Credit Portfolio Research Articles (Page 1)

ABSTRACT Most Eurozone credit institutions’ portfolios remain misaligned with Article 2.1(c) of the Paris Agreement. To address this, both the climate finance literature and the European policy initiatives emphasize mobilising private finance through prudential measures. However, these policies have yet to yield material shifts toward climate-consistency. By taking a broad view of the rules and practices that govern bank lending, a new pathway emerges. This explorative paper examines the relation between climate-consistent lending and four key design elements of banks’ architectures: equity, liabilities, exclusions and prudential approach & monetary policy. A vignette on district heating, a low-carbon source of heating, is used as an empirical referent to analyse how financial obstacles to climate-consistent loans relate to the configuration of commercial, ethical and promotional banks’ architectures. Drawing on seven interviews with Dutch bank employees and a heat grid finance expert, analysis of Dutch banks’ annual reports and a literature analysis, the article identifies two main financial obstacles: interest plus fees and risk rating. The level of interest plus fees appears to be influenced by a bank’s equity configuration, expressed in its return on equity target. The double-digit return targets of commercial banks seem to limit their capacity to provide viable rates for heat grids, compared to that of ethical and promotional banks, who have lower profit targets. Risk rating is mostly related to the ECB’s prudential approach and affects all banks equally. While the paper identifies two root causes, only the latter is addressed in the literature and policy debate. The analysis substantiates that in addition to prudential measures, equity configurations should be incorporated into academic and policy discussions on climate-consistent credit portfolio. Key policy insights The publicly listed equity configuration of commercial banks strongly disadvantages climate-consistent loans. The equity configuration of a bank shapes its return on equity target, which is around 10–14% for commercial banks in the EU. Double-digit return on equity targets are more likely to result in a level of interest plus fees that is incompatible with the debt servicing capacity of climate-consistent measures, such as heat grids, causing financial obstacles. The alternative equity configurations of ethical and promotional banks, such as private or registered shares, average return on equity targets of 6%, which reduce or lessen interest plus fees as financial obstacle. Neglecting banks’ equity configurations limits the scope of analysis and consequently reduces the instruments available to ensure climate-consistent bank portfolios.

This study evaluates the composition and quality of credit portfolios held by specialized lending institutions licensed and supervised by the Palestinian Monetary Authority (PMA) over the period 2020-2024. Using annual cross‑sectional data from four purposively selected institutions which together represent 69.7% of the sector’s active portfolio and 62.25% of working units, we analyze sectoral portfolio composition and risk using the Portfolio at Risk (PAR) indicator. Non‑parametric tests (Mann-Whitney U and Kruskal-Wallis) are employed to compare risk across sector groups (productive, consumer, and residential) and within productive subsectors. Results show that housing consistently dominates active portfolios, commercial and services tend to be the smallest shares, and risk patterns vary markedly across institutions and years. The consumer sector exhibits the highest sensitivity in PAR during 2023-2024, while housing remains comparatively less risky. Evidence indicates no significant difference between productive and consumer PAR in 2020-2022, but a significant divergence appears in 2023-2024. Similarly, there is no significant difference between productive and residential PAR across all years, and no significant differences among productive subsectors. Findings support portfolio diversification, targeted risk controls for consumer lending, and capacity building for credit officers and borrowers. The paper closes with policy recommendations and avenues for future research.

This study investigates the interconnected relationship between credit risk, profitability, and financial stability within the context of emerging market banking systems, using panel data from 10 listed Egyptian commercial banks over the period 2013–2023. Utilizing panel regression models with clustered standard errors to address heteroskedasticity and serial correlation, the analysis evaluates both the direct and mediating effects of credit risk on bank performance. Profitability, proxied by Return on Assets (ROA), is examined as a potential channel through which credit risk influences financial resilience, measured by Z-scores. The findings reveal that while capital adequacy significantly enhances profitability, credit risk does not exert a statistically significant influence on ROA. Furthermore, profitability does not significantly predict financial stability in the Egyptian context, challenging the linear transmission mechanisms proposed in traditional models. However, credit risk demonstrates a marginally significant negative effect on financial stability, reinforcing concerns about the structural vulnerabilities in credit portfolios. These results underscore the heterogeneous nature of bank behavior in emerging economies and highlight the limitations of earnings-based buffers in weak institutional environments. The study contributes to the literature by integrating risk management, income generation, and stability outcomes within a single empirical framework, offering context-specific insights that extend beyond conventional models developed for advanced markets. Practical implications are offered for policymakers and regulators seeking to strengthen provisioning practices and risk-sensitive performance metrics.

Indonesia's aquaculture industry has substantial economic potential, but it faces considerable credit risk from natural disasters like floods, which lead to high Non-Performing Loans (NPLs). Current methods for assessing credit risk do not adequately consider geographical risk factors. This research addresses this by developing a model to quantify flood-induced credit risk. The model integrates a Spatial Finance approach, Spatial Multi-Criteria Decision Analysis (AHP-GIS), and Monte Carlo risk simulation. Using a case study of flood-related credit losses from 2020 to 2022 in Kampar Regency, Riau, the model effectively maps flood vulnerability zones by weighting geospatial criteria through AHP. Key findings indicate that incorporating spatial factors significantly influences loss predictions. Credit portfolios in high flood risk areas show a maximum estimated loss (Value at Risk - VaR) that is 4.67% higher compared to traditional assessment scenarios. Therefore, this model provides a measurable tool for financial institutions to adjust credit portfolios, implement location-specific risk reduction strategies, and ultimately improve financing stability in the aquaculture sector.

ABSTRACTThis paper examines the underlying factors contributing to the misalignment of banks' credit portfolios with European environmental objectives. Drawing on panel data on green lending from 2015 to 2023, the empirical analysis reveals that such misalignment is primarily influenced by the country and sector in which the financed firms operate. The main findings indicate a positive relationship between green lending and the environmental performance of the country where the firm is based. Moreover, the significant presence of carbon‐intensive sectors within national economies shapes banks' credit allocation decisions, reflecting broader structural characteristics rather than bank‐specific strategies. Policymakers are therefore encouraged to support the alignment of bank lending with climate goals through public policies and enhanced regulations that promote firms' business model innovation. In addition, the implementation of appropriate macroprudential tools may help address the systemic dimension of climate‐related financial risk.

This study aims to analyze the influence of the lifestyle of credit relationship managers (RMs) and the potential for fraud on the occurrence of non-performing loans in the banking sector. Relationship managers are the spearheads of credit distribution, interacting directly with customers, so their behavior, lifestyle, and integrity have a significant impact on the quality of a bank's credit portfolio. This study uses a qualitative descriptive method with a systematic literature review approach, reviewing various recent studies related to bank employee lifestyles, factors driving fraud, and their correlation with non-performing loans. The results indicate that a consumptive lifestyle disproportionate to income can increase the risk of fraudulent behavior, such as manipulation of credit analysis or collusion with customers, which ultimately results in an increase in non-performing loans. Furthermore, weak internal control systems, pressure to achieve credit targets, and moral hazard exacerbate this risk. A lifestyle that prioritizes social symbols and self-image can also encourage employees to engage in deviant behavior to maintain this lifestyle. Several studies have shown that RMs trapped in a hedonistic lifestyle are more vulnerable to conflicts of interest and violations of professional ethics. Meanwhile, the potential for fraud in banking practices is also influenced by employees' weak personal financial literacy, as well as limited training in risk management and ongoing work ethics. In an organizational context, a work culture oriented toward achieving targets without regard for the quality of credit analysis has the potential to create a work climate that is permissive of irregularities. This study recommends strengthening a culture of integrity through the establishment of a firm code of ethics, technology-based supervision (such as an AI-based fraud detection system), and regular training on a healthy financial lifestyle and risk management for RMs.

The objective of this study is threefold. First, it examines the impact of climate risk (CRI) on credit risk, as measured by the ratio of non-performing loans (NPLs). Second, it investigates the effect of green growth (GGI) on NPLs. Third, it assesses whether GGI moderates the relationship between climate risk and NPLs. To achieve these objectives, the study utilizes a panel dataset of 40 traditional banks from Middle East and North Africa (MENA) countries, covering the years 2010 to 2022. The estimation employs the System Generalized Method of Moments (SGMM) estimator to address endogeneity and dynamic panel bias. Empirical results indicate that climate risk significantly increases the NPL ratio, leading to deterioration in credit quality under environmental stress. Conversely, green growth has a mitigating effect, significantly reducing credit risk among MENA banks. Additionally, the interaction between green growth and climate risk is negatively related to NPLs, suggesting that green growth can effectively shield bank credit portfolios from the adverse effects of climate risk. These findings have important implications for policymakers and financial institutions in the MENA region. Strengthening green growth policies can serve as a valuable tool to enhance banking sector resilience and promote sustainable financial development.

With mounting economic pressures in China, commercial banks are witnessing a continuous rise in non-performing loans, making credit risk management a renewed focus of attention. Effective risk management and control in credit operations serve as both essential require-ments for maintaining the healthy development of China's financial market and vital strate-gies for commercial banks to sustain competitiveness. When handling complex credit port-folios, how to effectively mitigate credit risks has become a critical challenge requiring in-depth research by grassroots commercial banks. This paper analyzes existing models and challenges in credit risk management within Chinese commercial banks, while proposing practical approaches to enhance risk management capa-bilities through real-world imple-mentation.

Abstract Financial regulation requires the submission of diverse and often highly granular data from financial institutions to regulators. In turn, regulators face the challenge of condensing this data into a comprehensive map that captures the mutual similarity or distance between different institutions and identifies clusters or outliers based on features like size, credit portfolio, or business model. Additionally, missing data due to varying regulatory requirements for different types of institutions, can further complicate this task. To address these challenges, we interpret the credit data of financial institutions as probability distributions whose respective distances can be assessed through optimal transport theory. Specifically, we propose a variant of Lloyd’s algorithm that applies to probability distributions and uses generalized Wasserstein barycenters to construct a metric space. Our approach provides a solution for the mapping of the banking landscape, enabling regulators to identify clusters of financial institutions and assess their relative similarity or distance.

The objectives to be achieved in this study are: to determine and test the credit risk management system has a direct and indirect effect on credit portfolio quality, 2) to determine and test the credit risk management system has a direct and indirect effect on credit risk mitigation through credit portfolio quality, to know and test big data has a direct effect on credit portfolio quality, 3) to know and test artificial intelligence and machine learning has a direct and indirect effect on credit portfolio quality.4) to know and test the credit process automation has a direct and indirect effect on credit portfolio quality. ) identify and test the direct and indirect effect of credit process automation on credit portfolio quality, 5) identify and test the direct effect of credit portfolio quality on credit risk mitigation. Novelty. Focus on Credit Risk in Sharia Context, because credit risk has been widely studied in conventional banking, but the focus on Islamic banking with the principles of contracts, profit sharing, and sharia values makes this research specific and contextual. 3) Technology Integration as a Strategic Variable, Research method. This research uses Partial Lesquare (PLS). Using primary data, with a sample of 675. Research findings. This study found that all exogenous variables have a significant direct and indirect effect on endogenous variables, except artificial intelligence and machine learning which have a direct effect on credit risk mitigation. Conclusion. The results of this study can be concluded that of the 13 (thirteen) hypotheses proposed all have a positive and significant direct and indirect effect on Credit Portfolio Quality and Credit Risk Mitigation.

The primary objective of this study is to develop an economic-mathematical model for constructing the credit policy of a commercial bank. This model is aimed at optimizing the structure of the credit portfolio, reducing credit risks, and enhancing the bank's financial stability in the context of a changing economic environment.The research methodology involves the application of economic-mathematical modeling techniques, such as correlation and regression analyses. These methods enabled the identification of key relationships between macroeconomic indicators and the internal parameters of the credit portfolio, as well as their impact on overall profitability and risk.The originality of the study lies in the development of a unique model tailored to the specific characteristics of commercial banking operations in Kazakhstan. The model takes into account both macroeconomic and bank-specific factors, making it universal and applicable for analyzing the credit policies of other banks not only in Kazakhstan but also abroad.The research findings demonstrate the high efficiency of the proposed model, as evidenced by the data from JSC «BankCenterCredit» for the period 2019-2023. The implemented credit risk management strategies have reduced the share of non-performing loans by 15% and increased the return on assets by 10%. This confirms that the proposed model contributes to the bank's stability and can be integrated into strategic planning. The practical value of the model lies in its potential use for developing and implementing a credit policy that aims to achieve long-term improvements in the financial stability and competitiveness of commercial banks.

Indonesia’s Islamic banking sector has experienced rapid expansion in recent decades; however, credit growth within this sector remains volatile and insufficiently explored, particularly in relation to broader macroeconomic fluctuations. This study addresses this knowledge gap by investigating the key macroeconomic and financial determinants influencing credit growth in Islamic banks. It is driven by the need to understand how external shocks and policy variables affect Islamic financing behavior. Utilizing monthly data from 2002 to 2023, the study employs a Vector Error Correction Model (VECM), Impulse Response Function (IRF), and Forecast Error Variance Decomposition (FEVD) to analyze both short- and long-term dynamics. The VECM results reveal a long-run equilibrium relationship between Islamic credit growth and macroeconomic indicators, including GDP, inflation, and interest rates. This finding suggests that Islamic credit, characterized by its unique Shariah-compliant principles, adjusts over time to restore equilibrium following disruptions. The IRF analysis further indicates that shocks to inflation and exchange rates tend to temporarily suppress credit growth, reflecting the sector’s sensitivity to price volatility and currency fluctuations. In contrast, positive shocks to GDP and stock market performance are associated with sustained increases in credit, underscoring the procyclical nature of Islamic bank lending. FEVD results show that GDP and inflation are the most significant drivers of credit growth variability, followed by interest rates and the exchange rate. These findings underscore that Islamic credit expansion is closely tied to real sector performance and overall macroeconomic stability. For policymakers and financial regulators, the study highlights the importance of maintaining sound macroeconomic fundamentals and fostering a stable investment climate. Such efforts are essential to support sustainable credit growth and enhance the resilience of Indonesia’s Islamic banking sector

This article presents a comprehensive study of innovative strategies for managing a bank’s credit portfolio in the context of the transformation of Ukraine’s financial and credit environment. Considering the high level of macroeconomic turbulence, institutional changes, the impact of martial law, inflationary processes, and shifts in consumer behavior, the author substantiates the urgency of modernizing traditional credit management models. Particular attention is paid to the transition from classical scoring methods to innovative approaches based on digital transformation, artificial intelligence, and big data analytics. The study examines six key directions of innovative modernization in credit portfolio management: digital transformation using AI/ML algorithms (Random Forest, XGBoost, Decision Trees) for objective analysis of borrowers’ creditworthiness; implementation of scenario modeling and stress testing to forecast risks under various macroeconomic conditions; segmentation of the credit portfolio by profitability and risk profile, allowing banks to optimize credit policies; strategic partnerships with fintech companies that accelerate the digitalization of credit processes without significant internal resource costs; enhancement of managerial digital literacy through training programs, promoting the adoption of new management approaches; and the formation of an ethical system for using artificial intelligence in lending. Based on constructed graphs and comparative analysis, the paper illustrates the transformation of the role of digital models in scoring procedures—from 10% in 2020 to over 60% in 2024 – indicating a paradigm shift in decision-making within the banking sector. Empirical data show that the most widely adopted tools of innovative risk management in 2024 are scenario modeling (58%) and stress testing (49%), while ethical AI auditing remains insufficiently implemented (24%). The article emphasizes that the strategic effectiveness of modern banking management depends not only on the ability to automate operational processes but also on the integration of a comprehensive approach to risk-oriented planning, personnel training, regulatory compliance, and technological ethics. The author concludes that innovative credit portfolio management is not merely a temporary crisis response but a long-term factor in ensuring financial stability, enhancing bank competitiveness, and serving as a tool for post-crisis economic recovery in Ukraine.

The impact of climate change on credit portfolios and banking resilience: Preliminary evidence from a developing economy

Climate change has become a global issue that significantly impacts the banking sector, particularly in the management of credit portfolios that are vulnerable to both physical and transition risks. These risks may affect asset quality and the overall financial stability of banks. Therefore, it is essential for banking institutions to demonstrate the capacity in managing such risks through scenario based approaches, such as the Climate Risk Management Scenario (CRMS). This study aims to analyze the capacity of PT Bank CDE in implementing CRMS as part of its climate risk management strategy for its credit portfolio. A qualitative approach with a case study strategy was employed. Data collection was conducted through semi structured interviews as the primary data source and document analysis of regulatory guidelines and the company’s sustainability reports as secondary data. The findings indicate that PT Bank CDE is at a fundamental stage in implementing CRMS. This organizational capacity is reflected in the establishment of an Environmental, Social, and Governance (ESG) Management unit, cross functional collaboration (involving ESG Management, IT, Business, and the ESG Subcommittee), and the adoption of the Three Lines Model principle, although it has not yet been formally institutionalized. These findings suggest an initial commitment to integrating climate risk into the company’s risk governance system.

Propagation of a Carbon Price in a Credit Portfolio through Macroeconomic Factors

Introduction. Agriculture is a basic element of the Ukrainian economy, providing a significant part of GDP, the lion’s share of commodity exports, and to a large extent forming the resource base and credit portfolio of the banking system. At the same time, the active development of the agribusiness sector requires not only significant additional volumes of long-term and cheap credit resources in the national currency, but also additional specific banking products and services, which are currently offered by banks only fragmentarily. Problems Statement. The analysis of the main factors of activating bank lending and improving the mechanism of comprehensive banking services for agribusiness enterprises in Ukraine and substantiation of the list of measures taken by the state aimed at solving existing problems in this area. The purpose is the analysis of the main obstacles standing in the way of activating bank lending and improving the mechanism of banking services for agribusiness enterprises, substantiation of necessary measures by the state aimed at overcoming existing negative trends in the field of lending and banking services for farmers. Methods. General scientific and special methods are used: analysis, synthesis, grouping, description, comparison, theoretical generalization and abstract-logical. Results. Credit and other banking products aimed at agricultural producers and the main factors hindering the activation of lending to agricultural enterprises in Ukraine are analyzed. A range of measures aimed at solving existing problems is determined, including the expansion of the range of specific banking services at the level of one of the state banks with the subsequent creation of a specialized agricultural bank in the medium term. Recommendations for legislative support for this process are proposed. Conclusions. The agricultural sector forms a significant share of GDP and a significant part of Ukraine’s export revenues, and its further development requires active support from the banking system. This highlights the need for a set of measures by the state aimed at activating bank lending to agribusiness enterprises in the “single window” mode. To this end, it is advisable to recommend: amending the Regulation on determining the amount of credit risk for active banking operations by banks of Ukraine in terms of easing the requirements for liquidity ratios of real estate collateral; easing the requirements for agricultural sector enterprises regarding formal compliance with ESG standards of production projects that are financed within the framework of the government program “Affordable Loans 5-7-9%”; developing an expanded range of credit products and related specific banking services for farmers, organizing the provision of this package by one of the state-owned banks in the “single window” mode; developing a mechanism for long-term targeted refinancing of banks with the subsequent allocation of these funds to agricultural enterprises in the form of long-term loans; clarification and synchronization of contradictory provisions of the current legislation of Ukraine regarding banks and banking activities; determination of the feasibility of creating a specialized state agrobank, which should offer agribusiness enterprises a wide range of credit products and related services, introduce successful mortgage lending practices, contributing to the formation of a liquid land market, and should also become the main operator for attracting and distributing funds from foreign partners that will flow to Ukraine within the framework of the implementation of the Green Deal programs etc.

Trade credit is a crucial component of supply chain financing, enabling businesses to manage cash flow and optimize inventory levels. This study delves into the application and implications of multiple trade credit types with different repayment periods and financing costs in a supply chain, encompassing short-term trade credit concatenated with bank financing, long-term trade credit, and a trade credit portfolio. Using a two-stage newsvendor model, we analyze the impact of different trade credit types on supply chain profitability under various scenarios. When facing multiple trade credit types, the retailer prefers financing from the trade credit type that has a lower marginal cost, and the resulting form of financing ensures an equal expected cost of each financing type. The analysis shows that in the case of a monopoly supplier, a long-term credit supplier’s profit is higher than that of a short-term credit supplier. Meanwhile, when the bank interest rate is sufficiently high, the retailer’s profit is highest under the trade credit portfolio mode, whereas when the bank interest rate is sufficiently low, the retailer’s profit is highest under the single short-term credit model. Comparing the effects of different financing modes, we find that there is no optimal financing mode for the overall profit of the supply chain.

The loss rate of a bank’s portfolio traditionally measures what portion of the exposure is lost in the case of a default. To overcome the difficulties involved in its computation due to, e.g., the lack of private data, one can utilize an inferred loss rate (ILR). In the existing literature, it has been demonstrated that this indicator has sufficiently close properties to the actual loss rate to facilitate capital adequacy analysis. The current study provides complete mathematical proof of an earlier-stated conjecture, that ILR can be instrumental in identifying a conservative upper bound of the capital adequacy requirement of a bank credit portfolio, using the law of large numbers and other techniques from measure-theory-based probability. The assumptions required in this proof are less restrictive, reflecting a more realistic view. In the current study, additional empirical evidence of the usefulness of the indicator is provided, using publicly available data from the Bulgarian National Bank. Despite the definite conservativeness of the capital buffer implied from the analysis of ILR, the empirical analysis suggests that it is still within the regulatory limits. Analyzing ILR together with the Inferred Rate of Default, we conclude that the indicator provides signals about a bank portfolio’s credit risk that are relevant, timely, and adequately inexpensive.

Purpose This study explores the varying role of financial literacy in shaping households’ credit and loan choices. It addresses a gap in the literature by examining how financial literacy is prospectively associated with holding credit or loans and transitions between different credit portfolios. Design/methodology/approach The study utilizes data from three waves of the Panel Study of Income Dynamics (PSID) survey. Household credit portfolios were identified using latent class analysis, followed by the estimation of a latent transition model to evaluate the relationship between financial literacy and transitions among different credit portfolio states. A “what-if” analysis was conducted to illustrate a likely long-term evolution of household credit portfolios under the assumption of a maximum financial literacy score on the financial literacy scale. Findings Consistent with theoretical predictions, the study finds a positive link between financial literacy and transitioning to a state where credit or loans are present in the household financial portfolio. Credit portfolios exhibit notable persistence over time, with non-indebted households having the highest likelihood of remaining in their state and medical debtors the lowest. Financial literacy significantly influences transitions into multiple and mortgage debtor classes but does not affect transitions related to medical, educational or credit card debt. At maximum financial literacy, the long-term equilibrium of household credit and loan holdings would likely shift toward a larger share of multiple and mortgage debtor households and a decline in non-indebted households. Originality/value This research addresses a critical gap in the literature on the relationship between financial literacy and financial inclusion on the borrowing side of the household balance sheet, including the choice of credit product type. It demonstrates that greater financial literacy increases the likelihood of holding multiple credits and loans, challenging the assumption that financial literacy always leads to universally desirable financial decisions. Furthermore, the study highlights the differential impact of financial literacy on credit choices, underscoring the complexity of credit decisions and the practical significance of financial literacy in shaping consumer credit portfolios.