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The recovery rate for retail and commercial customers in Germany: a look at collateral and its adjusted market values

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  • Peter-Hendrik Ingermann

    (Finance Center Muenster, University of Muenster)

  • Frederik Hesse

    (Finance Center Muenster, University of Muenster)

  • Christian Bélorgey

    (Finance Center Muenster, University of Muenster)

  • Andreas Pfingsten

    (Finance Center Muenster, University of Muenster)

Abstract

Based on a unique data set of 909 defaulted retail and commercial (self-employed and SMEs) credit customers in Germany, whose original loans were made by 123 different banks, our article confirms a significant positive influence of collateral, and of amicable agreements between the debtor and the bank (redemption), on the recovery rate [1 − loss given default (LGD)]. In a further analysis of collateral, systematic biases between the realized market price and the expected market values of real estate are revealed, even though the appraisal reports should have already considered all factors influencing the value. Using valuations that were adjusted for these recognized biases, we can increase the explanatory power of the underlying models. Moreover, we compare these models to models that apply, as is common practice in the banking industry, flat haircuts to collateral values and show the superior performance of our proposed approach.

Suggested Citation

  • Peter-Hendrik Ingermann & Frederik Hesse & Christian Bélorgey & Andreas Pfingsten, 2016. "The recovery rate for retail and commercial customers in Germany: a look at collateral and its adjusted market values," Business Research, Springer;German Academic Association for Business Research, vol. 9(2), pages 179-228, August.
    • Handle: RePEc:spr:busres:v:9:y:2016:i:2:d:10.1007_s40685-016-0028-5
    DOI: 10.1007/s40685-016-0028-5
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    Cited by:

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    2. Frank Ranganai Matenda & Mabutho Sibanda & Eriyoti Chikodza & Victor Gumbo, 2022. "Corporate Loan Recovery Rates under Downturn Conditions in a Developing Economy: Evidence from Zimbabwe," Risks, MDPI, vol. 10(10), pages 1-24, October.
    3. Nataliya Barasinska & Philipp Haenle & Anne Koban & Alexander Schmidt, 2023. "No Reason to Worry About German Mortgages? An Analysis of Macroeconomic and Individual Drivers of Credit Risk," Journal of Financial Services Research, Springer;Western Finance Association, vol. 64(3), pages 369-399, December.
    4. Frank Ranganai Matenda & Mabutho Sibanda & Eriyoti Chikodza & Victor Gumbo, 2021. "Determinants of corporate exposure at default under distressed economic and financial conditions in a developing economy: the case of Zimbabwe," Risk Management, Palgrave Macmillan, vol. 23(1), pages 123-149, June.
    5. Johannes Kriebel & Kevin Yam, 2020. "Forecasting recoveries in debt collection: Debt collectors and information production," European Financial Management, European Financial Management Association, vol. 26(3), pages 537-559, June.
    6. Barasinska, Nataliya & Haenle, Philipp & Koban, Anne & Schmidt, Alexander, 2019. "Stress testing the German mortgage market," Discussion Papers 17/2019, Deutsche Bundesbank.
    7. Georgescu, Oana-Maria & Ponte Marques, Aurea & Galow, Benjamin, 2024. "Loss-given-default and macroeconomic conditions," Working Paper Series 2954, European Central Bank.
    8. Barasinska, Nataliya & Ludwig, Johannes & Vogel, Edgar, 2021. "The impact of borrower-based instruments on household vulnerability in Germany," Discussion Papers 20/2021, Deutsche Bundesbank.

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