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How Bad Is a Bad Loan? Distinguishing Inherent Credit Risk from Inefficient Lending (Does the Capital Market Price This Difference?)

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  • Joseph Hughes

    (Rutgers University)

  • Choon-Geol Moon

    (Hanyang University)

Abstract

We develop a novel technique to decompose banks’ ratio of nonperforming loans to total loans into three components: first, a minimum ratio that represents best-practice lending given the volume and composition of a bank’s loans, the average contractual interest rate charged on these loans, and market conditions such as the average GDP growth rate and market concentration; second, a ratio, the difference between the bank’s observed ratio of nonperforming loans, adjusted for statistical noise, and the best-practice minimum ratio, that represents the bank’s proficiency at loan making; third, a statistical noise. The best-practice ratio of nonperforming loans, the ratio a bank would experience if it were fully efficient at credit-risk evaluation and loan monitoring, represents the inherent credit risk of the loan portfolio and is estimated by a stochastic frontier technique. We apply the technique to 2013 data on top-tier U.S. bank holding companies which we divide into five size groups. The largest banks with consolidated assets exceeding $250 billion experience the highest ratio of nonperformance among the five groups. Moreover, the inherent credit risk of their lending is the highest among the five groups. On the other hand, their inefficiency at lending is one of the lowest among the five. Thus, the high ratio of nonperformance of the largest financial institutions appears to result from lending to riskier borrowers, not inefficiency at lending. Small community banks under $1 billion also exhibit higher inherent credit risk than all other size groups except the largest banks. In contrast, their loan-making inefficiency is highest among the five size groups. Restricting the sample to publicly traded bank holding companies and gauging financial performance by market value, we find the ratio of nonperforming loans to total loans is on average negatively related to financial performance except at the largest banks. When nonperformance, adjusted for statistical noise, is decomposed into inherent credit risk and lending inefficiency, taking more inherent credit risk enhances market value at many more large banks while lending inefficiency is negatively related to market value at all banks. Market discipline appears to reward riskier lending at large banks and discourage lending inefficiency at all banks.

Suggested Citation

  • Joseph Hughes & Choon-Geol Moon, 2018. "How Bad Is a Bad Loan? Distinguishing Inherent Credit Risk from Inefficient Lending (Does the Capital Market Price This Difference?)," Departmental Working Papers 201802, Rutgers University, Department of Economics.
  • Handle: RePEc:rut:rutres:201802
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    Cited by:

    1. Shi, Tao & Li, Chongyang & Wanyan, Hong & Xu, Ying & Zhang, Wei, 2022. "The lending risk predicting of the folk informal financial organization from big data using the deep learning hybrid model," Finance Research Letters, Elsevier, vol. 50(C).
    2. Hughes, Joseph P. & Jagtiani, Julapa & Mester, Loretta J. & Moon, Choon-Geol, 2019. "Does scale matter in community bank performance? Evidence obtained by applying several new measures of performance," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 471-499.
    3. Joseph P. Hughes & Julapa Jagtiani & Choon-Geol Moon, 2022. "Consumer lending efficiency: commercial banks versus a fintech lender," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-39, December.
    4. Ferreira, Cândida, 2021. "Efficiency of European Banks in the Aftermath of the Financial Crisis: A Panel Stochastic Frontier Approach," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 36(1), pages 103-124.
    5. Joseph P. Hughes, 2018. "Comments on “The Evolving Complexity of Capital Regulation”," Journal of Financial Services Research, Springer;Western Finance Association, vol. 53(2), pages 207-210, June.
    6. Ze Song, 2019. "Long Term Health Efect of Earned Income Tax Credit," Departmental Working Papers 201902, Rutgers University, Department of Economics.
    7. Joseph P. Hughes & Loretta J. Mester, 2018. "The Performance of Financial Institutions: Modeling, Evidence, and Some Policy Implications," Departmental Working Papers 201805, Rutgers University, Department of Economics.

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    More about this item

    Keywords

    commercial banking; credit risk; nonperforming loans; lending efficiency;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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