Credit Portfolio Research Articles

Simulating Credit Loss Distributions: Empirical Versus the Vasicek Model

Because credit losses can be substantial, managing credit risk is a focus area of risk measurement and management. It is important for financial institutions to select credit risk models that accurately forecast losses. The Basel Committee on Banking Supervision (BCBS) chose the closed-form single risk factor Vasicek model for regulatory capital calculations. In this article, its forecast accuracy is compared with empirical loss distributions using simulated probabilities of default and losses given default. The effect of altering probabilities of default on asset correlations was analysed and how this affects credit portfolio loss distributions. The robustness of the Vasicek model against five different portfolios with unique compositions was explored: results highlight two key findings. Firstly, the Vasicek model is a good approximation of credit losses for a portfolio that does not contain dominating loans (it is, after all, based on the assumption of large-scale homogeneity). Secondly, the Vasicek model is a good approximation for expected loss (ELs) but lacks accuracy when determining extreme unexpected losses (ULs). Finally, credit capital requirements as a function of two variables are presented which reveals novel ways of viewing these values.

Особливості управління кредитним портфелем та кредитними ризиками комерційного банку в умовах необхідності стимулювання інвестиційних процесів в економіці

The article explores the theoretical and methodological aspects of managing the loan portfolio and credit risks of a commercial bank in the context of the need to stimulate investment processes in the economy. The article considers the essential characteristics of the loan portfolio of a commercial bank and allocates its key features with clarification of their economic content in terms of the qualitative aspect of formation and management of the pool of credit assets. The study examines current approaches to assessing the credit portfolio of a commercial bank, taking into account its key characteristics. Indeed, based on the results of monitoring the quality of the credit portfolio, it is possible to formulate a set of proposals for managing credit assets and assess the adequacy of measures implemented by the bank's management in the face of economic uncertainty to maintain competitive positions on the credit services market. A review of the dynamics of lending to non-financial corporations and households by maturity is carried out through the prism of the potential use of these borrowed financial resources to intensify the investment activity of economic entities.

Features of Managing the Credit Portfolio of Banking Institutions During Wartime

The article analyzes the features of managing the credit portfolios of Ukrainian banking institutions during wartime, focusing on the impact of macroeconomic instability and rising credit risks on banks' lending activities. The study reviews key theoretical approaches to credit risk management, such as the KMV model and liquidity theory, as well as practical aspects of portfolio diversification and cluster analysis of credit portfolios. A coefficient analysis of the Ukrainian banking sector from 2015 to 2023 is conducted to assess the effectiveness of credit portfolio management during the war. The aim of the study is to analyze the specific features of managing the credit portfolios of Ukrainian banking institutions during wartime, evaluate the effectiveness of managerial decisions aimed at minimizing credit risks, and identify the main factors affecting banks' lending activity during the period of martial law. Methodology. The research employs general scientific methods, including analysis and synthesis for assessing macroeconomic risks, coefficient analysis to examine the state of bank lending, and comparative methods to evaluate the effectiveness of various risk management approaches. Results. The study reveals that the war significantly affects the quality of bank assets and borrowers' creditworthiness, leading to an increase in non-performing loans. Asset diversification and credit policy optimization are proposed as tools to minimize risks in crisis conditions.

Quantifying credit portfolio sensitivity to asset correlations with interpretable generative neural networks

Quantifying credit portfolio sensitivity to asset correlations with interpretable generative neural networks

Saddlepoint Approximations for Credit Portfolio Distributions with Applications in Equity Risk Management

Saddlepoint Approximations for Credit Portfolio Distributions with Applications in Equity Risk Management

Optimization of the Credit Portfolio and Methodology for Evaluating a Public Support Policy: Case of the Support Fund for Large Ivorian Enterprises (FSGE)

Optimization of the Credit Portfolio and Methodology for Evaluating a Public Support Policy: Case of the Support Fund for Large Ivorian Enterprises (FSGE)

An Application of Credit Portfolio Modelling and CDO Pricing

An Application of Credit Portfolio Modelling and CDO Pricing

Regulatory Intervention Effectiveness and Performance of Financial Institutions in Nigeria.

Deposit Money Banks have over the years made good contributions to Nigeria’s economic development. However much remains to be done as various regulatory interventions implemented to ensure safe and sound financial services delivery have not achieved the expected results as Nigerian banks still carry poor credit portfolios, illiquidity, weak asset quality, and high interest rates and this may be attributed to sub-optimal increase in asset base, increasing loan loss provision, huge non-performing loan, poor earnings of non-interest income and return on assets. This study adopted ex-post facto design using multiple regressions estimation techniques to analyse the data which was extracted from annual financial statements of three (3) foremost DMBs in Nigeria (UBA, FBN and GTB). The study revealed that combined variations in the institutions intervention effectiveness (shareholders fund, reserve requirements, statutory reserve, asset quality and prime lending rate) have resulted into 60% changes in all the explanatory variables of bank performance. It is therefore recommended that the CBN should be more proactive in the exercise of their regulatory intervention functions when an indication emerges that any of the banks’ are experiencing liquidity crisis to avoid systemic distress in the banking industry as intermediation of funds can get disrupted and liquidity challenges turn into reputational damage.

How to Construct a Long-Only Multifactor Credit Portfolio?

How to Construct a Long-Only Multifactor Credit Portfolio?

ՀՀ առևտրային բանկերի կապիտալի համարժեքության և իրացվելիության ռիսկերի գնահատում / Assessment of the Risks of Capital Adequacy and Realization of RA Commercial Banks

This article isdevoted to the assessment the current state of reliability and stability of RA commercial banks. The research presented situational problems arising from current global challenges, in particular, based on the financial indicators of the fourth quarter of 2023 interim reports, to assess the behavior of banks' capital adequacy and liquidity, as well as the main indicators characterizing the risks of normative capital, in case of a decline in the economic activity of the country, in case of unreliable classification of 5%, 10%, 20% and 30% of the credit portfolio of RA commercial banks, based on the financial indicators of the interim reports of the fourth quarter of 2023. The grounds of insolvency established by the banking legislation of the Republic of Armenia do not theoretically allow the formation of negative capital in banks, but in practice it is possible if the latter hide the real quality of assets in the financial statements.

Agricultural Mutual Insurance in Asia, Latin America, and the Caribbean: An Integrative Review of the Micro-Level Schemes

Risk sharing is an excellent complement to risk reduction in the agricultural sector as two of the four main risk management strategies. Agricultural Mutual Insurance (AMI) is gradually becoming the most sustainable way to promote insurance products, specifically regarding farm insurance. This study aims to answer the following questions: What do successful schemes have in common? What triggers their particularities? Which approach still needs to be implemented that could be relevant? Additionally, how the Caribbean Catastrophe Risk Insurance Facility (CCRIF SPC) could be an opportunity for Caribbean countries such as Haiti to develop micro-insurance structures that effectively reach the farm level?To address these questions, we reviewed various papers on AMI schemes in Asia, Latin America, and the Caribbean. By searching for ‘Agricultural Insurance’ and ‘Mutual Insurance’ through trustworthy scientific databases such as ScienceDirect, Google Scholar, Scopus, and MDPI, we found 1091 hits by April 2024. We considered papers in English or French, published in journals with DOI or URL, official reports from countries or United Nations organizations, World Bank reports, books, and approved dissertations. Based on their suitability, we reviewed 58 papers, focusing on countries where micro-level mutual insurance has been implemented, such as Japan, China, India, Bangladesh, Nepal, and Mexico.Successful agricultural mutual insurance schemes share relevant features, such as local government involvement and low premium cost (≤ 10% of the sum insured). Without reinsurance, mutual insurance funds are inadequate against catastrophes; hence, they resort to the international market for reinsurance if not supported by government reinsurance. Mutual insurance is generally developed among farmers cultivating similar crops or belonging to a cooperative, where subscriptions can be individual or group-based. Agricultural loans often drive farm insurance, enhancing the agricultural credit portfolio. Countries with high disaster risk levels, like Haiti, Puerto Rico, Myanmar, and the Philippines, are potential recipients of funds from the World Bank Cat bond and the CCRIF. The study suggests that AMI implemented as a public-private partnership or following a cross-sector model is more likely to succeed.The study argues that Agricultural Mutual Insurance funds for disasters such as hurricanes and floods are feasible in Haiti and other vulnerable Caribbean countries, supported by financial structures like the World Bank CAT bond and the CCRIF SPC.The study provides insights into an innovative approach to be implemented in countries frequently experiencing disasters where governments cannot highly subsidize insurance premiums for farmers. While focusing on Haiti, the suggestions can also apply to Puerto Rico, Myanmar, and the Philippines. Specifically, the paper calls for Haitian leaders to include farmers as contributors and beneficiaries of the CCRIF SPC.This study develops a business model canvas describing the relevant features that ensure the viability and effectiveness of an AMI scheme. It is unique in providing a pattern based on successful models and highlighting what countries facing similar natural disaster exposures can learn from each other to enhance resilience and adaptation to climate risks.

Changing the Dollar Exchange Rate Up and Down and its Impact on the Performance of Iraqi Commercial Banks

The study examines the impact of the dollar exchange rate on Iraqi commercial banks' performance from 2016 to 2020. It uses secondary data from 10 banks, representing 80% of Iraq's total assets. Results show a negative effect of the dollar's rise on banks' profitability, liquidity, credit quality, and operational efficiency. Conversely, a decline in the dollar's price increases banks' profitability, liquidity, credit portfolio quality, and resource efficiency. Recommendations include diversifying revenue sources, increasing coverage ratios, restructuring credit portfolios, and developing information and financial supervision systems.

Bonds with Benefits: Impact Investing in Corporate Debt

The regulatory focus on quantifiable sustainable investing shifts investors’ demand toward impact products, which creates challenges in achieving their primary target of outperformance. This study demonstrates the implications of sustainable investment in actively managed credit portfolios using carbon emissions, Sustainable Development Goals (SDGs), and green bonds. All three measures exhibit a low correlation with systematic factors, such as value and momentum, providing an opportunity for a sustainable alpha. Furthermore, we demonstrate a concave relationship between outperformance and sustainability. Therefore, systematic investors achieve a sustainable portfolio at a low cost, whereas sustainability-oriented investors harness factor returns and meet their initial targets.

Evaluating the impact of COVID-19 on the monetary crisis by machine learning

In this study, machine learning is examined in relation to commercial machine learning's resilience to the COVID-19 pandemic-related crisis. Two approaches are used to assess the pandemic's impact on machine learning risk, as well as a method to prioritize sectors according to the crisis's potential negative consequences. I conducted the study to determine Santander machine learning's resilience. The data mining area offers prospects for COVID-19's future. A total of 13 machine learning demos were selected for its organization. The Hellweg strategy and the technique for order preference by similarity to ideal solution (TOPSIS) technique were utilized as direct request strategies. Parametric assessment of machine learning versatility in business was based on capital sufficiency, liquidity proportion, market benefits, and share in an arrangement of openings with a perceived disability, and affectability of machine learning's credit portfolio to monetary hazard. As a result of the COVID-19 pandemic, these enterprises were ranked according to their threat. Based on the findings of the research, machine learning worked the best for the pandemic. Meanwhile, machine learning suffered the most during the downturn. It can be seen, for example, in conversations about the impact of the pandemic on developing business sector soundness and managing financial framework solidity risk.

A generalised latent Poisson factor modelling approach for default correlations in credit portfolios

Default risk is one of the major concerns for lending institutions and banking regulators. This paper focuses on the analysis of default data, using a new approach based on generalised latent Poisson factor models. In this case, the correlation structure of the default events is driven by a small number of common latent factors. Conditional to these factors, the defaults become independent and each default sequence is fitted to a generalised linear model with Poisson response and log-link function. This model provides a flexible framework for the computation of the value-at-risk and the expected shortfall of a credit portfolio. The practical implementation of the proposed local Fisher scoring estimation algorithm is illustrated by a Monte Carlo simulation study. Then, a real scenario, with default data taken from a large database provided by Standard & Poor's, is used to analyse the empirical behaviours of the different risk measures. The achieved results show promising performance.

The Financial Dimensions of the Entrepreneurship Environment Supporting Small Enterprises: An Applied Study

Small and micro enterprises play a very important role in supporting the Egyptian economy, as they contribute to achieving sustainable development in its economic, social and political dimensions, especially when the state suffers from scarcity of natural resources and the main investment available to it is in the human element, and this is evidenced by the fact that the Social Fund for Development pumped Financing loans for small and micro projects, where the total actual disbursement to the final beneficiary amounted to about 2.4 billion pounds, which financed about 113.7 thousand small and micro projects that provided about 162.5 thousand job opportunities, and the total grants spent on infrastructure, community development and training amounted to (376.2) million pounds It provided 6.1 million work days, in addition to 4,753 job opportunities during the training. With the belief of the political leaders in Egypt in the importance of small and medium enterprises in supporting the national economy and providing job opportunities for young people, President Abdel Fattah El-Sisi launched an initiative in early 2016, instructing the Central Bank of Egypt to provide 200 billion pounds to support small and medium enterprises with an interest rate not exceeding 5%. The CBE increased loans to small and medium enterprises, calling for 20% of credit portfolios within 4 years, with a total of 200 billion pounds. It also asked banks to present their strategies to achieve this goal within 4 years, The study concluded with several findings, the most important of which is the key role of national initiatives in supporting small businesses in the Egyptian environment. And the role of entrepreneurship in developing the national economy. Keywords: Entrepreneurship – Small enterprises – Egyptian environment

The Financial Dimensions of the Entrepreneurship Environment Supporting Small Enterprises: An Applied Study

Small and micro enterprises play a very important role in supporting the Egyptian economy, as they contribute to achieving sustainable development in its economic, social and political dimensions, especially when the state suffers from scarcity of natural resources and the main investment available to it is in the human element, and this is evidenced by the fact that the Social Fund for Development pumped Financing loans for small and micro projects, where the total actual disbursement to the final beneficiary amounted to about 2.4 billion pounds, which financed about 113.7 thousand small and micro projects that provided about 162.5 thousand job opportunities, and the total grants spent on infrastructure, community development and training amounted to (376.2) million pounds It provided 6.1 million work days, in addition to 4,753 job opportunities during the training. With the belief of the political leaders in Egypt in the importance of small and medium enterprises in supporting the national economy and providing job opportunities for young people, President Abdel Fattah El-Sisi launched an initiative in early 2016, instructing the Central Bank of Egypt to provide 200 billion pounds to support small and medium enterprises with an interest rate not exceeding 5%. The CBE increased loans to small and medium enterprises, calling for 20% of credit portfolios within 4 years, with a total of 200 billion pounds. It also asked banks to present their strategies to achieve this goal within 4 years, The study concluded with several findings, the most important of which is the key role of national initiatives in supporting small businesses in the Egyptian environment. And the role of entrepreneurship in developing the national economy. Keywords: Entrepreneurship – Small enterprises – Egyptian environment

ANALYSIS OF CUSTOMER PROFILE CHARASTERISTIC WITH CREDIT QUALITY USING THE CLUSTERING METHOD FOR RISK MITIGATION AND SMALL MEDIUM ENTERPRISE CREDIT PORTOFOLIO EXPANSION PLANNING

in managing the Small Medium Enterprise credit portfolio. The strategy taken by a bank must be adapted to the general characteristics of the target debtors for business expansion and risk mitigation so that business expansion and risk mitigation efforts can be carried out effectively for certain groups. Based on these problems, the purpose of this research is to identify groups of debtors with similar characteristics based on debtor profile data and their credit quality, and to understand the differences in credit risk and opportunities for business expansion among these groups. The data used is the profile of the distribution of debtors from Bank ABC of 5088 debtors. The analysis technique used is K-Means and KMedoids with the evaluation criteria used are silhouette score, davies-bouldin index and computation time. Completion of the optimal number of groups is done by analyzing the WSS graph using the elbow method. Analysis of business expansion and risk reduction is carried out separately where business expansion analysis is carried out for debtors with a collectibility value of 1 and risk reduction analysis is carried out for debtors who have a collectibility value of 2 – 5. The results show that there are 5 groups in the business expansion analysis and 3 groups in risk mitigation analysis. The high value of the silhouette index and davies-bouldin index makes the grouping results have a strong structure. The KMedoids method is used in this analysis because it has better evaluation criteria than K-Means. Priority is also determined for each group formed so that it can be determined which group has the greatest opportunity to become target expansion and which group has the greatest risk that needs to be mitigated. In general, business sectors such as agriculture and plantations are experiencing a decline in economic activity in 2022, so it needs attention from the bank so that it does not disrupt the credit portfolio. To complement the results of this study, an analysis of external and internal business health needs to be carried out in more depth so that the big picture of credit problems at Bank ABC can be identified.

Fast approximation methods for credit portfolio risk calculations

Credit risk is one of the main risks financial institutions are exposed to. Within the last two decades, simulation-based credit portfolio models became extremely popular and replaced closed-form analytical ones as computers became more powerful. However, especially for non-homogenous and non-granular portfolios, a full simulation of a credit portfolio model is still time consuming, which can be disadvantageous within some use cases like credit pricing or within stress testing situations where results must be available very quickly. For this purpose, we investigate if methods based on artificial intelligence (AI) can be helpful to approximate a credit portfolio model. We compare the performance of AI-based methods within three different use cases with suitable non AI-based regression methods. As a result, we see that AI-based methods can generally capture portfolio characteristics and speed-up calculations but - depending on the specific use case and the availability of training data - they are not necessarily always the best choice. Particularly, considering the time and costs for collecting data and training of the complex algorithms, non-AI-based methods can be as good as or even better than AI-based ones, while requiring less computational effort.

The effect of moral hazard on the SMEs credit portfolio guaranteed by Colombia's National Guarantee Fund

This article determines the effect of moral hazard on the probability of default of the credit portfolio of small and medium-sized companies guaranteed by Colombia's National Guarantee Fund. A copula methodology with two logit models with traditional and moral Hazard financial ratios was used. The results show that the probabilities of default have the same pattern, evidencing that by incorporating the ratios of moral hazard, no significant variations are shown in the results. Thus, the moral hazard categories become an important tool not only at the calculation level of individual default probability but also in a portfolio.