From an Internal Audit perspective, the integration of Artificial Intelligence (AI) into credit risk modelling through Machine Learning (ML) algorithms presents significant challenges due to the complexity and multidimensional nature of these models. While AI enhances predictive performance and...

This study provides a comparative analysis of European banking systems, focusing on how macroeconomic factors influence non-performing loans (NPLs) to evaluate bank credit risk from 2008 to 2022. Using the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) model, the research examines both...

Climate risk is the negative effect of climate change on several aspects of the environment, business, and society. There are two categories of climate risks: physical risks include direct impacts due to extreme events and chronic changes due to climate modifications that have become commonplace;...

Traditionally, business risk management models have not taken into consideration household composition for the purposes of credit granting or project financing in order to manage the risk of default. In this research, an improvement in the risk management model was obtained by introducing...

Over the past decade, the debate on the microeconomic effects of financial inclusion has intensified, with a growing body of research exploring how access to financial services impacts banks' behaviors. Studying the effect of financial inclusion on bank risk is crucial because it helps...

In the aftermath of global financial crises and amid increasing complexity in banking operations, understanding and managing various types of risk - especially liquidity, credit, and solvency risks - has become a global concern for financial stability. This study addresses a critical gap in the...

We develop a novel stress testing framework to quantify the risks to the German banking sector from the green transition. Our methodology combines a macro-level and a micro-level approach to calculate scenario-dependent probabilities of default and losses. The macro approach leverages...

This paper explores how the low-carbon transition affects firms' credit ratings and market-implied distance-to-default. We develop a novel dataset covering firms' greenhouse gas emissions alongside climate disclosure and forward-looking emission reduction targets. Panel regression analysis...

This study aims to combine deep and recurrent neural networks with a reduced-form portfolio model to predict future default rates across economic sectors. The industry-specific forecasts for Italian default rates produced with the proposed approach demonstrate its effectiveness, achieving...

How do banks respond to geopolitical risk, and is this response distinct from other macroeconomic risks? Using U.S. supervisory data and new geopolitical risk indices, we show that banks reduce cross-border lending to countries with elevated geopolitical risk but continue lending to those...

Climate change is expected to lead to more frequent and intense extreme weather events, such as floods and droughts, which in turn increase physical risks. In this paper, we assess the direct exposure of Slovak banks' corporate loan portfolios to riverine flood risk. We propose several...

This study examines how dismantling Mafia-connected firms affects banks' lending practices. Using a unique dataset of 667 such firms and loan-level data from the European Central Bank, our analysis shows that anti-Mafia operations precede an increase in bank loans to businesses that operate in...

This study addresses the quantification of credit risk in solidarity economy entities, proposing a new methodology to redefine the concept of a "default" in the frequent situations of extreme class imbalances. The objective is to develop and evaluate credit scoring models that enhance risk...

How do banks respond to geopolitical risk, and is this response distinct from other macroeconomic risks? Using U.S. supervisory data and new geopolitical risk indices, we show that banks reduce cross-border lending to countries with elevated geopolitical risk but continue lending to those...

The paper analyses the association between the reporting of the Sustainable Development Goals (SDGs) and the behaviour of Romanian banks, focusing on the relationship between SDG disclosure scores (both total and across the four sustainability dimensions) and credit risk management practices,...

We study the credit risk of banks in Germany from lending to non-financial firms. We model changes in Expected Credit Loss, which is derived from the guidelines in the IFRS 9 accounting standard. We map the accounting model to a dataset with individual loans as the unit of observation...

This research article presents a comparative analysis between logistic regression as a traditional method, artificial neural networks (ANNs), and decision tree as machine learning techniques for predicting credit risk. It meticulously examines and evaluates these three methods, elucidating their...

Carbon risk, a type of climate risk, is expected to have a crucial impact, especially on high-carbon-emitting, "polluting" firms as opposed to less carbon-intensive, "clean" ones. With a rising number of actions and policies being continuously proposed to mitigate these concerns and an...

This study investigates the underlying reasons for banks' continued support of fossil fuel-based firms and examines the role of public guaranteed loans (PGLs) in redirecting resources towards greener economic activities, thereby facilitating the climate transition process. Using a unique...

Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrictive for real-life applications since it cannot discover hidden nonlinearities and interactions...

The internal ratings-based (IRB) approach maps bank risk profiles more adequately than the standardized approach. After switching to IRB, banks' risk-weighted asset (RWA) densities are thus expected to diverge, especially across countries with different supervisory strictness and risk levels....

The EU faces two economic challenges: managing non-performing exposures (NPEs) and climate change. This paper analyzes the relationship between the NPEs of domestic banking groups and climate risks, including macroeconomic variables such as the GDP growth rate, unemployment rate (UnEmp), and the...

We present a statistical test for the long-term calibration in rating systems that can deal with overlapping time windows as required by the guidelines of the European Banking Authority (EBA), which apply to major financial institutions in the European System. In accordance with regulation,...

The increasing population and emerging business opportunities have led to a rise in consumer spending. Consequently, global credit card companies, including banks and financial institutions, face the challenge of managing the associated credit risks. It is crucial for these institutions to...

Climate risk refers to the risks associated with climate change and has already started to impact various sectors of the economy. In this work, we focus on the impact of physical risk on the probability of default for a firm in the agribusiness sector. The probability of default is estimated...

Climate change adaptation efforts are heavily dependent on a country's fiscal capacity and the associated costs of undertaking adaptation policies. The current accumulation of high debt levels in emerging and low-income developing countries, which are disproportionately affected by climate...