Access to Credit in a Market Downturn

Casu, Barbara; Chiaramonte, Laura; Croci, Ettore; Filomeni, Stefano

doi:10.1007/s10693-022-00388-x

Cited by 7 publications

(3 citation statements)

References 73 publications

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“…In this regard, a valuable contribution is provided by Giannetti et al (2011) who document that "trade credit usage is correlated with the buyer's banking relationships", by focusing on the United States. Specifically, they show that firms receiving trade credit secure financing from relatively uninformed banks, thus supporting our findings that the proprietary soft information collected by the bank decreases the likelihood of the borrowing firm being credit-constrained (Berger and Udell 2002;Gobbi and Sette 2014;Presbitero et al 2014;Bolton et al 2016;Casu et al 2022). Moreover, Giannetti et al (2011) find that firms that make greater use of the trade credit channel have shorter relationships with their banks.…”

Section: Trade Credit Channel and Relationship Bankingsupporting

confidence: 85%

Trade credit and firm investments: empirical evidence from Italian cooperative banks

Filomeni

Modina

Tabacco

2022

Rev Quant Finan Acc

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By exploiting a unique and proprietary panel dataset comprising 6480 Italian SMEs having a relationship with 99 cooperative banks over the period 2008–2014, we investigate the influence of the trade credit channel on firm investment decisions in the Italian market, distinguished by a considerable presence of relationship cooperative banks’ branches with a heterogeneous geographical distribution. Firstly, our findings confirm a significant influence of the trade credit channel on firm investment decisions. Secondly, we document that SMEs located in those Italian provinces with an abundance of cooperative banks’ branches rely less on trade credit to finance investments. Lastly, we show that longer firm-bank relationships decrease firm dependence on trade credit to boost investments. Our study is of particular relevance because it strengthens the effectiveness of the trade credit channel for SMEs in spurring corporate investments. Indeed, fostering a deep understanding of the real effects of firm financing sources is paramount to encourage investment by SMEs and to allow them to preserve their positioning in the market. Moreover, we exploit the Italian market, well-suited to perform such an analysis, since it is characterized by more inter-personal financing relationships as compared to other countries.

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Section: Trade Credit Channel and Relationship Bankingsupporting

confidence: 85%

Trade credit and firm investments: empirical evidence from Italian cooperative banks

Filomeni

Modina

Tabacco

2022

Rev Quant Finan Acc

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“…That is, such methods use qualitative soft information in adjunct to traditional quantitative hard information that is mostly collected from a borrower's financial statements or business plans. Specifically, hybrid rating models allow for the hardening of qualitative soft information in an attempt to combine hard and soft information about borrowers into numerical ratings that reflect their creditworthiness and repayment prospects that ultimately influence banks' lending decisions (Bertomeu & Marinovic, 2016;Brown et al, 2015Brown et al, , 2012Casu et al, 2022;Filomeni et al, 2021;Gropp & Guettler, 2018;Liberti & Petersen, 2019;Roy & Shaw, 2021). Supervisory agencies also support this process of hardening soft information (BCBS, 2000;BCBS, 2005;Federal Reserve, 2011;OeNB, 2004).…”

Section: Related Literaturementioning

confidence: 99%

“…Accounting-based approaches attempt to forecast defaults by using accounting information based on the firm's balance-sheet data (Altman, 1968;Altman & Sabato, 2008;Beaver, 1966;Louzada et al, 2016;Ohlson, 1980). Hybrid models attempt to predict defaults by combining hard and 'hardened' soft information about borrowers in their credit ratings (Brown et al, 2012(Brown et al, , 2015Casu et al, 2022;Filomeni et al, 2021;Liberti & Mian, 2009;Liberti & Petersen, 2019;Roy & Shaw, 2021;Xu et al, 2018). The DD, calculated on the basis of observable equity market data, is widely used for predicting the insolvency risk of listed companies, especially in the US equity market (Bharath & Shumway, 2008;Byström, 2006;Vassalou & Xing, 2004).…”

Section: Introductionmentioning

confidence: 99%

Can market information outperform hard and soft information in predicting corporate defaults?

et al. 2023

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Recent evidence has shown that hybrid models for credit ratings are important when assessing the risk of firms. Within this stream of literature, we aim to provide novel evidence on how hard (quantitative), soft (qualitative), and market information predict corporate defaults for unlisted firms by implementing the Cox proportional hazard model. We address this research question by exploiting a unique proprietary dataset comprising of detailed information on internal credit ratings of European unlisted mid‐sized firms and compute their Merton's distance‐to‐default (DD) measure of credit risk with market data collected on comparable publicly listed companies. Our results show that the bank's use of hard, soft, and market information when assessing the credit ratings of borrowers has a significant influence on the prediction of their defaults. Further, we investigate the significant influence of soft information in predicting corporate defaults by drawing on two separate processes through which loan officers can inject soft information in credit scoring, that is, ‘codified’ and ‘uncodified’ discretion. Finally, when we distinguish between the loan officer's discretion to upgrade or downgrade an applicant's credit score, we find that it is the upgrade that is likely to predict a lower probability of a firm defaulting. This study contributes to the policy debate on safeguarding the banking sector's continuity by positing that integrating market information into banks' hybrid methods of credit rating helps to improve the accuracy in predicting unlisted firms' credit risk that is useful to policy makers for the design of future forward‐looking financial risk management frameworks.

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Owner Guarantees, Observed and Unobserved Risks, and Bank Lending Spreads

Duarte,

Gama,

Gulamhussen

2024

J Financ Serv Res

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In this paper, we examine the influence of owner guarantees on loan rates. Other studies on the influence of business collateral have used survey and credit register data to establish this link. They support it with the pre-lending information theory and post-lending incentive theory and find that the latter predominates the former. Thus, we measure observed and unobserved risks on bank lending spreads negotiated over the counter to show the co-existence of both theories. The main findings and robustness tests show that owner guarantees reduce bank lending spreads for safe but not risky firms, supporting the pre-lending information theory rather than the post-lending incentive theory. These findings underscore the role of owner guarantees in allaying the information problems the bank confronts prior to lending.

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Access to Credit in a Market Downturn

Cited by 7 publications

References 73 publications

Trade credit and firm investments: empirical evidence from Italian cooperative banks

Trade credit and firm investments: empirical evidence from Italian cooperative banks

Can market information outperform hard and soft information in predicting corporate defaults?

Owner Guarantees, Observed and Unobserved Risks, and Bank Lending Spreads

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