid climate risks," Research in International Business and Finance, Elsevier, vol. 73(PA).
    7. 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.

  5. Andrés Alonso & José Manuel Marqués, 2019. "Innovación financiera para una economía sostenible," Occasional Papers 1916, Banco de España.

    Cited by:

    1. 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.

Articles

  1. 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).

    Cited by:

    1. Dong, Mengming Michael & Stratopoulos, Theophanis C. & Wang, Victor Xiaoqi, 2024. "A scoping review of ChatGPT research in accounting and finance," International Journal of Accounting Information Systems, Elsevier, vol. 55(C).
    2. Ito, Arata & Sato, Masahiro & Ota, Rui, 2025. "A novel content-based approach to measuring monetary policy uncertainty using fine-tuned LLMs," Finance Research Letters, Elsevier, vol. 75(C).
    3. Wood, Katherine & Pyun, Chaehyun & Pham, Hieu, 2025. "Beyond Green Labels: Assessing Mutual Funds’ ESG Commitments through Large Language Models," Finance Research Letters, Elsevier, vol. 74(C).
    4. Julian Junyan Wang & Victor Xiaoqi Wang, 2025. "Assessing Consistency and Reproducibility in the Outputs of Large Language Models: Evidence Across Diverse Finance and Accounting Tasks," Papers 2503.16974, arXiv.org, revised Jun 2025.
    5. Chong Zhang & Xinyi Liu & Zhongmou Zhang & Mingyu Jin & Lingyao Li & Zhenting Wang & Wenyue Hua & Dong Shu & Suiyuan Zhu & Xiaobo Jin & Sujian Li & Mengnan Du & Yongfeng Zhang, 2024. "When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments," Papers 2407.18957, arXiv.org, revised Sep 2024.
    6. Can Celebi & Stefan Penczynski, 2024. "Using Large Language Models for Text Classification in Experimental Economics," Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) 24-01, School of Economics, University of East Anglia, Norwich, UK..
    7. Arata ITO & Masahiro SATO & Rui OTA, 2024. "Content-based Metric on Monetary Policy Uncertainty by Using Large Language Models," Discussion papers 24080, Research Institute of Economy, Trade and Industry (RIETI).
    8. Wu, WenTing & Chen, XiaoQian & Zvarych, Roman & Huang, WeiLun, 2024. "The Stackelberg duel between Central Bank Digital Currencies and private payment titans in China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

  2. 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:

    1. 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).
    2. 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).
    3. Cosma, Simona & Rimo, Giuseppe & Torluccio, Giuseppe, 2023. "Knowledge mapping of model risk in banking," International Review of Financial Analysis, Elsevier, vol. 89(C).
    4. Riyadh Mehdi & Ibrahim Elsiddig Ahmed & Elfadil A. Mohamed, 2025. "Rating the Impact of Risks in Banking on Performance: Utilizing the Adaptive Neural Network-Based Fuzzy Inference System (ANFIS)," Risks, MDPI, vol. 13(5), pages 1-23, April.

  3. 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:

    1. Mingchen Li & Kun Yang & Wencan Lin & Yunjie Wei & Shouyang Wang, 2024. "An interval constraint-based trading strategy with social sentiment for the stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-31, December.
    2. 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).
    3. Blanco-Oliver Antonio & Lara-Rubio Juan & Irimia-Diéguez Ana & Liébana-Cabanillas Francisco, 2024. "Examining user behavior with machine learning for effective mobile peer-to-peer payment adoption," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-30, December.
    4. 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.
    5. 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.
    6. Cristiana Tudor & Robert Sova, 2025. "An automated adaptive trading system for enhanced performance of emerging market portfolios," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-39, December.
    7. Gang Kou & Yang Lu, 2025. "FinTech: a literature review of emerging financial technologies and applications," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-34, December.
    8. 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).
    9. Calabrese, G.G. & Falavigna, G. & Ippoliti, R., 2024. "Financial constraints prediction to lead socio-economic development: An application of neural networks to the Italian market," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 9 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.
  1. NEP-BIG: Big Data (5) 2020-11-16 2021-03-15 2022-08-29 2023-05-22 2025-04-07. Author is listed
  2. NEP-CMP: Computational Economics (4) 2020-11-16 2021-03-15 2022-08-29 2025-04-07. Author is listed
  3. NEP-RMG: Risk Management (4) 2020-11-16 2021-03-15 2021-03-29 2025-04-07. Author is listed
  4. NEP-ENV: Environmental Economics (3) 2019-10-07 2021-03-29 2023-05-22. Author is listed
  5. NEP-PAY: Payment Systems and Financial Technology (3) 2020-11-16 2022-08-29 2025-03-03. Author is listed
  6. NEP-ENE: Energy Economics (2) 2023-05-22 2024-09-16
  7. NEP-SBM: Small Business Management (2) 2021-03-29 2025-03-03
  8. NEP-AGR: Agricultural Economics (1) 2024-09-16
  9. NEP-BAN: Banking (1) 2020-11-16
  10. NEP-CBA: Central Banking (1) 2024-09-16
  11. NEP-FDG: Financial Development and Growth (1) 2025-04-07
  12. NEP-FMK: Financial Markets (1) 2020-11-16
  13. NEP-NET: Network Economics (1) 2025-04-07

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Andres Alonso should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.