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The Digital Journey of Banking and Insurance, Volume II pp 119–134Cite as

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Distributed Calculation Credit Portfolio Models

Abstract

Credit portfolio models are—besides rating models—the most important tools to measure and manage credit risks. The technological advancement in cheap and size-adaptable computational power enables fast and efficient new model implementation patterns for Monte-Carlo-based credit portfolio models. As an illustrative example, the well-accepted CreditMetrics model is implemented on a Hadoop cluster.

Keywords

  • Hadoop
  • Spark
  • CreditMetrics
  • Distributed calculation

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Notes

  1. 1.

    See Gupton et al. (1997).

  2. 2.

    See Kealhofer (1998).

  3. 3.

    See Wilde (1997).

  4. 4.

    See Wilson, Portfolio credit risk (I) (1997) and Wilson, Portfolio credit risk (II) (1997), The German Savings Banks Association (DSGV) has developed a specific model variant.

  5. 5.

    CreditRisk+ is a closed formula model, which is a solved algorithm (e.g. by using Fourier transformation).

  6. 6.

    The convergence of Monte Carlo simulation is a widely discussed topic in science (see xx).

  7. 7.

    In practical implementations, only in rare situations do more than three factor-loadings not equal zero. These three main factors usually cover the main impact of the economy on the client. In some implementations, the factor-loadings are restricted to one factor (representing the whole economy, e.g. GDP).

  8. 8.

    Value at risk (see Jorion 2006).

  9. 9.

    Expected shortfall (see McNeil et al. 2005).

  10. 10.

    See Sect. 2.3.1.

  11. 11.

    One common application is the calculation of risk contributions of a single client to the portfolio VaR.

  12. 12.

    Worker node is a common expression in cluster architectures like Hadoop and describes the server (node) doing the bulk of the work (in terms of data or computational power); the counterpart is the master node, which is responsible for overseeing the key operations.

  13. 13.

    Some of the more technical improvements by Spark parameters are discussed in the following section (Sect. 3.3).

  14. 14.

    CDH 6.1.1: CDH 6.1.1 Release Notes | 6.x | Cloudera Documentation.

Literature

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Authors and Affiliations

  1. ifb SE, Grünwald, Germany

    Volker Liermann, Sangmeng Li & Johannes Waizner

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  1. Volker Liermann
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  2. Sangmeng Li
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  3. Johannes Waizner
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Correspondence to Volker Liermann .

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  1. ifb SE, Grünwald, Germany

    Volker Liermann

  2. ifb Americas, Inc., Charlotte, NC, USA

    Claus Stegmann

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Liermann, V., Li, S., Waizner, J. (2021). Distributed Calculation Credit Portfolio Models. In: Liermann, V., Stegmann, C. (eds) The Digital Journey of Banking and Insurance, Volume II. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-78829-2_7

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  • DOI: https://doi.org/10.1007/978-3-030-78829-2_7

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