Targets defined in accordance with Environmental, Social and Governance (ESG) criteria confront the business world, particularly the banking industry, with new challenges. The aim of this paper is to study the effect of ESG controversies on the credit rating of the European banking sector,...

Based on the risk hedging perspective, this paper examines the impact of directors' and officers' liability insurance (hereafter referred to as D&O liability insurance) on the pricing of corporate bonds. We find that the purchase of D&O liability insurance can effectively reduce corporate bond...

Relying on a perspective borrowed from monetary policy announcements and introducing an econometric twist in the traditional event study analysis, we document the existence of an "event risk transfer", namely a significant credit risk transmission from the sovereign to the corporate sector after...

Using an international sample of more than 65,000 rating actions by Fitch, Moody's and S&P, we analyze the effect of the Dodd-Frank Act on credit ratings. We document that (i) rating report content changes significantly after Dodd-Frank and (ii) show, by exploiting within firm-quarter variation,...

Corporate credit lines are drawn more heavily when funding markets are more stressed. This covariance elevates expected bank funding costs. We show that credit supply is dampened by the associated debtoverhang cost to bank shareholders. Until 2022, this impact was reduced by linking the interest...

Using a sample of UK firms, we investigate whether external audit quality has an informational role for firms credit score. In our general research setting, we could not find any evidence on the association between firms’ credit score and external audit quality. However, when firms are...

The aim of the paper was to analyse the factors influencing European banks' credit ratings by taking into account the size of these institutions. A literature review onthe indicators that can impact bank notes has been made. As a result, the following hypotheses have beendrawn:banks' capital...

This paper tests for the sensitivity of R&D to financing constraints conditional on restrictions in external financing. Financing constraints of firms are identified by an exogenously calculated rating index. Restrictions in external financing are determined by (i) the specific time period...

The transformation of credit scores into probabilities of default plays an important role in credit risk estimation. The linear logistic regression has developed into a standard calibration approach in the banking sector. With the advent of machine learning techniques in the discriminatory phase...

We document capital misallocation in the U.S. investment-grade (IG) corporate bond market, driven by quantitative easing (QE). Prospective fallen angels - risky firms just above the IG rating cutoff-enjoyed subsidized bond financing since 2009, especially when the scale of QE purchases peaked...

The COVID-19 pandemic has posed a significant challenge for credit managers and risk management of financial institutions and regulators worldwide. The challenge faced arises because the consequences of outbreaks and epidemics are not distributed equally throughout, with some sectors of the...

The increasing role of the financial sector in the move toward a more sustainable economic model continues apace. The Coronavirus (COVID-19) shock shone a light on the need for all society to correct course, and the financial sector is responding. The pace of environmental, social, and...

In the research, a conceptual model with the export performance scale EXPERF (Export Performance Scale) being the dependent variable and with country credit ratings being the independent variables has been developed, and it is intended to empirically investigate the impact of the country credit...

The increasing role of the financial sector in the move toward a more sustainable economic model continues apace. The Coronavirus (COVID-19) shock shone a light on the need for all society to correct course, and the financial sector is responding. The pace of environmental, social, and...

The tax credit rating mechanism was formally implemented in 2014. As an important tax collection and management innovation, it has attracted the attention of regulatory authorities and scholars. Different from the literature that directly examines corporate tax compliance, we focus on the impact...

Although psychometric features have been considered for alternative credit scoring, they have not yet been applied to peer-to-peer (P2P) lending because such information is not available on platforms. This study proposed an alternative credit scoring model for P2P lending by extracting typical...

For the emerging peer-to-peer (P2P) lending markets to survive, they need to employ credit-risk management practices such that an investor base is profitable in the long run. Traditionally, credit-risk management relies on credit scoring that predicts loans' probability of default. In this...

The paper models and analyses the dynamics of credit spread curves based on ratings over the period from 2004 to 2021. Using more than 1.5 million data points of individual bonds, instead of using index data, monthly asset swap spread (ASW) curves are constructed for all rating levels. The paper...

This research examines the potential impact of Basel IV capital requirements (CAR) on bank lending ability in Africa. To achieve the objective, the study simulated Basel IV capital ratio using historical data to create sample representative banks as if the selected banks had implemented Basel IV...

When firms are forced to publicly disclose financial information, credit rating agencies are supposed to improve their risk assessments. Theory predicts such an information quality effect but also an adverse reputational concerns effect because credit analysts may become increasingly concerned...

While previous academic research highlights the potential of machine learning and big data for predicting corporate bond recovery rates, the operations management challenge is to identify the relevant predictive variables and the appropriate model. In this paper, we use meta-learning to combine...