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1

Levin, V., and S. Khonov. "Exact maximum likelihood estimator for the probability of default on estimation provision consumer credit portfolio of the bank." Bulletin of Science and Practice, no. 2 (February 15, 2017): 186–93. https://doi.org/10.5281/zenodo.291870.

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In the context of increasing competition in the banking market, increasing regulatory requirements for transparency and sound risk–creation on this basis of adequate risk provisions in the banking sector is of paramount importance. In this paper, firstly it is proposed to use for estimating credit risks the exact maximum likelihood estimators (MLE) of the structure of stratified population for any sizes of the credit portfolio. These exact MLE could be applied to estimate Basel-II risk parameter PD (Probability of Default) and could be used to optimise provisions for covering expected losses o
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2

Setiawan, Rahmat, Octavia Reniar Putri, and Aulia Claraning Sukmawati. "Diversifikasi Portofolio Kredit, Risiko dan Return Bank." Jurnal Akuntansi 15, no. 1 (2023): 189–99. http://dx.doi.org/10.28932/jam.v15i1.6376.

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Banks as financial intermediaries, can diversify their credit portfolios into different sectors. This study aims to determine the effect of credit portfolio diversification on risks borne and returns earned by banks. The sample in this study was 61 conventional commercial banks in Indonesia for the 2012-2014 period with a total of 112 observations. The results show that credit portfolio diversification has a significant negative effect on bank risk and return. In other words, a more diversified credit portfolio can reduce bank risk and return. Keywords: diversification, loan portfolio, bank’s
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3

Lefcaditis, Constantinos, Anastasios Tsamis, and John Leventides. "Concentration risk model for Greek bank's credit portfolio." Journal of Risk Finance 15, no. 1 (2014): 71–93. http://dx.doi.org/10.1108/jrf-06-2013-0043.

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Purpose – The IRB capital requirements of Basel II define the minimum level of capital that the bank has to retain to cover the current risks of its portfolio. The major risk that many banks are facing is credit risk and Basel II provides an approach to calculate its capital requirement. It is well known that Pillar I Basel II approach for credit risk capital requirements does not include concentration risk. The paper aims to propose a model modifying Basel II methodology (IRB) to include name concentration risk. Design/methodology/approach – The model is developed on data based on a portfolio
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4

Di Clemente, Annalisa. "Modeling Portfolio Credit Risk Taking into Account the Default Correlations Using a Copula Approach: Implementation to an Italian Loan Portfolio." Journal of Risk and Financial Management 13, no. 6 (2020): 129. http://dx.doi.org/10.3390/jrfm13060129.

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This work aims to illustrate an advanced quantitative methodology for measuring the credit risk of a loan portfolio allowing for diversification effects. Also, this methodology can allocate the credit capital coherently to each counterparty in the portfolio. The analytical approach used for estimating the portfolio credit risk is a binomial type based on a Monte Carlo Simulation. This method takes into account the default correlations among the credit counterparties in the portfolio by following a copula approach and utilizing the asset return correlations of the obligors, as estimated by rigo
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5

Siregar, Yosua Sopater, Apriani Dorkas Rambu Atahau, and Imanuel Madea Sakti. "ANALISIS PORTOFOLIO KREDIT, RISIKO, DAN RETURN BANK UMUM KONVENSIONAL." Jurnal Manajemen 19, no. 1 (2022): 18–38. http://dx.doi.org/10.25170/jm.v19i1.2334.

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This study aims to determine the credit portfolio strategy (focus or diversification strategy) based on the economic sector in conventional commercial banks grouped by business activity (BUKU) in the period January 2016 - December 2018 and analyze the effect of credit portfolio concentration and credit risk on rates of return. This study uses secondary data obtained from Indonesian Banking Statistics at the Financial Services Authority (OJK). This study used 4 samples, namely BUKU I, BUKU II, BUKU III, BUKU IV. Bank return as dependent variable was measured by Return on Assets (ROA) whereas Co
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6

Malla, Buddhi Kumar. "Credit Portfolio Management in Nepalese Commercial Banks." Journal of Nepalese Business Studies 10, no. 1 (2018): 101–9. http://dx.doi.org/10.3126/jnbs.v10i1.19138.

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Credit portfolio management is a key function for banks (and other financial institutions, including insurers and institutional investors) with large, multifaceted portfolios of credit, often including illiquid loans (Nario, Pfister, Poppensieker & Stegemann, 2016). After global financial crisis of 2007-2008, the credit portfolio management function has become most crucial functions of the bank and financial institutions. The Basel III, third installment of Basel accord was developed after crisis to strengthen bank capital requirements by increasing bank liquidity and decreasing bank lever
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7

Vosloo, Pieter G., and Paul Styger. "The process approach to the management of loan portfolios." Journal of Economic and Financial Sciences 3, no. 2 (2009): 171–88. http://dx.doi.org/10.4102/jef.v3i2.341.

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Many factors impacted the credit risk environment in the past decade, the most significant of which were the Basel II Capital Accord requirements. Foremost in the financial industry’s focus was, and still is, the implementation of these requirements and their associated outcomes. In the aftermath of the Basel II implementation, credit risk managers’ focus will return to understanding the portfolio philosophy in managing their credit portfolios. They will be required to adapt an integrated risk management framework, taking into account the interdependence of various building blocks, data fields
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8

Orlova, E. V. "Mechanism and model of credit portfolio diversification." Issues of Risk Analysis 17, no. 1 (2020): 78–89. http://dx.doi.org/10.32686/1812-5220-2020-17-1-78-89.

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Under conditions of demand for credit resources growing in Russian economy the importance of credit risks assessment and their influence on the credit organizations efficiency is increased. Empirical studies show that credit risks in the banking today are increasing nonlinearly relative to the main characteristics of the credit — the level of credit risk, credit terms, interest rate. Therefore, the formation of the most acceptable from the point of view of risk reducing of the bank’s credit portfolio is a scientifically based and practically important problem. The aim of the work is to justify
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9

Klotz, Stefan, and Andreas Lindermeir. "Multivariate credit portfolio management using cluster analysis." Journal of Risk Finance 16, no. 2 (2015): 145–63. http://dx.doi.org/10.1108/jrf-09-2014-0131.

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Purpose – This paper aims to improve decision making in credit portfolio management through analytical data-mining methods, which should be used as data availability and data quality of credit portfolios increase due to (semi-)automated credit decisions, improved data warehouses and heightened information needs of portfolio management. Design/methodology/approach – To contribute to this fact, this paper elaborates credit portfolio analysis based on cluster analysis. This statistical method, so far mainly used in other disciplines, is able to determine “hidden” patterns within a data set by exa
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10

Aris, Abdul Shaheer, and Ekramuddin Rahimi. "The Impact of Loan Portfolio Management on Credit Risk: Evidence from Banking Sector of Afghanistan." Journal of Economics, Finance and Accounting Studies 5, no. 5 (2023): 12–22. http://dx.doi.org/10.32996/jefas.2023.5.5.2.

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This article empirically examined the effects of loan portfolio diversification on commercial banks' credit risk in Afghanistan from 2007 to 2019. In this paper, the annualized data is used to run the regression model, and the least-squares method was followed; meanwhile, the Hirschman-Herfindahl index is used as a diversification index. Eventually, the estimation results in compliance with the traditional theory of portfolio management represent that loan portfolio diversification has a negative-significant impact on credit risk, while the capital adequacy ratio coefficient according to the m
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11

Tunay, K. Batu, Hasan F. Yuceyılmaz, and Ahmet Çilesiz. "An International Comparison on Excessive Credit Expansion, Credit Guarantee Programs and The Risks Arising." Khazar Journal of Humanities and Social Sciences 23, no. 1 (2020): 83–102. http://dx.doi.org/10.5782/2223-2621.2020.23.1.83.

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Crediting in the banking sector plays an important role in all developed and developing countries. For this reason, it is monitored continuously by public authorities and measures are taken to control credit supply in economic growth periods. On the other hand, in an economic slowdown, when banks are reluctant to increase their credit portfolio, public credit guarantee programs are put into use to increase the credit supply. In this study, a sample covering 26 advanced and emerging economies was analyzed, and the effects of credit gap, credit guarantees and economic growth on credits and arisi
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12

Dmytryshyn, Lesia, and Ivan Blahun. "A model for achieving the allocative efficiency of credit resources in Ukraine’s banking system." Banks and Bank Systems 11, no. 3 (2016): 8–16. http://dx.doi.org/10.21511/bbs.11(3).2016.01.

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The article presents a model for achieving the allocative efficiency of credit resources in Ukraine’s banking system. The research involves establishing a set of criteria for assessing a borrower’s creditworthiness and analyzing them by means of the discriminant analysis, Helwig’s methods, cluster analysis, the dendrite method, and principal component analysis; the methods are, then, contrasted. This is followed by designing an optimal credit portfolio of the banking system and comparing it with actual credit portfolios with the help of similarity metrics. Keywords: banking system, borrower’s
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13

Marchenko, Olha V., Olha S. Petrykiva, and Kateryna O. Korobko. "Minimizing Credit Risk and Improving the Quality of the Bank’s Loan Portfolio." Business Inform 11, no. 538 (2022): 205–10. http://dx.doi.org/10.32983/2222-4459-2022-11-205-210.

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The article considers the main factors that form credit risk and determines the role of credit risk in the process of formation of the credit portfolio of a commercial bank. It is determined that bank lending involves the functioning of a complex mechanism that includes certain actions aimed at attracting cheap funds and their use in accordance with the terms of the established lending policy, taking into account the minimum risk and maximum profit. As you know, the main source of income of banks is the profit from lending. In this regard, the main problem facing the bank’s management today is
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14

Buhel, Yuliia. "Features of Managing the Credit Portfolio of Banking Institutions During Wartime." Economic Analysis, no. 34(3) (2024): 246–56. https://doi.org/10.35774/econa2024.03.246.

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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
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15

Kucukkocaoglu, Guray, and M. Ayhan Altintas. "Using non-performing loan ratios as default rates in the estimation of credit losses and macroeconomic credit risk stress testing: A case from Turkey." Risk Governance and Control: Financial Markets and Institutions 6, no. 1 (2016): 52–63. http://dx.doi.org/10.22495/rgcv6i1art6.

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In this study, inspired by the Credit Portfolio View approach, we intend to develop an econometric credit risk model to estimate credit loss distributions of Turkish Banking System under baseline and stress macro scenarios, by substituting default rates with non-performing loan (NPL) ratios. Since customer number based historical default rates are not available for the whole Turkish banking system’s credit portfolio, we used NPL ratios as dependent variable instead of default rates, a common practice for many countries where historical default rates are not available. Although, there are many
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16

Yamanaka, Suguru. "Random thinning model with a truncated credit quality vulnerability factor: Application to top-down-type credit risk assessment." International Journal of Financial Engineering 06, no. 03 (2019): 1950024. http://dx.doi.org/10.1142/s2424786319500245.

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In the top-down approach of intensity-based credit risk modeling, a procedure called “random thinning” is needed to obtain credit event intensities for sub-portfolios. This paper presents a random thinning model incorporating a risk factor called the credit quality vulnerability factor (CQVF) to capture time-series variation in credit event occurrence in a target sub-portfolio. In particular, we propose a type of CQVF that follows truncated normal distributions specified by macroeconomic variables. Using credit event samples of Japanese firms, our empirical analysis aims to clarify the applica
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17

Ticona Aguilar, Pablo. "La calidad de la cartera de créditos y su incidencia en la solvencia financiera de las Cooperativas de Ahorro y Crédito de la región Puno, 2012-2014." Semestre Económico 6, no. 2 (2017): 125–52. http://dx.doi.org/10.26867/se.2017.v06i2.69.

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The purpose of this study was to determine the factors that have an effect on the deterioration of the quality of the credits portfolio and to estimate the incidence of the quality of the credit portfolio in the financial solvency of the savings and credit cooperatives of the Puno region, period 2012 - 2014; the problem that credit and savings cooperatives are facing is the high delinquency of more than 10%, which affects the quality of the credit portfolio and puts financial solvency in risk. For the achievement of the proposed objectives, the non-experimental research design, descriptive and
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18

Waqar Azeem Naqvi, Syed M., Tahseen M. Khan, and Sayyid Salman Rizavi. "The Efficiency of Credit Portfolio Management in Pakistan’s Banking Sector." Lahore Journal of Business 4, no. 2 (2016): 51–72. http://dx.doi.org/10.35536/ljb.2016.v4.i2.a3.

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This study highlights the differences in performance of commercial banks operating in Pakistan in the context of credit portfolio management. Specifically, we look at their credit allocation policies and outcomes in the shape of nonperforming loans (NPLs). We categorize a sample of 34 banks into four major groups: public, private, Islamic and foreign banks. The study tests several hypotheses related to the overall efficiency of banks’ credit portfolio management over time as well as the drivers of NPLs and priority sectors for lending across these four categories. The findings broadly suggest
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19

BUCAY, NISSO, and DAN ROSEN. "Applying Portfolio Credit Risk Models to Retail Portfolios." Journal of Risk Finance 2, no. 3 (2001): 35–61. http://dx.doi.org/10.1108/eb043466.

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20

Rhee, Dong-Woo, Hyoung-Goo Kang, and Soo-Hyun Kim. "Strategic Asset Allocation Of Credit Guarantors." Journal of Applied Business Research (JABR) 31, no. 5 (2015): 1823. http://dx.doi.org/10.19030/jabr.v31i5.9406.

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<p>How to manage the portfolio of credit guarantors is important in practice and public policy, but has not been investigated well in the prior literature. We empirically compare four different approaches in managing credit guarantor portfolios. The four approaches are equal weighted, minimum variance, mean variance optimization and equal risk contribution methods. In terms of risk return ratio, the mean variance optimization model performs best in out-of-sample test. This result contrasts with previous findings against mean variance optimization. Our results are robust. The results do n
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21

Anagnostou, Ioannis, Sumit Sourabh, and Drona Kandhai. "Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory." Complexity 2018 (2018): 1–15. http://dx.doi.org/10.1155/2018/6076173.

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Portfolio credit risk models estimate the range of potential losses due to defaults or deteriorations in credit quality. Most of these models perceive default correlation as fully captured by the dependence on a set of common underlying risk factors. In light of empirical evidence, the ability of such a conditional independence framework to accommodate for the occasional default clustering has been questioned repeatedly. Thus, financial institutions have relied on stressed correlations or alternative copulas with more extreme tail dependence. In this paper, we propose a different remedy—augmen
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22

Mühlbacher, Andreas, and Thomas Guhr. "Extreme Portfolio Loss Correlations in Credit Risk." Risks 6, no. 3 (2018): 72. http://dx.doi.org/10.3390/risks6030072.

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The stability of the financial system is associated with systemic risk factors such as the concurrent default of numerous small obligors. Hence, it is of utmost importance to study the mutual dependence of losses for different creditors in the case of large, overlapping credit portfolios. We analytically calculate the multivariate joint loss distribution of several credit portfolios on a non-stationary market. To take fluctuating asset correlations into account, we use an random matrix approach which preserves, as a much appreciated side effect, analytical tractability and drastically reduces
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23

Huang, Huijun, and Yuzhong Li. "Optimization of a Rural Portfolio Credit Granting System Using Improved Two-Dimensional Strip Packing Grouping Delay Problem." Systems 10, no. 5 (2022): 193. http://dx.doi.org/10.3390/systems10050193.

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Rural preferential loans usually take the form of portfolio credits. From the perspective of public interest, the total delay time for obtaining loans is expected to be minimized. To use rural portfolio credits effectively, the two-dimensional strip packing grouping delay problem (2SPGDP) is improved to optimize the rural portfolio credit granting system. First, 2SPGDP is established by adding grouping constraints and the latest start time constraints to the two-dimensional strip packing problem, and the total delay is taken as the optimization objective. Second, based on the depth search reve
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24

DORFLEITNER, GREGOR, and TAMARA PFISTER. "JUSTIFICATION OF PER-UNIT RISK CAPITAL ALLOCATION IN PORTFOLIO CREDIT RISK MODELS." International Journal of Theoretical and Applied Finance 17, no. 06 (2014): 1450039. http://dx.doi.org/10.1142/s0219024914500393.

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Risk capital allocation is based on the assumption that the risk of a homogeneous portfolio is scaled up and down with the portfolio size. In this article we show that this assumption is true for large portfolios, but has to be revised for small ones. On basis of numerical examples we calculate the minimum portfolio size that is necessary to limit the error of gradient risk capital allocation and the resulting error in a portfolio optimization algorithm or pricing strategy. We show the dependency of this minimum portfolio size on different parameters like the probability of default and on the
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25

Pohorelenko, N. P., and A. Y. Yurchenko. "Evaluating the Processes of Management of Credit Portfolio of JSC CB «PrivatBank»." Business Inform 10, no. 513 (2020): 325–32. http://dx.doi.org/10.32983/2222-4459-2020-10-325-332.

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The article is aimed at studying the status and structure of the credit portfolio of JSC CB «PrivatBank», also evaluating the processes of management of the bank’s credit portfolio through the computation of the coefficient of credit portfolio management efficiency. While analyzing financial indicators, a consideration and a research of the status of bank lending in modern conditions of the national economy of Ukraine were carried out. The reasons for reducing the proportion of the credit portfolio in the GDP structure during the research period are summarized. The fundamental principles of th
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26

Annalisa, Di Clemente. "The Credit Securitisation Process as a Tool of Portfolio Credit Risk Managing." STUDI ECONOMICI, no. 104 (January 2012): 5–28. http://dx.doi.org/10.3280/ste2011-104001.

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This study explores the role of the credit securitisation process in managing the credit risk amount of the banking loan portfolio, when the bank originator retains a residual equitylike class as illiquid first loss position (FLP). An Importance Sampling Monte Carlo simulation model has been implemented for estimating the portfolio credit risk amount, taking into account the portfolio credit risk mitigation effect provided by the credit securitisation process. This study identifies the credit asset pool able to produce the larger effect of credit risk reduction on the loan portfolio, when the
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27

Mercurio, Peter Joseph, Yuehua Wu, and Hong Xie. "Option Portfolio Selection with Generalized Entropic Portfolio Optimization." Entropy 22, no. 8 (2020): 805. http://dx.doi.org/10.3390/e22080805.

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In this third and final paper of our series on the topic of portfolio optimization, we introduce a further generalized portfolio selection method called generalized entropic portfolio optimization (GEPO). GEPO extends discrete entropic portfolio optimization (DEPO) to include intervals of continuous returns, with direct application to a wide range of option strategies. This lays the groundwork for an adaptable optimization framework that can accommodate a wealth of option portfolios, including popular strategies such as covered calls, married puts, credit spreads, straddles, strangles, butterf
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28

Jakob, Kevin, and Matthias Fischer. "GCPM: A ?exible package to explore credit portfolio risk." Austrian Journal of Statistics 45, no. 1 (2016): 25–44. http://dx.doi.org/10.17713/ajs.v45i1.87.

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In this article we introduce the novel GCPM package, which represents a generalized credit portfolio model framework. The package includes two of the most popular mod- eling approaches in the banking industry namely the CreditRisk+ and the CreditMetrics model and allows to perform several sensitivity analysis with respect to distributional or functional assumptions. Therefore, besides the pure quanti?cation of credit portfolio risk, the package can be used to explore certain aspects of model risk individually for every arbitrary credit portfolio. In order to guarantee maximum ?exibility, most
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29

Kaur Brar, Jagdeep, Antoine Kornprobst, Willard John Braun, Matthew Davison, and Warren Hare. "A Case Study of the Impact of Climate Change on Agricultural Loan Credit Risk." Mathematics 9, no. 23 (2021): 3058. http://dx.doi.org/10.3390/math9233058.

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Changing weather patterns may impose increased risk to the creditworthiness of financial institutions in the agriculture sector. To reduce the credit risk caused by climate change, financial institutions need to update their agricultural lending portfolios to consider climate change scenarios. In this paper we introduce a framework to compute the optimal agricultural lending portfolio under different increased temperature scenarios. In this way we quantify the impact of increased temperature, taken as a measure of climate change, on credit risk. We provide a detailed case study of how our appr
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30

Ostrovska, N. "Modeling of credit portfolio management efficiency." Galic'kij ekonomičnij visnik 70, no. 3 (2021): 89–101. http://dx.doi.org/10.33108/galicianvisnyk_tntu2021.03.089.

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Credit operations, among the great variety of services provided by the bank, are one of the most important activities. In the assets of commercial banks, loans occupy a strong position of the most extensional and profitable items. The reliability and financial stability of commercial banks depends on the composition and structure of the bank's loan portfolio and the process of its management. Under current conditions, the development and improvement of the bank's loan portfolio management system intended to minimize the credit risks and ensure the sustainable operation of commercial banks have
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31

Sicking, Joachim, Thomas Guhr, and Rudi Schäfer. "Concurrent credit portfolio losses." PLOS ONE 13, no. 2 (2018): e0190263. http://dx.doi.org/10.1371/journal.pone.0190263.

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32

Iscoe, Ian, Alexander Kreinin, Helmut Mausser, and Oleksandr Romanko. "Portfolio credit-risk optimization." Journal of Banking & Finance 36, no. 6 (2012): 1604–15. http://dx.doi.org/10.1016/j.jbankfin.2012.01.013.

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33

Lamichhane, Basu Dev. "Credit Portfolio Management in Nepalese Microfinance Institutions (MFIs): A Shifting Guide to Credit Risk Management." Interdisciplinary Journal of Management and Social Sciences 4, no. 1 (2023): 8–20. http://dx.doi.org/10.3126/ijmss.v4i1.54097.

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This paper attempts to provide a first step toward understanding the role of credit portfolio management in Nepalese microfinance institutions (MFIs) and overcome those problems associated with credit risk management. The credit portfolio management (CPM) has become most crucial functions of the Nepalese MFIs for sound loan portfolio quality. This study is based on descriptive research design. Several findings are made through the review of the literature that is parallel to achieving the objectives of the study. MFIs are financial intermediaries ("banks") that have a direct impact on economic
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34

Zverev, Alexei, Victoria Mandron, Tatiana Rebrina, Maria Mishina, and Yulia Karavaeva. "Investment policy of the banking sector: data from Russia." Revista Amazonia Investiga 10, no. 42 (2021): 149–62. http://dx.doi.org/10.34069/ai/2021.42.06.14.

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The growing investment activity of banking sector organisations is an important condition for securing diversification of assets and obtaining additional sources of income, as well as maintaining the required level of liquidity. Economic crises and instability of stock markets affect the investment policy of a bank, the quality of its investment portfolio, and the scope of investment transactions with securities. The purpose of the research is to carry out a comprehensive analysis of the investment mechanism of the Russian banking sector and its organisation, to characterise the investment pol
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35

Шевченко, Наталія, and Марта Копитко. "PROBLEMS OF RISK MANAGEMENT AND CREDIT SECURITY OF BANKS IN CONDITIONS OF WAR AND ECONOMIC INSTABILITY." "Scientific notes of the University"KROK", no. 4(76) (December 31, 2024): 287–94. https://doi.org/10.31732/2663-2209-2024-76-287-294.

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The article considers the basic essence of the concept of “bank credit security”, which is defined as a set of measures or directions aimed at minimizing the negative risks associated with the issuance, management and repayment of loans to individuals and legal entities. It is determined that the main structural elements of credit security management by a banking institution are: formation of a loan portfolio, credit policy and credit strategy; identification of risks and factors affecting the level of credit security; insurance against credit risks: formation of reserves, diversification, set
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36

Lapshin, Viktor, and Anton Markov. "MCMC-based credit rating aggregation algorithm to tackle data insufficiency." Applied Econometrics 68, no. 4 (2022): 50–72. http://dx.doi.org/10.22394/1993-7601-2022-68-50-72.

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This paper investigates how credit rating aggregation might lead to a more efficient estimation of key portfolio risk management metrics: expected credit losses (ECL) and risk‐weighted assets (RWA). The proposed technique for credit rating aggregation is based on the Markov Chain Monte‐Carlo methodology and leads to a statistically smaller variance of ECL and RWA than the naïve and distribution‐based alternatives. This conclusion holds for three public datasets and four simulated studies. The paper results might be helpful for portfolios that suffer from data insufficiency or rely on external
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37

Chataigner, Marc, and Stéphane Crépey. "Credit Valuation Adjustment Compression by Genetic Optimization." Risks 7, no. 4 (2019): 100. http://dx.doi.org/10.3390/risks7040100.

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Since the 2008–2009 financial crisis, banks have introduced a family of X-valuation adjustments (XVAs) to quantify the cost of counterparty risk and of its capital and funding implications. XVAs represent a switch of paradigm in derivative management, from hedging to balance sheet optimization. They reflect market inefficiencies that should be compressed as much as possible. In this work, we present a genetic algorithm applied to the compression of credit valuation adjustment (CVA), the expected cost of client defaults to a bank. The design of the algorithm is fine-tuned to the hybrid structur
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38

Rizky, Bimbi Ardhana, Sudarno Sudarno, and Diah Safitri. "PENGUKURAN RISIKO KREDIT DAN PENGUKURAN KINERJA DARI PORTOFOLIO OBLIGASI." Jurnal Gaussian 7, no. 1 (2018): 43–53. http://dx.doi.org/10.14710/j.gauss.v7i1.26634.

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Except getting coupon as a profit, there is loss probability in bond investment that is credit risks investment. One way to measure the credit risk of a bond is to use the credit metrics method. It uses the ratings of the bond issuer company and the transition rating issued by the rating company for its calculations. Mean Variance Efficient Portfolio (MVEP) can be used to make an optimal portfolio so that risk can be obtained to a minimum. An assessment of portfolio performance is needed to increase confidence to invest. Sharpe index can measure portfolio performance based on return value of b
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39

BELIKOVA, Tetiana, and Marharyta PUSHKINA. "Methods for analyzing the quality of a banks loan portfolio." Economics. Finances. Law, no. 4/1 (April 30, 2020): 35–40. http://dx.doi.org/10.37634/efp.2020.4(1).8.

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Lending is one of the major banking institutions. But lending has some risks of varying degrees. The main purpose of banks is to repay loans and to maximize profits. To do this, banks need to implement an efficient, flexible and modern credit portfolio quality management system. An important element of this system is the analysis of the quality of the loan portfolio. That is why the consideration of the methods by which banks can carry out this analysis is a very actual topic. The purpose of this paper is to review methods of analyzing the quality of a bank's loan portfolio, as well as to outl
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Fischer, Matthias, Thorsten Moser, and Marius Pfeuffer. "A Discussion on Recent Risk Measures with Application to Credit Risk: Calculating Risk Contributions and Identifying Risk Concentrations." Risks 6, no. 4 (2018): 142. http://dx.doi.org/10.3390/risks6040142.

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In both financial theory and practice, Value-at-risk (VaR) has become the predominant risk measure in the last two decades. Nevertheless, there is a lively and controverse on-going discussion about possible alternatives. Against this background, our first objective is to provide a current overview of related competitors with the focus on credit risk management which includes definition, references, striking properties and classification. The second part is dedicated to the measurement of risk concentrations of credit portfolios. Typically, credit portfolio models are used to calculate the over
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SOLOVEI, Nadiia, and Ihor SKRYPNYCHENKO. "Problems of qualitative evaluation of commercial bank loan." Economics. Finances. Law, no. 1/2 (January 31, 2020): 15–19. http://dx.doi.org/10.37634/efp.2020.1(2).3.

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The article defines the nature of the loan portfolio, as well as the problems in the assessment and analysis of the commercial bank loan portfolio. In order to improve the existing credit portfolio of the bank, the dynamics, categories of the borrower ratio and the quality of the loan portfolio are analyzed, based on the obtained data, significant factors influencing the formation and management of the analyzed bank's loan portfolio are determined. Generation of a loan portfolio is usually subject to issuance of loans with maximum yield on the same terms. The profitability of a loan transactio
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Yadav, Sandeep. "Balancing Profitability and Risk: The Role of Risk Appetite in Mitigating Credit Risk Impact." International Scientific Journal of Engineering and Management 03, no. 12 (2024): 1–7. https://doi.org/10.55041/isjem01087.

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Balancing profitability and risk is a central challenge for financial institutions, especially in the context of managing credit risk. This paper explores the concept of risk appetite as a strategic framework for aligning an institution’s risk-taking activities with its financial objectives. By defining risk appetite in measurable terms, institutions can calibrate their credit risk strategies to ensure optimal decision-making that mitigates potential losses while maintaining profitability. The study examines how risk appetite influences credit decision-making processes, including credit underw
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Ivanova, Natalia A. "FEATURES OF LOAN PORTFOLIO ANALYSIS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 12/2, no. 153 (2024): 113–20. https://doi.org/10.36871/ek.up.p.r.2024.12.02.012.

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The article is devoted to the assessment of the loan portfolio of financial and credit organizations. The functions of the loan portfolio, the stages of its formation in a commercial bank, the specifics of the sale of the portfolio are considered. Attention is also paid to the analysis of the loan portfolio of financial and credit structures. The indicators of qualitative analysis of the loan portfolio are characterized, the characteristics of professional regulatory, financial and current price methods in assessing the loan portfolio are presented. In conclusion, it is noted that the loan por
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BROLL, UDO, B. MICHAEL GILROY, and ELMAR LUKAS. "MANAGING CREDIT RISK WITH CREDIT DERIVATIVES." Annals of Financial Economics 03, no. 01 (2007): 0750004. http://dx.doi.org/10.1142/s2010495207500042.

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Credit risk is one of the most important forms of risk faced by national and international banks as financial intermediaries. Managing this kind of risk through selecting and monitoring corporate and sovereign borrowers and through creating a diversified loan portfolio has always been one of the predominant challenges in bank management. The aim of our study is to examine how a risky loan portfolio affects optimal bank behavior in the loan and deposit markets, when derivatives to hedge credit risk are available. In a stochastic continuous-time framework a hedging model is developed where the b
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Adzobu, Lydia Dzidzor, Elipkimi Komla Agbloyor, and Anthony Aboagye. "The effect of loan portfolio diversification on banks’ risks and return." Managerial Finance 43, no. 11 (2017): 1274–91. http://dx.doi.org/10.1108/mf-10-2016-0292.

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Purpose The purpose of this paper is to test whether diversification of credit portfolios across economic sectors leads to improved profitability and reduced credit risks for Ghanaian banks that have been characterized by high non-performing loans in recent times (IMF, 2011). Design/methodology/approach Static and dynamic estimations, namely Prais-Winsten, fixed and random effect estimators, feasible generalized least squares as well as the system generalized methods of moments are employed on the annual data of 30 Ghanaian banks that operated between 2007 and 2014 to determine the effect of l
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Milonas, Natasa, and Gary van Vuuren. "Simulating Credit Loss Distributions: Empirical Versus the Vasicek Model." International Journal of Economics and Financial Issues 14, no. 2 (2024): 77–88. http://dx.doi.org/10.32479/ijefi.15698.

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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
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Jakubiak, Ewa. "THOUSING CREDIT CONDITIONS DURING THE CRISIS." International Journal of New Economics and Social Sciences 18, no. 2 (2023): 73–81. http://dx.doi.org/10.5604/01.3001.0054.3038.

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The purpose of this study is to discuss issues related to housing credits. This credit plays the most significant role in the portfolio of bank credits for households. At the same time, it is the most popu-lar credit among customers who are natural persons.The basic issues related to housing credit were discussed at the beginning of the article. The rese-arch and inquiries were carried out on the basis of studies of the literature on the subject and reports of the institutions of the Polish financial market.
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Ermolenko, O. M. "MINIMIZING CREDIT RISK AND IMPROVING THE QUALITY OF THE CREDIT PORTFOLIO OF THE COMMERCIAL BANK." Scientific bulletin of the Southern Institute of Management, no. 2 (June 30, 2017): 18–23. http://dx.doi.org/10.31775/2305-3100-2017-2-18-23.

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The article examines the main factors shaping the credit risk and defines the role of credit risk in the process of formation of a credit portfolio of commercial banks. In conditions of instability and financial uncertainty, credit institutions are faced with risks, including credit, because credit operations occupy the largest share in their activities. The quality of loan portfolio determines the capabilities of the Bank in its functioning on the market of credit products, which affects the level of lending activity and the possibility of recovery in the credit market. The process associated
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Ghadban, Mohammed Kareem, and Yasser Sami Hussein. "Changing the Dollar Exchange Rate Up and Down and its Impact on the Performance of Iraqi Commercial Banks." Migration Letters 21, S1 (2023): 236–48. http://dx.doi.org/10.59670/ml.v21is1.6042.

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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 infor
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Danstun, Ngonyani, and Mapesa Harun. "The Effect of Credit Collection Policy on Portfolio at Risk of Microfinance Institutions in Tanzania." Studies in Business and Economics 14, no. 3 (2019): 131–44. http://dx.doi.org/10.2478/sbe-2019-0049.

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AbstractThis paper presents the results of the study on the effect of credit collection policy on portfolio at risk of microfinance institutions in Tanzania. The study used cross-sectional survey data of microfinance institutions in three regions of Dar es salaam, Morogoro and Dodoma. Random sampling was employed to obtain a sample of 219 respondents in all three regions. Multiple linear regression analysis was used to determine the effect of credit collection policy on portfolio at risk of microfinance institutions. Results show that, there is a positive relationship between interest rates ch
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