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In this paper, we explore the impact of the COVID-19 pandemic on the credit risk of large European companies. We selected corporations belonged to the EuroStoxx 50 Index and whose CDS (Credit Default Swap) may be found in the iTraxx Europe Index. Then we applied the methodology of event studies to our database of companies, chosen as the event, the day of the declaration of pandemic by the WHO. The results indicate that the significance levels of the CAR (Cummulative Abnormal Default) show that the impact on the credit risk of the companies, as measured by the change in the spread of CDS, is important and depending on the sector in which the corporation is included. [ABSTRACT FROM AUTHOR]

We empirically analyze the LendingClub dataset, the pioneer of the peer-to-peer digital lending market. We aim to contextualize the business model through its database and the variables involved in the risk profile of the participants. We consider four different periods to capture economic cycles and their impact on the credit profile of borrowers. We implement K-Means Clustering Analysis to analytically define a segmentation pattern for participants based on the interest rate of the loans and the FICO (Fair Isaac Company) score. The clusters are constant throughout the periods studied and allow to detect average income levels, issued loans destination and borrower geographic origin according to risk profile. Few studies contemplate all the information available for the LendingClub operation (2007-2020Q3), therefore, this study illustrates how this business model has transitioned to maturity. This work achieves two objectives: to demonstrate the evolution of clients and the platform over time in terms of the risk profiles of participating borrowers, and to highlight the use of K-Means Clustering as an appropriate tool for profiling against to other analytical alternatives. [ABSTRACT FROM AUTHOR]

Credit score models quantify the risks in credit operations, customer segmentation, and approve or reject requests to credit customers. These models provide the necessary information to calculate the probabilities of default of any customer through the application of parametric or non-parametric techniques. This work identifies which model (Logit, Probit, Neural Networks, or Linear Support-Vector Machine (L-SVM)) may be more appropriate to measure the credit risk of individuals in a Family Benefit Fund located in Colombia. The results show Linear Support Vector Machine produces better performance, but Probit - Stepwise models are equally useful and they have the advantage of being interpreting the calibrated parameters. [ABSTRACT FROM AUTHOR]

The micro-business sector in the country, especially the increase in neighborhood stores due to the economic situation of the country and that this type of business has become a strategy for generating cash for people, in addition to the economic transformation that the municipality has undergone. of Circassia, Quindío in recent years, "Analysis of financial risks in stores in the urban sector of the municipality of Circassia during the period 2015-2020", which aims, through a survey of stores in the municipality, to identify and classify risks to which they are exposed to later qualify them in a risk matrix and finally determine an administrative tool that allows stores to mitigate the risks exposed. [ABSTRACT FROM AUTHOR]

The micro and small business in Peru has been in constant development for 40 years, since then the Municipal Savings and Credit Banks (CMAC) appeared, which have administrative, financial, and economic autonomy and participate in the decentralization of the financial services; However, the growth of the loan portfolio is accompanied by high delinquency indicators related to the credit risk of these institutions. The objective of this work is to analyze whether the over-indebtedness of clients, measured as the balance and number of financial entities that the debtor has, is a variable that has a positive and direct relationship to credit risk, leading to the establishment of higher provisions that negatively affect in the income statements of this group of institutions. This research has a quantitative and correlational approach, where the data collected from 48 months, (2016-2019), were processed using the statistical methodology CRISP-DM, where the direct relationship of the over-indebtedness with the credit risk of the CMAC. The relevance of this research is aimed at making strategic decisions that allow better control of the payment behavior of your credit operations and this is reflected in better economic results. [ABSTRACT FROM AUTHOR]

This article presents an exciting application of machine learning for loan origination in microfinance. Microfinance targets people who cannot build a credit history and therefore cannot access loans from banks or other financial institutions. We use data from a Mexican microfinance company that operates in several regions throughout the country. The objective is to guide intermediate lenders to choose their clients and achieve a lowerr credit default risk. We use several statistical models such as principal component analysis, clustering analysis and a regression tree. We obtain, as a result, a series of recommendations based on the characteristics of the clients. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to estimate the default probabilities in infrastructure projects. For that, we analyze the exposure of the lenders to a state of default. This application is made by assuming the debt service coverage ratio (DSCR) dynamic itself and the payment profile determined by the available cash flow of the project, where these are stochastically modeled following the same assumptions of the valuation theory of options developed by Black and Scholes (1973) and Merton (1973). In this way, through the adaptation of structural models developed for illiquid assets, as an extension of the credit risk models of Merton (1974) and KMV of Moody's, the probability, exposure and loss components of the lenders are analyzed in scenarios of default. [ABSTRACT FROM AUTHOR]

This article presents an analysis of the possible relationship between the spreads of sovereign bonds and the premia of credit default swaps (CDS) to determine whether they are useful tools for the measurement of the sovereign risk either separately or by taking into account the joint evolution of their values. The data refer to ten countries in the Eurozone along 2008-2016. By applying the causality Granger test for these variables, after six different ways of proxy, CDS premia are found to be the cause of the risk spreads in certain cases, although a bidirectional relationship is predominant in many other cases. So the CDS market contains clear and highly useful information on the sovereign risk. [ABSTRACT FROM AUTHOR]

The financial system is one of the main elements for the development of a country's economy, but an inappropriate liquidity management can make this system collapse, that is, they can disappear from the market, leaving many of its partners bankrupt. for the loss of your savings. Savings and credit cooperatives are small entities but they fulfill a similar function as large banks. The objective of this article is to analyze the Ecuadorian financial system, but within the context of savings and credit cooperatives that are small institutions that provide services to clients, for this study institutions from segment 4 and 5 will be used (data from about 150 cooperatives by segment). For the study, data collected and provided by the control body of the popular and solidarity financial system will be used. In conclusion, it seeks to demonstrate the impact suffered by the liquidity of cooperatives when it is affected by high delinquency in the loan portfolio. [ABSTRACT FROM AUTHOR]

In this paper, we establish a comparison between one of the most traded financial derivatives in the markets, the so-called catastrophe bonds (abbreviated as cat bonds) and the corporate bonds. In the first section, we start from a brief definition as well as some basic concepts. In section two, we will enumerate the type of investors to whom these products might interesting and how to price them. Afterwards, in section three we move onto the analysis of the trading rule proposed, that is, the comparison with Corporate bonds, our benchmark, in terms of expected returns. In sections four and five, we will point out some key issues on how the credit risk associated to these products can be reduced and, finally, in the last section, we will conclude with some discussions and remark the state-of-the-art research on this field. [ABSTRACT FROM AUTHOR]

The theory of support vector machines applied to the classification of credits granted by the United States fintech banking LendingClub is presented. The classification given by the svm method to credits will be analyzed against what has already been granted by the entity. The most important variables that LendingClub manages for the granting of credits are analyzed, comparing it with the classification of payment or non-payment that the svm experiment gives. [ABSTRACT FROM AUTHOR]

Facing an hypothetical, but increasingly, case of default risk on a mortgage or a fall in interest rates, an important issue raised by the borrower is the possibility of minimizing that risk by selecting the best refinancing option. In this paper, a mortgage refinancing model is presented, developing a purely quantitative programming method with a simulation based on an algorithm created especially for this case and that can be useful for mortgage debtors. Thus, we begin by explaining the theoretical basis on which the research is based, to proceed to develop the problem, continuing with its implementation. Finally, the results are analyzed and the most relevant conclusions are commented. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of the great financial crisis on the behavior of the Brazilian credit market through a panel of 101 Brazilian banks. For that, we measure the amount of cash involved in the credit activity in the different segments that compound the Brazilian financial system. The results show that: (i) the crisis did not change the relationship between the credit market and the credit risk, regarding the Brazilian financial system as a whole; (ii) both the state-owned and the private-owned segments of the financial system were significantly affected by the crisis, but in opposite directions. While the private segment extracted cash from the credit portfolio, reacting to the worsening in credit risk, the state-owned segment injected cash in the credit portfolio, acting counter-cyclically and compensating the private reaction. [ABSTRACT FROM AUTHOR]

The objective of this study is to analyze the influence of elements underlying accounting regulation in the disclosure of credit risk practiced by Credit Rights Investment Funds (FIDCs). The sample consists of 148 FIDCs whose explanatory notes from 2012 to 2014 were analyzed as to the level of compliance with disclosure standards through content analysis and statistical tests. The results indicate that the FIDCs partially meet the regulatory requirements for disclosure about credit risk, that there has been a relative improvement in the level of disclosure over time, that compliance with ICVM n° 489/11 is higher than CPC 40 (R1), and that quantitative normative criteria are the most publicized aspects. The constructs of the Asymmetric Information Theory allow us to understand that the asymmetry of credit risk information remains in securitization market and that the specificity of the regulations influences its occurrence. [ABSTRACT FROM AUTHOR]

The financial crisis of 2008 transformed, in some countries, to economic and social one, created serious problems to the banking system. Capital basis and asset exposures, especially through the non-performing loans, have been the most important. Capital inadequacy caused the failure of banks that didn't succeed to accomplish the capital requirements set by Basel II obligations. The treatment was not the same for all banks as only those considered as significant banks, for the economy, received capital aid from their state. The paper investigates through capital basis requirements and asset exposures the crisis' consequences on Cyprus and Greek cooperative banks. The consequences were cataclysmic for the cooperative banking systems of the two countries. In Greece, the cooperative banks did not receive any state aid, leading to the bankruptcy of many of them. In Cyprus, once all the cooperative banks were merged into the central cooperative bank, the latter received state aid as it was considered as a significant bank for the national economy. Moreover, the high level of non-performing loans and the new economic environment that the crisis had caused, forced the cooperative banks to change their asset exposures structure and their credit policy. [ABSTRACT FROM AUTHOR]

In this paper we characterize the bank mortgage borrowers in Chile and propose models to assess their credit risk. In particular, we study the mortgagors’ payment profile based on an empirical analysis that includes information of more than 150,000 new debtors during the period 2012-2014. Both the specify features of mortgage debt as initial loan amount and maturities, as well as debtor´s characteristics as credit history, illiquidity and coverage ratio are related to the probability of mortgage default. [ABSTRACT FROM AUTHOR]

The paper shows a mathematical description of the operational and logistic regression technique based on lectures by authors who have profoundly worked its empirical application. The concept of credit risk is defined in a statistical context. A description of economic activities considered in the study. Then, construction was synthesized in 19 SPSS logistic regression model: definition of group training and selection of variables related to business solvency. Finally, results are presented in tables, with the coding of variables, statistical goodness of fit and predictive power to determine the probability that an SME company insolvent fall and create a risk to creditors. It was found that companies reported accumulated losses are eight times more likely to fall insolvent companies with positive retained earnings. [ABSTRACT FROM AUTHOR]

The paper investigates the behavior of one of the most important credit risk assessment models, the KMV, based on Merton's (1974) theoretical formulation, in a sample of companies listed on the Ibovespa from 2001 to 2010. Besides the standard KMV performance, a variation of the KMV model, created by Bharath and Shumway (2008) - KMV naïve, was also evaluated for the same sample of companies. Through a sensitivity analysis, in which parameters of both methods were modified, the performance of the models was analyzed in different scenarios. A backtesting analysis was also performed, in which estimated default frequencies were compared with actual defaults of the companies. The results suggest that the naïve model, despite its simplicity, tends to overestimate the risks, indicating that in the case of Brazil, Merton's standard model is more appropriate. [ABSTRACT FROM AUTHOR]

In this paper, we study household debt default behavior in Chile using survey data. Previous research in this area suggests financial and personal variables help estimate individual and group probabilities of default. We study mortgage and consumer default separately, as the default decisions and overall borrower behavior are different for each type of debt. Our study finds that income and income-related variables are the only significant and robust variables that explain default for both types of debt. Demographic or personal variables are affected by only one type of debt but not more. For example, the level of education is a factor that affects mortgage default, whereas the determinants of consumer debt default include the age of the household head, and the number of people within the household that contribute to the total family income. We find that the probability of default decreases as the family income increases, and that our estimations are consistent with other studies similar to ours. [ABSTRACT FROM AUTHOR]

This paper proposes the inflow into non-performing loans (INPL) ratio, defined as the change in the stock of non-performing loans adjusted by write-offs and standardized by loans, as the main measure to be used for modelling the credit risk of the Chilean banking system. In particular, the paper identifies certain statistical and conceptual advantages of this measure with respect to loan loss provisions (LLP), which support this idea. First, the INPL ratio by type of credit has a greater time span than LLP. Second, the forward-looking nature of LLP --one of its main advantages over the INPL ratio-- is applicable only from 2004 onward due to various changes in Chilean reporting standards. Third, LLP is discretionary because provisioning is made on the basis of relative risk aversion of banks. Fourth, the INPL ratio produces smoother series than LLP for consumer and mortgage loans. In addition, the dynamic structure observed in both time series does not differ significantly. The econometric model estimated for the period January 1997 to June 2010 shows that the INPL ratio has statistically significant relations with macroeconomic aggregates such as the annual output growth, the short and long term interest rates, the annual inflation rate, the peso-dollar exchange rate, and non expected credit growth. Finally, the out-of-sample forecasts indicate differences between the actual and projected INPL ratios that are economically significant only in the case of mortgage credit. For the remaining portfolios, the evolution of this ratio during the period of July 2008 to June 2010 does not differ significantly from that predicted by the econometric model. [ABSTRACT FROM AUTHOR]

The growth of micro-credit along with the excellent conditions to carry out microfinance activity in the economy and financial system of the Republic of Peru are pushing for Microfinance Institutions (IMF) increased competition with banks in this segment business. Like in commercial banks, in microfinance questions such as: is this customer profitable?, What is the credit limit that I must accept to his/her application?, What interest rate should I charge to him/ her?, How I can reduce the risk default?, etc., are matters to be assessed properly. We propose a method that could facilitate improvement in customer qualification between failed and not failed. To this end, we propose a methodology that analyzes credit risk in the provision of microcredit through the design of a credit scoring model that we apply to a Development Agency for Small and Micro Enterprise (EDPYME), which is an IMF under the supervision by the Banking and Insurance Superintendency (SBS). [ABSTRACT FROM AUTHOR]

The growth of micro-credit along with the excellent conditions to carry out microfinance activity in the economy and financial system of the Republic of Peru are pushing for Microfinance Institutions (IMF) increased competition with banks in this segment business. Like in commercial banks, in microfinance questions such as: is this customer profitable?, What is the credit limit that I must accept to his/her application?, What interest rate should I charge to him/ her?, How I can reduce the risk default?, etc., are matters to be assessed properly. We propose a method that could facilitate improvement in customer qualification between failed and not failed. To this end, we propose a methodology that analyzes credit risk in the provision of microcredit through the design of a credit scoring model that we apply to a Development Agency for Small and Micro Enterprise (EDPYME), which is an IMF under the supervision by the Banking and Insurance Superintendency (SBS). [ABSTRACT FROM AUTHOR]

This paper poses a new methodology to estimate the required economic capital for a retail credit portfolio. The methodology is based on both the general copula concept and some core results from the extreme value theory (EVT). The main results support the fact that the proposed methodology is more flexible than other traditional techniques, in particular when it makes use of generalized elliptical and/or grouped t Student copulas to model the dependence structure of risk-parameters or when it includes elements of the EVT to analyze the extreme loss behavior of a retail credit portfolio. In applying algorithms, the paper includes data from a Mexican bank. [ABSTRACT FROM AUTHOR]

This paper analyzes the relation between debt maturity structure and default risk. We use data on over 47,189 non-financial Spanish firms during the period 1995-2006. The results show that firms rated as low risk have more long-term debt. However, maturity is a non-monotonic function of risk ratings, with low risk firms and high risk firms having short-term debt and intermediate risk firms having long-term debt. [ABSTRACT FROM AUTHOR]

This article presents a Credit Default Swap (CDS) assessment model for Colombian corporate bonds, based on reduced credit risk models and on the Monte Carlo simulation method where the underlying asset follows a stochastic Stopped Poisson process. This model is an interesting alternative for CDS assessment in countries where the corporate bond market shows low liquidity and the credit derivative market is incipient or does not exist, which is the case in Colombia. Applying this model leads to good results for CDS for investment-grade securities although it tends to overestimate the premiums on securities in the last level of degree of speculation. Furthermore, the conclusion is drawn that the sensitivity of the CDS premiums is high regarding the credit event occurrence rate and low regarding the recovery rate and the interest rate. Such results confirm those obtained from other empirical studies conducted in countries with a developed credit derivate market. [ABSTRACT FROM AUTHOR]