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A Dual Study Approach to Understanding SME Credit Pricing Influencers: Illustrations from the United Kingdom and the Canadian Computer Animation and Visual Effects Industries

It has been empirically established that the differences in the lending rates charged by traditional and large lenders to large versus small creditors can be largely attributed to differences in information opacity (Dietrich, 2012; Holmes et. al. 1994). The greater the information possessed by the creditor, the lower the rate charged to the borrower, suggesting again that a risk premium is being charged for information opacity. Securitizing debt with collateral can reduce the lending rate charged, however differences in the rates charged cannot be fully explained by information opacity or availability of collateral. This dual study approach aims at increasing the understanding of loan pricing determinants. The first study uses data from the UK Survey of SME Finances, 2007 to explore factors internal and external to the firm that are significant in influencing credit prices, providing insight on why credit prices fluctuate from firm to firm. The second study uses interviews with firm owners in the Toronto computer animation and visual effects (CA&VFX) industries to effectively capture the intricacies and gain insight on the nuances involved in the pricing of credit for firms in these industries. The results of the first study suggest that the use of collateral, loan amount, loan duration, and firm size are significant credit pricing influencers while a firm’s strategic orientation, specifically product innovation and propensity to export, are of little importance. Results from the second study suggest that firm owner perceptions generally align with the extant literature on collateralization and relationships with lenders.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/31186
Date January 2014
CreatorsBourgeois, Elliott
ContributorsFreel, Mark
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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