IDEAS home Printed from https://ideas.repec.org/a/gam/jfinte/v4y2025i3p31-d1704560.html

Credit Sales and Risk Scoring: A FinTech Innovation

Author

Listed:
  • Faten Ben Bouheni

    (Department of Finance and Real Estate, Menlo College, Atherton, CA 94027, USA)

  • Manish Tewari

    (Department of Finance, Menlo College, Atherton, CA 94027, USA)

  • Andrew Salamon

    (Bloomberg, San Francisco, CA 94105, USA)

  • Payson Johnston

    (School of Business, University of Tennessee Southern, Pulaski, TN 38478, USA)

  • Kevin Hopkins

    (Economist, Kevin Hopkins Inc., Sandy, UT 84092, USA)

Abstract

This paper explores the effectiveness of an innovative FinTech risk-scoring model to predict the risk-appropriate return for short-term credit sales. The risk score serves to mitigate the information asymmetry between the seller of receivables (“Seller”) and the purchaser (“Funder”), at the same time providing an opportunity for the Funder to earn returns as well as to diversify its portfolio on a risk-appropriate basis. Selling receivables/credit to potential Funders at a risk-appropriate discount also helps Sellers to maintain their short-term financial liquidity and provide the necessary cash flow for operations and other immediate financial needs. We use 18,304 short-term credit-sale transactions between 23 April 2020 and 30 September 2022 from the private FinTech startup Crowdz and its Sustainability, Underwriting, Risk & Financial (SURF) risk-scoring system to analyze the risk/return relationship. The data includes risk scores for both Sellers of receivables (e.g., invoices) along with the Obligors (firms purchasing goods and services from the Seller) on those receivables and provides, as outputs, the mutual gains by the Sellers and the financial institutions or other investors funding the receivables (i.e., the Funders). Our analysis shows that the SURF Score is instrumental in mitigating the information asymmetry between the Sellers and the Funders and provides risk-appropriate periodic returns to the Funders across industries. A comparative analysis shows that the use of SURF technology generates higher risk-appropriate annualized internal rates of return (IRR) as compared to nonuse of the SURF Score risk-scoring system in these transactions. While Sellers and Funders enter into a win-win relationship (in the absence of a default), Sellers of credit instruments are not often scored based on the potential diversification by industry classification. Crowdz’s SURF technology does so and provides Funders with diversification opportunities through numerous invoices of differing amounts and SURF Scores in a wide range of industries. The analysis also shows that Sellers generally have lower financing stability as compared to the Obligors (payers on receivables), a fact captured in the SURF Scores.

Suggested Citation

  • Faten Ben Bouheni & Manish Tewari & Andrew Salamon & Payson Johnston & Kevin Hopkins, 2025. "Credit Sales and Risk Scoring: A FinTech Innovation," FinTech, MDPI, vol. 4(3), pages 1-29, July.
  • Handle: RePEc:gam:jfinte:v:4:y:2025:i:3:p:31-:d:1704560
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2674-1032/4/3/31/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2674-1032/4/3/31/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stohs, Mark Hoven & Mauer, David C, 1996. "The Determinants of Corporate Debt Maturity Structure," The Journal of Business, University of Chicago Press, vol. 69(3), pages 279-312, July.
    2. Diamond, Douglas W, 1991. "Monitoring and Reputation: The Choice between Bank Loans and Directly Placed Debt," Journal of Political Economy, University of Chicago Press, vol. 99(4), pages 689-721, August.
    3. Berger, Allen N & Frame, W Scott & Miller, Nathan H, 2005. "Credit Scoring and the Availability, Price, and Risk of Small Business Credit," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(2), pages 191-222, April.
    4. Allen Berger & Adrian Cowan & W. Frame, 2011. "The Surprising Use of Credit Scoring in Small Business Lending by Community Banks and the Attendant Effects on Credit Availability, Risk, and Profitability," Journal of Financial Services Research, Springer;Western Finance Association, vol. 39(1), pages 1-17, April.
    5. Allen N. Berger & Marco A. Espinosa‐Vega & W. Scott Frame & Nathan H. Miller, 2005. "Debt Maturity, Risk, and Asymmetric Information," Journal of Finance, American Finance Association, vol. 60(6), pages 2895-2923, December.
    6. Faten Ben Bouheni & Manish Tewari, 2023. "Common risk factors and risk–return trade-off for REITs and treasuries," Journal of Asset Management, Palgrave Macmillan, vol. 24(5), pages 374-395, September.
    7. Şenay Ağca & John R. Birge & Zi'ang Wang & Jing Wu, 2023. "The impact of COVID‐19 on supply chain credit risk," Production and Operations Management, Production and Operations Management Society, vol. 32(12), pages 4088-4113, December.
    8. Amir Sufi, 2007. "Information Asymmetry and Financing Arrangements: Evidence from Syndicated Loans," Journal of Finance, American Finance Association, vol. 62(2), pages 629-668, April.
    9. Barclay, Michael J & Smith, Clifford W, Jr, 1995. "The Maturity Structure of Corporate Debt," Journal of Finance, American Finance Association, vol. 50(2), pages 609-631, June.
    10. Faten Ben Bouheni & Manish Tewari & Mouwafac Sidaoui & Amir Hasnaoui, 2023. "An econometric understanding of Fintech and operating performance," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 22(3), pages 329-352, May.
    Full references (including those not matched with items on IDEAS)

    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. Graham, John R. & Li, Si & Qiu, Jiaping, 2008. "Corporate misreporting and bank loan contracting," Journal of Financial Economics, Elsevier, vol. 89(1), pages 44-61, July.
    2. Ca Nguyen & John K. Wald, 2022. "Debt maturity and the choice between bank loans and public bonds," Review of Quantitative Finance and Accounting, Springer, vol. 59(1), pages 239-272, July.
    3. Ovtchinnikov, Alexei V., 2016. "Debt decisions in deregulated industries," Journal of Corporate Finance, Elsevier, vol. 36(C), pages 230-254.
    4. Tanaka, Takanori, 2016. "How do managerial incentives affect the maturity structure of corporate public debt?," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 130-146.
    5. Allen N. Berger & Tanakorn Makaew & Raluca Roman, 2015. "Did bank borrowers benefit from the TARP program : the effects of TARP on loan contract terms," Research Working Paper RWP 15-11, Federal Reserve Bank of Kansas City.
    6. Mian, Atif & Santos, João A.C., 2018. "Liquidity risk and maturity management over the credit cycle," Journal of Financial Economics, Elsevier, vol. 127(2), pages 264-284.
    7. Silvia Magri, 2010. "Debt Maturity Choice of Nonpublic Italian Firms," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(2‐3), pages 443-463, March.
    8. Parise, Gianpaolo, 2018. "Threat of entry and debt maturity: Evidence from airlines," Journal of Financial Economics, Elsevier, vol. 127(2), pages 226-247.
    9. Wu, Julia Yonghua & Opare, Solomon & Bhuiyan, Md. Borhan Uddin & Habib, Ahsan, 2022. "Determinants and consequences of debt maturity structure: A systematic review of the international literature," International Review of Financial Analysis, Elsevier, vol. 84(C).
    10. David Abad & Juan Pedro Sánchez-Ballesta & José Yagüe, 2017. "The short-term debt choice under asymmetric information," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 8(3), pages 261-285, August.
    11. Adrian Van Rixtel & Luna Romo González & Jing Yang, 2015. "The determinants of long-term debt issuance by European banks: evidence of two crises," BIS Working Papers 513, Bank for International Settlements.
    12. Quijano, Margot, 2013. "Financial fragility, uninsured deposits, and the cost of debt," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 159-175.
    13. Yener Altunbas & Alper Kara & David Marques-Ibanez, 2010. "Large debt financing: syndicated loans versus corporate bonds," The European Journal of Finance, Taylor & Francis Journals, vol. 16(5), pages 437-458.
    14. Silvia Magri, 2006. "Debt maturity of Italian firms," Temi di discussione (Economic working papers) 574, Bank of Italy, Economic Research and International Relations Area.
    15. Custódio, Cláudia & Ferreira, Miguel A. & Laureano, Luís, 2013. "Why are US firms using more short-term debt?," Journal of Financial Economics, Elsevier, vol. 108(1), pages 182-212.
    16. Wenlian Gao & Feifei Zhu & Kai Chen, 2023. "The role of bank lenders in firm leverage adjustments," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(1), pages 63-97, February.
    17. Chen, Andrew H. & Mazumdar, Sumon C. & Yan, Yuxing, 2000. "Monitoring and bank loan pricing," Pacific-Basin Finance Journal, Elsevier, vol. 8(1), pages 1-24, March.
    18. Emanuele Brancati & Marco Macchiavelli, 2020. "Endogenous debt maturity and rollover risk," Financial Management, Financial Management Association International, vol. 49(1), pages 69-90, March.
    19. Cai, Jun & Cheung, Yan-Leung & Goyal, Vidhan K., 1999. "Bank monitoring and the maturity structure of Japanese corporate debt issues," Pacific-Basin Finance Journal, Elsevier, vol. 7(3-4), pages 229-249, August.
    20. Daniševská, P. & de Jong, A. & Verbeek, M.J.C.M., 2004. "Do Banks Influence the Capital Structure Choices of Firms?," ERIM Report Series Research in Management ERS-2004-040-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jfinte:v:4:y:2025:i:3:p:31-:d:1704560. 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.