IDEAS home Printed from https://ideas.repec.org/p/hal/cesptp/halshs-01391106.html
   My bibliography  Save this paper

Bringing the Customer Back to the Foreground: The End of Conduct Risk?

Author

Listed:
  • Bertrand K. Hassani

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this chapter, we argue that conduct risk arising from the way financial institutions are conducting business with respect to their customers might be prevented, mitigated and potentially annihilated. Indeed, we believe that data science, proper segmentation, product design and control will lead to a tremendous reduction of conduct rusk exposure and a such these topics are addressed here.

Suggested Citation

  • Bertrand K. Hassani, 2016. "Bringing the Customer Back to the Foreground: The End of Conduct Risk?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01391106, HAL.
    • Handle: RePEc:hal:cesptp:halshs-01391106
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01391106
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-01391106/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bertrand K. Hassani, 2016. "Scenario Analysis in Risk Management," Springer Books, Springer, number 978-3-319-25056-4, January.
    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. Bertrand K. Hassani & Alexis Renaudin, 2018. "The Cascade Bayesian Approach: Prior Transformation for a Controlled Integration of Internal Data, External Data and Scenarios," Risks, MDPI, vol. 6(2), pages 1-17, April.
    2. Jozef Klucka & Rudolf Gruenbichler & Jozef Ristvej, 2021. "Relations of COVID-19 and the Risk Management Framework," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    3. Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01592168, HAL.
    4. Williams Kwasi Peprah & Mensah Morris Ayaa, 2022. "The Convergence of Financial Decision, Business Strategy Through Organisational Competitiveness to Sustainable Competitive Advantage: A Conceptual Analysis," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 14(2), pages 1-87, February.
    5. Bertrand K. Hassani, 2016. "Bringing the Customer Black to the Foreground: The End of Conduct Risk?," Documents de travail du Centre d'Economie de la Sorbonne 16067, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    6. E. Nadyrova & Е. Надырова, 2018. "Анализ рисков криптовалют и способы их минимизации в современных рыночных условиях // Analysis of Cryptocurrency Risks and Methods of their Mitigation in Contemporary Market Conditions," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 6(3), pages 65-78.
    7. Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Post-Print halshs-01592168, HAL.
    8. Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Documents de travail du Centre d'Economie de la Sorbonne 17034r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2017.
    9. Horst Treiblmaier, 2021. "Exploring the Next Wave of Blockchain and Distributed Ledger Technology: The Overlooked Potential of Scenario Analysis," Future Internet, MDPI, vol. 13(7), pages 1-13, July.
    10. Bertrand K. Hassani, 2016. "Bringing the Customer Back to the Foreground: The End of Conduct Risk?," Post-Print halshs-01391106, HAL.
    11. Huawei Li & Guohe Huang & Yongping Li & Jie Sun & Pangpang Gao, 2021. "A C-Vine Copula-Based Quantile Regression Method for Streamflow Forecasting in Xiangxi River Basin, China," Sustainability, MDPI, vol. 13(9), pages 1-22, April.

    More about this item

    Keywords

    Conduct risk; Scenario analysis; Risk management; Data science;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hal:cesptp:halshs-01391106. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.