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Financial Innovation, Organizations, and Small Business Lending

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The Changing Geography of Banking and Finance

Abstract

Technological innovation and changes in bank organizational structure have each had a significant effect on small business lending. Both of these phenomena have a spatial dimension. Technological innovation may allow banks to lend at a longer distance if it significantly diminishes the importance of direct customer contact. If consolidation produces fewer banking offices, then the average distance between borrowers and lenders will necessarily increase. The impact of these effects on small business lending, however, greatly depends on the extent to which hard information about borrower quality is a good substitute for soft information. This chapter assesses the theoretical and empirical evidence on the extent to which these changes will likely effect small business lending.

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Notes

  1. 1.

    For a review of the relationship lending literature see Berger and Udell (1998), Boot (2000) and Elyasiani and Goldberg (2004).

  2. 2.

    For a rare exception see Agarwal and Hauswald (2007) who are able to distinguish between relationship lending and transaction lending at the loan level.

  3. 3.

    The lack of data on lending technologies also makes it difficult to test the impact of market structure on credit availability to small businesses. Some theoretical work suggests that increased competition impedes relationship lending (but not transactions lending) (Petersen and Rajan 1995); but other theoretical work (Boot and Thakor 2000) – and the structure, conduct and performance hypothesis – suggests the opposite. Empirical evidence on the importance of these effects is mixed, possibly in part because it suffers from this inability to isolate relationship loans (e.g., Laderman 2006, Carbo-Valverde et al. 2009).

  4. 4.

    For a more comprehensive analysis of technology driven changes in the banking industry over this period see DeYoung et al. (2004).

  5. 5.

    See, for example, Petersen and Rajan (2002), Berger and Frame (2006), and DeYoung et al. (2007). See also Hauswald and Marquez (2003) for a theoretical model of the effect of advances in information technology on credit markets and an analysis of market structure and the incentives to gather information.

  6. 6.

    See Udell (2004) for more detail on equipment lending, equipment appraising, and liquidation.

  7. 7.

    Dun and Bradstreet is the world’s largest third party information exchange. It is similar to a credit registry except that it is a for profit private enterprise.

  8. 8.

    A related issue is whether information innovation necessarily benefits borrowers. It has been shown theoretically that in some cases innovation can lead to more capture, increasing borrower costs and lender profits (Dell’Ariccia and Marquez 2004). One paper has been able to examine the issue of capture using data and a methodology that can distinguish between relationship loans and transactions loans at the loan level. It finds evidence of capture in relationship loans (Agarwal and Hauswald 2007).

  9. 9.

    One study found that within nine US metropolitan areas the distance between borrowers and their lenders actually decreased between 1997 and 2001 (see Brevoort and Hannan 2006, Brevoort and Wolken 2009: Chapter 3, this volume).

  10. 10.

    Arguably, loan officers accumulate information about their borrowers by visiting them personally. The additional time involved in traveling an extra 3 miles may not be economically significant. That is, as long as the increased distance does not move the borrower out of the local “information market”, the 3 extra miles may not matter.

  11. 11.

    One recent paper emphasized that the viable model for community (i.e., small) banks in the long run is likely one that emphasizes “personalized service and relationships based on soft information” (DeYoung et al. 2004). The authors identified the “profitable” sector of the community banking segment of the industry in the US today (i.e., the sector whose average ROE is equal to the average ROE of large banks). They suggested that the number of these ‘profitable” small banks may be the best forecast of how many community banks might ultimately survive industry consolidation. However, they also emphasized that estimating how many community banks there will be in the future is also a “fool’s” game.

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Authors and Affiliations

  1. Department of Finance, Kelley School of Business, Indiana University, 1309 E. Bloomington, IN, 47405-1701, USA

    Gregory F. Udell

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Correspondence to Gregory F. Udell .

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    Udell, G.F. (2009). Financial Innovation, Organizations, and Small Business Lending. In: Zazzaro, A., Fratianni, M., Alessandrini, P. (eds) The Changing Geography of Banking and Finance. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-98078-2_2

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