An integrated credit rating and loan quality model: application to bank shipping finance

A survey of shipping finance research: Setting the future research agenda

“…As shown in Figure 2, shipping bank loans have traditionally been the predominant financing source in the shipping industry, accounting for approximately 75% of the total ship-funding requirements during the period 2007-2017. The popularity of bank borrowings among shipowning companies can be explained by: (i) the lower cost and more readily available nature of bank loans which are highly desirable features among shipowners given the capital intensive nature of the business and the short-lived investment opportunities involved; (ii) relying on debt as a funding source does not affect the ownership structure of a shipping company, which is important given that shipping businesses are typically reluctant to endure significant changes in their traditional family oriented and highly concentrated ownership structures, (iii) raising funds through bank loans does not require the public disclosure of (confidential) strategic, financial and operational information, unlike for instance in IPOs and corporate bond issues (Kavussanos and Tsouknidis, 2014;; and (iv) historically, shipping bank loans have been granted on the basis of relationship banking, based on which a long-term rapport is established on amicable trust and information sharing between the obligor and the bank (Gavalas and Syriopoulos, 2014;Kavussanos and Tsouknidis, 2016;Mitroussi et al, 2016).…”

“…In a related study, Gavalas and Syriopoulos (2014) also examine factors used in the assessment of shipping loans' default risk based on primary data, collected from a bank survey questionnaire during the period April-June 2012. The authors survey a sample of 16 managers to capture their perception on the importance of default risk drivers in shipping bank loan agreements.…”

“…The authors survey a sample of 16 managers to capture their perception on the importance of default risk drivers in shipping bank loan agreements. Having specified an initial set of credit criteria based on the survey conducted, Gavalas and Syriopoulos (2014) rely on the UTADIS method to determine a utility function and the cut-off utility thresholds for granting a loan in a manner similar to Dimitras et al (2002). Results show that the credit rating migration probability (i.e.…”

Predicting corporate failure for listed shipping companies

“…Thus market conditions and the dynamics of a sector, both operational and financial, need to be considered in determining credit risk (Gavalas and Syriopoulos, 2015).…”

A multicriteria decision support tool for modelling bank credit ratings

“…Zopounidis et al 2015, for a bibliographic survey), eventually proving to be great assets in supporting decision-makers' (DMs) financial decisions. In the strand of credit rating analysis that this study is addressed at in particular, MCDA models have been used in a variety of assessment and predictive frameworks, making use of value functions (Doumpos and Pasiouras 2005;Gavalas and Syriopoulos 2015), rough sets theory (Capotorti and Barbanera 2012), goal programming (García et al 2013) and outranking techniques (Angilella and Mazzù 2015;Doumpos and Figueira 2019).…”