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Ha Thu NGUYEN

Personal Details

First Name:Ha Thu
Middle Name:
Last Name:Nguyen
Suffix:
RePEc Short-ID:png170
[This author has chosen not to make the email address public]

Affiliation

EconomiX
Université Paris-Nanterre (Paris X)

Nanterre, France
http://economix.fr/
RePEc:edi:modemfr (more details at EDIRC)

Research output

as
Jump to: Working papers

Working papers

  1. Ha-Thu Nguyen, 2016. "Reject inference in application scorecards: evidence from France," EconomiX Working Papers 2016-10, University of Paris Nanterre, EconomiX.
  2. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
  3. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.

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. Ha-Thu Nguyen, 2016. "Reject inference in application scorecards: evidence from France," EconomiX Working Papers 2016-10, University of Paris Nanterre, EconomiX.

    Cited by:

    1. Mengnan Song & Jiasong Wang & Suisui Su, 2022. "Towards a Better Microcredit Decision," Papers 2209.07574, arXiv.org.
    2. Adrien Ehrhardt & Christophe Biernacki & Vincent Vandewalle & Philippe Heinrich & S'ebastien Beben, 2019. "R\'eint\'egration des refus\'es en Credit Scoring," Papers 1903.10855, arXiv.org.
    3. Qiang Liu & Yingtao Luo & Shu Wu & Zhen Zhang & Xiangnan Yue & Hong Jin & Liang Wang, 2022. "RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring," Papers 2206.00568, arXiv.org.
    4. Rogelio A. Mancisidor & Michael Kampffmeyer & Kjersti Aas & Robert Jenssen, 2019. "Deep Generative Models for Reject Inference in Credit Scoring," Papers 1904.11376, arXiv.org, revised Sep 2021.

  2. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.

    Cited by:

    1. Tomáš Vaněk & David Hampel, 2017. "The Probability of Default Under IFRS 9: Multi-period Estimation and Macroeconomic Forecast," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(2), pages 759-776.

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 3 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-BAN: Banking (2) 2014-05-24 2015-02-16
  2. NEP-RMG: Risk Management (2) 2014-05-24 2015-02-16
  3. NEP-CFN: Corporate Finance (1) 2014-05-24
  4. NEP-CNA: China (1) 2015-02-16
  5. NEP-ECM: Econometrics (1) 2016-03-10
  6. NEP-PAY: Payment Systems and Financial Technology (1) 2016-03-10
  7. NEP-TRA: Transition Economics (1) 2015-02-16

Corrections

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