IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v13y2020i8p180-d398327.html
   My bibliography  Save this article

Use of Machine Learning Techniques to Create a Credit Score Model for Airtime Loans

Author

Listed:
  • Bernard Dushimimana

    (College of Engineering, Carnegie Mellon University Africa, Kigali BP 6150, Rwanda)

  • Yvonne Wambui

    (College of Engineering, Carnegie Mellon University Africa, Kigali BP 6150, Rwanda)

  • Timothy Lubega

    (College of Engineering, Carnegie Mellon University Africa, Kigali BP 6150, Rwanda)

  • Patrick E. McSharry

    (College of Engineering, Carnegie Mellon University Africa, Kigali BP 6150, Rwanda
    African Center of Excellence in Data Science, University of Rwanda, Kigali BP 4285, Rwanda
    Oxford Man Institute of Quantitative Finance, Oxford University, Oxford OX2 6ED, UK)

Abstract

Airtime lending default rates are typically lower than those experienced by banks and microfinance institutions (MFIs) but are likely to grow as the service is offered more widely. In this paper, credit scoring techniques are reviewed, and that knowledge is built upon to create an appropriate machine learning model for airtime lending. Over three million loans belonging to more than 41 thousand customers with a repayment period of three months are analysed. Logistic Regression, Decision Trees and Random Forest are evaluated for their ability to classify defaulters using several cross-validation approaches and the latter model performed best. When the default rate is below 2%, it is better to offer everyone a loan. For higher default rates, the model substantially enhances profitability. The model quadruples the tolerable level of default rate for breaking even from 8% to 32%. Nonlinear classification models offer considerable potential for credit scoring, coping with higher levels of default and therefore allowing for larger volumes of customers.

Suggested Citation

  • Bernard Dushimimana & Yvonne Wambui & Timothy Lubega & Patrick E. McSharry, 2020. "Use of Machine Learning Techniques to Create a Credit Score Model for Airtime Loans," JRFM, MDPI, vol. 13(8), pages 1-11, August.
    • Handle: RePEc:gam:jjrfmx:v:13:y:2020:i:8:p:180-:d:398327
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/13/8/180/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/13/8/180/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jenny C. Aker & Isaac M. Mbiti, 2010. "Mobile Phones and Economic Development in Africa," Journal of Economic Perspectives, American Economic Association, vol. 24(3), pages 207-232, Summer.
    2. William A. Belson, 1959. "Matching and Prediction on the Principle of Biological Classification," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 8(2), pages 65-75, June.
    3. Ibtissem Baklouti, 2013. "Determinants of Microcredit Repayment: The Case of Tunisian Microfinance Bank," African Development Review, African Development Bank, vol. 25(3), pages 370-382, September.
    4. Ibtissem Baklouti, 2013. "Determinants of Microcredit Repayment: The Case of Tunisian Microfinance Bank," African Development Review, African Development Bank, vol. 25(3), pages 370-382.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Omar H. Fares & Irfan Butt & Seung Hwan Mark Lee, 2023. "Utilization of artificial intelligence in the banking sector: a systematic literature review," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(4), pages 835-852, December.
    2. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2023. "Explainable FinTech lending," Journal of Economics and Business, Elsevier, vol. 125.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lucia Dalla Pellegrina & Giorgio Di Maio & Paolo Landoni & Emanuele Rusinà, 2021. "Money management and entrepreneurial training in microfinance: impact on beneficiaries and institutions," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 1049-1085, October.
    2. Namizata Binaté Fofana & Johan A. C. van Ophem & Anke Niehof & Gerrit Antonides, 2014. "Effects of HIV/AIDS and Microfinance of Women on Income, Medical Expenditures and Schooling in Côte d'Ivoire," African Development Review, African Development Bank, vol. 26(2), pages 322-332, June.
    3. Salvador Cruz Rambaud & Joaquín López Pascual & Emilio M. Santandreu, 2023. "A socioeconomic approach to the profile of microcredit holders from the Hispanic minority in the USA," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
    4. Syeda Sonia Parvin & Belayet Hossain & Muhammad Mohiuddin & Qingfeng Cao, 2020. "Capital Structure, Financial Performance, and Sustainability of Micro-Finance Institutions (MFIs) in Bangladesh," Sustainability, MDPI, vol. 12(15), pages 1-18, August.
    5. Jin, Ming & Yin, Mingmei & Chen, Zhongfei, 2021. "Do investors prefer borrowers from high level of trust cities? Evidence from China’s P2P market," Research in International Business and Finance, Elsevier, vol. 58(C).
    6. Andualem Kassegn & Ebrahim Endris, 2022. "Factors affecting loan repayment rate among smallholder farmers got loans from the Amhara Credit and Saving Institution: In the case of Habru District, Amhara Regional State, Ethiopia," International Area Studies Review, Center for International Area Studies, Hankuk University of Foreign Studies, vol. 25(1), pages 73-96, March.
    7. Aminat Olayinka Olohunlana & Ngozi Bosede Adeleye & Somod Dapo Olohunlana & Hauwah K. K. AbdulKareem, 2022. "Gender heterogeneity and microfinance sustainability in Sub‐Saharan Africa," African Development Review, African Development Bank, vol. 34(2), pages 232-243, June.
    8. Dilruba Khanam & Muhammad Mohiuddin & Asadul Hoque & Olaf Weber, 2018. "Financing micro-entrepreneurs for poverty alleviation: a performance analysis of microfinance services offered by BRAC, ASA, and Proshika from Bangladesh," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 8(1), pages 1-17, December.
    9. Jorge Mota & António Carrizo Moreira & Cristóvão Brandão, 2018. "Determinants of microcredit repayment in Portugal: analysis of borrowers, loans and business projects," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 17(3), pages 141-171, November.
    10. Lucia Dalla Pellegrina & Giorgio, Di Maio & Paolo Landoni & Beatrice Rama, 2019. "Activating women cognitive abilities: Impact of a financial literacy pilot program in India," Working Papers 412, University of Milano-Bicocca, Department of Economics, revised May 2019.
    11. Dilruba Khanam & Syeda Sonia Parvin & Muhammad Mohiuddin & Asadul Hoque & Zhan Su, 2018. "Financial Sustainability of Non-Governmental Microfinance Institutions (MFIs): A Cost-Efficiency Analysis of BRAC, ASA, and PROSHIKA from Bangladesh," Review of Economics & Finance, Better Advances Press, Canada, vol. 12, pages 43-56, May.
    12. Christian Lambert Nguena & Roger Tsafack Nanfosso, 2013. "Facteurs Microeconomiques du Deficit de Financement des PME au Cameroun," AAYE Policy Research Working Paper Series 13_004, Association of African Young Economists, revised Nov 2013.
    13. Christian Lambert Nguena et Roger Tsafack Nanfosso, 2014. "Facteurs Microéconomiques du Déficit de Financement des PME au Cameroun," African Development Review, African Development Bank, vol. 26(2), pages 372-383, June.
    14. Bilau, José & St-Pierre, Josée, 2018. "Microcredit repayment in a European context: evidence from Portugal," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 85-96.
    15. Sonia Di Giannatale. & Daniel Ventosa-Santaulària. & María José Roa. & Alexander Elbittar. & Darío Trujano., 2020. "The Role of Cognitive and Personality Characteristics in Timely Microcredit Repayment: Evidence from a Survey Conducted by Provident, Mexico. (El papel de las características cognitivas y de personali," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 1-20, May.
    16. Hubert Tchakoute Tchuigoua, 2021. "Proximity‐based screening tools and credit rationing: Lessons from a Cameroonian greenfield microfinance institution," African Development Review, African Development Bank, vol. 33(3), pages 506-517, September.
    17. Sulin Pang & Huili Xian & Rongzhou Li, 2022. "A default penalty model based on C2VP2C mode for internet financial platforms in Chinese market," Electronic Commerce Research, Springer, vol. 22(2), pages 485-511, June.
    18. Khan, Tahsina & Khanam, Shamsun Nahar & Rahman, Md Habibur & Rahman, Syed Mahbubur, 2019. "Determinants of microfinance facility for installing solar home system (SHS) in rural Bangladesh," Energy Policy, Elsevier, vol. 132(C), pages 299-308.
    19. Richa Agarwal & Ashok Kumar Pokhriyal, 2022. "The moderating effect of attitude to risk on the role of microfinance in entrepreneurship development in Uttarakhand region, India," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 12(1), pages 107-117, December.
    20. Gutiérrez-Romero, Roxana & Ahamed, Mostak, 2021. "COVID-19 response needs to broaden financial inclusion to curb the rise in poverty," World Development, Elsevier, vol. 138(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:13:y:2020:i:8:p:180-:d:398327. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may 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.