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This article extends previous research by Malhotra, Malhotra, and Malhotra (2024) exploring advanced machine learning models to predict the credit outlook for banking and nonbanking finance companies. The authors compare the predictive performance of five models, which include XGBoost, random forest classifier, gradient boost, AdaBoost using decision tree classifier, and AdaBoost using support vector classifier. The primary goal is to enhance predictive accuracy and detect potential distress signals early. Our findings reveal XGBoost as the standout performer, demonstrating superior accuracy across all credit outlooks while minimizing false positives. Gradient boosting also performs well, showing promise for accurate prediction. Cross-validation ensures model generalizability, with gradient boosting and SVM consistently performing well. The results emphasize the potential of machine learning models in accurately categorizing finance companies based on credit outlooks. Furthermore, the superiority of gradient boosting suggests its integration into operational frameworks for enhanced credit risk assessment, promoting stability within the financial industry. [ABSTRACT FROM AUTHOR]

Based on a comprehensive dataset of Chinese A-share stocks, we find significant evidence for analysts' anchoring in China. This anchoring behavior exists only when forecasts are lower than the industry median and correlates to a series of analysts' and corporate characteristics. The following market reactions to analyst anchoring are discontinuous: only forecasts without analysts' anchoring achieve higher and positive returns in the next period, while those with anchoring bias have no influence on the following returns. Further analyses based on the earnings response coefficient reveal that analysts' anchoring inhibits earnings information dissemination, and discontinuous stock performance is mainly from professional institutions. Overall, this paper provides evident results about analyst anchoring and its impact, and the findings are beneficial for investors to efficiently use analysts' forecast information. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sharia multifinance companies are one of Indonesia's Islamic non-bank financial industries that also utilize technological advances to facilitate people who want to apply for Islamic financing online. This study aims to analyse to analyze the determinants of awareness and intention of Indonesian muslim to become a customer of sharia multifinance companies. This study was quantitative by using questionnaire as the method of collecting data which distributed to a total of 418 respondents. The data analysed by using structural equation models with Smart PLS software. The results of this study found that religious commitment, awareness and reputation have a positive and significant impact on the intention to become a customer of sharia multifinance companies. The results of this study contribute to increase the understanding of sharia multifinance companies on the awareness and intention of Muslim in Indonesia to become their customer. [ABSTRACT FROM AUTHOR]

How do companies finance their investments? We examine the financing of investments according to firms' listing status, their size, and the nature of the investments. We show that private firms rely more on bank credit than public firms and less on financial debt, equity, and cash flow. We also show that the contribution of financial debt and equity increases with firm size. Considering both dimensions, we always find an increasing contribution of other financial debt and equity with firm size in both populations. Therefore, even in a bank-based economy, equity plays an important role in the investment of larger private firms. (JEL D25, E22, G21, G30, G31, G32) [ABSTRACT FROM AUTHOR]

Non-banking finance companies (NBFCs) have had a rather unpredictable presence, survival and growth in the Indian financial markets. It is rather well known by now that the risk-borne activities undertaken by a few NBFCs raised a few red flags and brought many stable heavyweight organizations in the finance sector to a screeching halt in their tracks. Due to the recent IL&FS and the DHFL crises, one might easily conclude to restrict, restrain and rein in the NBFC sector with increased regulations. Clamping down on the NBFC sector would not work, as they reach out to the nook and corner of the country, with many citizens seeking services from the NBFC sector, especially when they do not find a suitable solution to their credit needs from the formal banking sector. The authors find that some of the basic challenges for the NBFC sector have always been, and shall always remain, to find an ideal mix of capital from varied sources to fund the growing credit demand while being devoid of excessive risk from any one set of lenders. Towards the end of this paper, upcoming challenges for the NBFC sector domestically as well as globally along with its most suitable solutions from a practical implementation perspective have been suggested. [ABSTRACT FROM AUTHOR]

Web applications are utilized everywhere these days to share services and data online. Because companies deal with sensitive data, hackers have found them attractive targets. Vulnerabilities persist despite the numerous security procedures we've created to safeguard these applications. Major security issues have been identified in web applications used by various organizations, such as banks, healthcare providers, finance companies, and retail businesses. Cross-site scripting (XSS) attacks are one of the most significant issues, according to a report from White Hat Security. These attacks enable hackers to execute harmful programs on a user's web browser, resulting in issues such as the theft of data, cookies, passwords, and credit card numbers. This study focuses on the primary weaknesses present in contemporary web applications, particularly XSS attacks. We go over the many kinds of XSS attacks, provide instances from the real world, and describe how they operate. We also examine defenses against these attacks, discussing what works and what doesn't. [ABSTRACT FROM AUTHOR]

This research article scrutinises the connotation among bond prices and electricity prices (EP) across different threshold regions in India using threshold regression analysis. We resolve to investigate whether or not there exists a non-linear association between bond prices and EP and if this relationship differs across different threshold regions. The data covers a period of five years from 2018 to 2022, and the analysis includes three different threshold regions based on different threshold bond prices. The results show that there exists significant non-linear association between bond prices and EP, and this relationship differs across the three threshold regions. We surmise presence of an optimality between bond prices (interest rates) and EP, beyond which the EP increase. We conclude that as interest rates increase, the cost of financing for electricity companies also increases, which may lead to higher EP. However, there may be a certain threshold beyond which the cost of financing becomes too high, leading to a decrease in investment and ultimately a decrease in electricity supply, which in turn could lead to higher EP. [ABSTRACT FROM AUTHOR]

This article presents a comparative study on forecasting the credit outlook of banking and nonbanking finance companies using five distinct machine learning models: Logistics regression, k-nearest neighbor (kNN), decision tree classifier, support vector machines (SVM), and naïve Bayes classifier. The research evaluates the efficacy of these models in categorizing financial companies based on their credit outlook (negative, neutral, and positive). Our findings reveal that the kNN model with a k value of 7 demonstrated superior performance in terms of test accuracy compared to the other models. Although models such as the kernelized SVM and logistic regression exhibited commendable performance, none could match the high-test accuracy achieved by the kNN model. [ABSTRACT FROM AUTHOR]

The Green Financial Reform and Innovation (GFRI) policy not only serves as a crucial tool for facilitating a comprehensive transition towards sustainable practices in economic and social development but also has a significant influence on the operational activities of companies. However, there is limited research on whether the GFRI policy can affect companies' overcapacity. To address this gap, we use data from the China Stock Market & Accounting Research Database and the Chinese Research Data Services Platform to evaluate the impact of green finance on companies' overcapacity. The results show that the GFRI policy can effectively alleviate companies' overcapacity. Moreover, the GFRI policy can alleviate companies' overcapacity by strengthening market competition, enhancing financing constraints, and promoting innovation. Further, the GFRI policy exerts a more pronounced effect on alleviating overcapacity in non-labor-intensive companies, companies in heavily polluting industries, and companies in regions with weak environmental supervision. This paper not only supplements the relevant literature on alleviating overcapacity but also provides more theoretical support for promoting a national green financial system in practice. [ABSTRACT FROM AUTHOR]

This study examines the announcement effect of a green bond on the issuer's stock returns in the Indian Stock Market. The event study methodology for data analysis and abnormal returns were calculated using the market model for the 16-day event window that includes the 5 days prior and 10 days after the issuance of the green bonds. The findings of this study show that green bond announcements do not create any significant abnormal returns, thus suggesting investors' irrationality toward environmental factors. This study informs policymakers that investor education relating to the environment is needed in India. [ABSTRACT FROM AUTHOR]

Copyright of FinanzRundschau is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Die Unternehmensbesteuerung (Ubg) is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research explores the impact of financial indicators on the credit ratings of companies listed on the S&P 500, employing a Sys-GMM model to address endogeneity concerns. Three independent variables categorized as market and survival factors alongside seven control variables sourced from leverage, liquidity, interest coverage, profitability, market, survival, and macroeconomic domains were investigated. The sample consisted of 2398 observations from Capital IQ Pro, spanning nine years (2013 to 2021) and encompassing 240 public companies. The findings suggest that neither Tobin's Q (TQ) nor Total Shareholder Return (TSR) lack significant correlations with credit ratings, implying that stock market performance and total shareholder return do not directly impact credit ratings. In contrast, the Altman Z-score (AZS) emerged as a significant predictor, indicating its importance in assessing credit risk. These insights enhance the understanding of financial indicators' impacts on credit ratings, aiding financial institutions and companies in prudent lending and financing decisions. [ABSTRACT FROM AUTHOR]

In an era where crowdfunding in Portugal is garnering increased public attention, exemplified by notable campaigns like the recent funding of the nurses' strike, we explore its potential as an alternative financial source to traditional banking. Through a comprehensive case study, we delve into pertinent issues, encompassing European legislation, market dynamics, and a survey disseminated to representatives of the four prominent Portuguese crowdfunding platforms. Comprising forty-one questions across four categories, the survey extracts insights on platform details, company/project information, investor perspectives, and the financing process, along with an evaluation of platform advantages/disadvantages vis-à-vis traditional banking. Despite heightened visibility, crowdfunding remains relatively unfamiliar to the broader public, yet it diverges from banking not as a substitute but as a complementary financial mechanism. Emphasizing accessibility, process agility, and reduced bureaucracy, crowdfunding serves as a means of swiftly gaining recognition for a company or project while tapping into a broad audience. Rather than competition, it offers supplementary support, facilitating the identification and validation of investment opportunities and concepts. Moreover, it streamlines subsequent interactions with banks and investors, enhancing confidence in a project's viability. In essence, crowdfunding emerges not as an alternative but a strategic complement, enriching the financial landscape with its unique attributes. [ABSTRACT FROM AUTHOR]

The present paper investigates the relationship between stock prices, credit ratings, and ESG scores for banks internationally. First, it describes stock prices and ESG scores at an annual frequency, as well as stock price and credit risk at a daily frequency. The relationships between (a) stock price and credit rating returns with ESG score returns and (b) among ESG scores are examined by pairwise annual correlation, and daily correlations are examined between price and credit rating returns. Furthermore, Granger causality is used to examine the relationships between the following: (a) price and ESG score annual returns; (b) price and credit rating daily returns; and (c) total and pillar annual ESG scores. This study makes a significant contribution to the literature by providing a detailed temporal analysis using both annual and daily data frequencies, which is relatively rare in the field. There is evidence of statistically and empirically important relations in the form of pairwise correlations. The regressions reveal a low significance of few ESG score changes in explaining credit rating changes. A unique aspect of this paper is the comprehensive analysis of 16 granular ESG scores, including overall scores, pillar scores, and sub-scores, allowing for a multi-faceted understanding of how specific ESG factors impact financial metrics. We found evidence of the significance of COVID-19 in all research questions. Additionally, this paper highlights the impact of the COVID-19 pandemic on the relationships between ESG scores, credit ratings, and stock prices, offering timely insights into the heightened importance and volatility of ESG factors during crisis periods. Future research needs to shed more light on this relationship, however. [ABSTRACT FROM AUTHOR]

Most entrepreneurs seek VC funding after the reward-based crowdfunding campaign succeeds, and venture capitalists (VCs) can contribute to the project in two aspects: investment and operational expertise. With a game-theoretical model, we find that entrepreneurs face twelve possible scenarios contingent on the mass market revenue and revenue share, including the six scenarios wherein neither side exerts effort to complete the project. To attract VC funding and ensure the project completion after a campaign success, entrepreneurs should set the funding goal above a certain threshold. Specifically, we identify three ranges of the revenue share and derive the lower bound for the funding goal in each range. However, we notice that entrepreneurs prefer a low funding goal to promise the campaign success and the optimal goal will be the lower bound in each range. Moreover, we show that the revenue share is decisive to the role of VCs in the project. If the entrepreneur's share exceeds a high threshold, the venture capitalist becomes a pure investor with no incentive to exert effort, similar to the role of banks; if the share is less than a low threshold, the entrepreneur won't follow up but transfers the project, and the VC investor will be a project owner; if the share stays medium, the VC investor acts as a partner and there may exist "free-riding". In the extension, we consider the revenue share an endogenous and analyse the role of VCs further. Interestingly, the VC investor prefers to own the project and occupy all revenue in mass market, while the entrepreneur treats the inefficient venture capitalist as a pure investor and the efficient one as a partner. In addition, when cooperating with efficient VCs, the entrepreneur is more likely to enlarge her share as the mass market revenue increases. [ABSTRACT FROM AUTHOR]

In this paper, we developed an approach for the empirical testing of the relationship between the financing choices of companies and the abnormal returns obtained by their shareholders. We innovate by incorporating controls on how this relationship is affected by the capabilities of each funding source, at different levels of returns, through quantile regression. The estimation of the model for a sample of Brazilian companies indicates the inexistence of a significant relationship between abnormal returns and debt issuance. The same occurs between abnormal returns and equity issuance, with one exception: when there is a deficit of internal financing that extrapolates the available safe debt and the abnormal returns are, at least, median, this relationship becomes significant and positive. Considered as a whole, the results suggest an indifference to the sources of funds used by the company. Among the contributions, we highlight the incorporation of the aforementioned controls, which bridges the gap identified in the literature relating business financial flows and stock returns. [ABSTRACT FROM AUTHOR]

An ongoing question in capability research is how to incorporate the value of freedom into the measurement of inequality. This article proposes an approach to answering this question in the housing domain and its operationalisation. The approach places an evaluation focus to the conditions constraining or expanding housing choices in the dimensions of opportunity, security, and ability. For operationalisation, the study designed a measurement of multidimensional housing disadvantages (MHDs) using the Alkire-Foster method and data from the Netherlands. Indicators include the entitlement to housing tenure options, vulnerability in housing cost payments, and ability to plan finance for housing. The measurement outcome demonstrates that the MHDs measurement can provide information on whose housing choices are more intensely constrained, thus having a lower capability for housing, and whose current housing situation is likely a result of coerced choices. The findings indicate that adults living with housemates or family (latent households), youths, and those with precarious jobs have a significantly lower capability for housing compared to other population groups. This article also compares the freedom-oriented measure of MHDs with functioning-oriented and other conventional measures and discusses its distinguishing properties. This comparison suggests a need to revisit current policy priorities in addressing housing inequality. [ABSTRACT FROM AUTHOR]

This study aims to determine the effect of Shareholders' Rights and the Board of Directors as well as the Audit Committee and Disclosure to Investors on Return On Equity in Financing Companies listed on the Indonesia Stock Exchange (Period 2018-2022). Through this quantitative approach, the research method used is descriptive analysis and hypothesis testing with a total population of 20 non-bank financing companies and a sample of 4 non-bank financing companies listed during the 2018-2022 period. The results show that Shareholders' Rights and the Audit Committee have a significant effect on ROE. In contrast, the Board of Directors and Disclosure to Investors show no effect on ROE. [ABSTRACT FROM AUTHOR]

Debt is a financial instrument used by companies to finance their growth, make investments and maintain efficient operations. The market share index (MPI) is an indicator of a company's competitive position in its respective market. This application studies the relationship between indebtedness and MPI in a data set of companies in the manufacturing environment belonging to zone 3 of Ecuador. For the resolution of this study, two phases are used, the first one resides in a Spearman correlation analysis, the second one establishes a relational case by means of an automated boosting regression. The results show that a positive relationship coexists between short-term indebtedness and asset indebtedness, and MPI. This suggests that firms with significant levels of short-term indebtedness and asset indebtedness tend to have higher MPI. [ABSTRACT FROM AUTHOR]

In recent years, China's automobile industry has undergone rapid development, creating new opportunities for the auto loan industry. Currently, auto financing companies are actively seeking to expand their cooperation with banks. Therefore, improving the approval rate and scale of joint loan business is of significant practical importance. In this paper, we propose a Stacking‐based financial institution risk approval model and select the optimal stacking model by comparing its performance with other models. Additionally, we construct a bank approval model using deep learning techniques on a biased data set, with feature extraction performed using convolution neural networks (CNN) and feature‐based counterfactual augmentation used for balanced sampling. Finally, we optimize the model of the prediction of auto finance companies by selecting the optimal coefficients of loss function based on the features and results of the bank approval model. The proposed approach leads to an approximately 6% increase in the joint loan approval rate on the actual data set, as demonstrated by experimental results. [ABSTRACT FROM AUTHOR]

Copyright of Zeitschrift für Bankrecht und Bankwirtschaft is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The relevance of the study is that the pandemic has affected the financial stability of many businesses. The purpose of the study is to consider the features of bank lending to businesses in a pandemic. Providing credit in the era of the coronavirus is associated with increased risk. However, this does not mean that it is impossible to obtain new funding. Banks still offer a variety of credit products, including mortgages and cash or credit card loans. Changes in the level of debt mask the distinction between new borrowings and repayments of existing amounts. Business loans are mostly short-term, and their rates can be adjusted relatively easily. Historical data shows that on average, 90% of new business loans have a variable or fixed rate with a maturity of less than one year. The huge surge in loans to new businesses is primarily conditioned upon this short-term financing. The speed and scale of the return of the gap to the pandemic is unprecedented. The practical significance lies in the analysis of problems and obstacles to bank lending to businesses in a pandemic, and ways to solve them. [ABSTRACT FROM AUTHOR]

Many researchers have investigated the consumer's attitude towards using credit cards. However, how the different attributes contribute to credit card usage attitude is not evident. Thus, the main theoretical contribution of this study is to examine the importance and performance of a set of variables that explain the attitude towards using credit cards. It provides essential inputs to banking institutions towards the relationship between bank image, credit knowledge, transaction behaviour, transaction control behaviour, and credit card usage attitude using cognitive–motivational–relational (CMR) theory. We used an adapted questionnaire to survey 383 Indian consumers from the National Capital Region (NCR). We applied variance-based partial least square structural equational modelling (PLS-SEM) on SmartPLS software to identify the importance and performance of each variable using importance performance map analysis (IMPA). Some significant findings include that credit knowledge and transaction behaviour are essential constructs determining credit card usage attitude. Moreover, the study also found that if banks enhance the credit knowledge of their consumers, they could build positive attitudes among consumers, based upon which their service marketing strategies could be shaped accordingly. [ABSTRACT FROM AUTHOR]

Narcissistic managers with characteristics such as desire for fame and power seeking to protect their interests have the necessary motivation to be effective on the relationship between discretionary accruals and credit rating and, as a result, change the credit rating of companies to their desired rating. The purpose of the present study is to investigate the relationship between discretionary accruals and credit rating by considering the moderating effect of managers' narcissism. The statistical sample of the current research includes 113 companies listed on the Tehran Stock Exchange and 17 companies listed on the Iranian Foreign Exchange in the period of 2011-2021. The data of this research was collected by referring to the Kodal website, the website of the Iranian Statistics Center and Rahvard Novin software. Hypotheses were tested through multivariate regression models and generalized least squares approach using EViews 12 software. The results of the statistical test of research hypotheses confirm that discretionary accruals have a positive and significant effect on the credit rating of economic units. That is, with the increase of discretionary accrual items, the credit rating of economic units increases. Also, the findings of the research indicate that there is a moderating effect of managers' narcissism with three indicators of the size of managers' signatures, managers' cash bonus and managers' photo in the relationship between discretionary accruals and the credit rating of economic units. In other words, managers' narcissism based on the indicators of the size of managers' signatures, managers' cash bonus and managers' photos strengthens the positive relationship between discretionary accruals and credit rating. Based on these results, credit rating agencies are suggested to pay more attention to the narcissistic factors of managers and discretionary accruals in the credit rating process of economic units. [ABSTRACT FROM AUTHOR]

Islamic Easy House Financing (IEHF) increased from RS. 6.8 billion to RS 23.3 billion over 10 years. Identifying the factors that affect the satisfaction of both Muslim and non-Muslim clients with Islamic Easy House Financing (IEHF) is significant. This research then considers the major variables that impact Pakistan's choice of Islamic Easy House Finance (IEHF). Questionnaires were distributed to 160 employees of Meezan Islamic Bank. The current study employed a testing strategy called random sampling. The questionnaire was divided into two segments. One segment included data about the segments, while the other segment focused on the factors that influence how Muslims finance their Islamic Easy House (IEHF). The results demonstrate that several significant variables impact the choice of Islamic Easy House Financing (IEHF), including circumstances, management quality, integrity, prominence in the media, and social impact. The most reliable indication is reputation, as most customers feel comfortable choosing Islamic Easy House Finance (IEHF) because Islamic Meezan Bank has a strong reputation and vision. The study needs to be completely structured. The focus also refers to representatives of a single financial institution. Future research may involve personnel from various Islamic financial institutions. Policymakers and directors could use the tests suggested in the current study as a guide for enhancing Islamic Meezan Bank products and services. There will be an article published on Pakistan's Meezan Islamic Bank as part of the study. This research is the first to examine Pakistan's easy-house-choice Shari'ah laws. For experts and scholars concerned about advancements in Pakistan's Meezan Islamic Bank's banking sector, the findings made throughout this research process will be of the utmost importance. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this paper is to study the impact of political connection and governance on credit rating and whether there is a substitution or complementary relationship between them. Design/methodology/approach: In order to achieve the objective, a succession of eight ordered probit regressions has been carried out. Moderating variables between the political connection and governance characteristics were introduced. The whole population is taken as a sample, i.e., 27 Tunisian companies that are evaluated by FITSH NORTH AFRICA agencies over a period of 10 years (2009–2018). Findings: The outcomes are mixed. They show that the political connection does not always influence credit rating; the size and board independence always improves credit rating; the duality between the functions affects credit rating; whereas the majorities' proportion does not influence credit rating; and a substitution between the political connection and the governance characteristics is validated. Research limitations/implications: Like any other research, our results are factors of our measures and variable choice and depends heavily on the how these variables were conceived. Also, although our number of observations responds to the statistical result generalization requirements, our sample remains relatively narrow with 27 companies only. Practical implications: In practice, the research will allow investors to have a better vision upon the future of their investments based on whether to develop their governance system or promote political networking. It will also prompt lenders to look beyond ratings and consider factors such as political connections to make a rational judgment on their future placements. Social implications: This study leads us to find various solutions: the establishment of credit agencies that take into consideration all the data of all the operators taken as a whole (bank, leasing company, and factoring). It encourages the reorganization of the Tunisian banking sector through mergers for example. Originality/value: This study is a pioneer in the credit rating field in Tunisia, where the source of debt financing is the most used by all enterprises across all sectors. This study extends the literature of political connection effectiveness, independent directors, board size, in improving corporate performance and credit rating. [ABSTRACT FROM AUTHOR]

The article discusses developments in automotive finance in the U.S. Topics include the settlement made by the Federal Trade Commission (FTC) on junk fees and discriminatory practices of Passport Automotive Group, Inc., actions taken by the Massachusetts attorney general against an automobile group operating two dealerships in Massachusetts and against a nationwide automobile captive finance company, and state regulation of ancillary products.

Based on data from A-share listed companies in China from 1990 to 2018, this research explores the impact of international sanctions on enterprise technological innovation and their mechanism. Findings demonstrate that international sanctions have a significant inhibitory impact on enterprise technological innovation and are still valid after several robustness tests and endogeneity treatments. Analysis of heterogeneous enterprises presents that the inhibitory effect is mitigated in state-owned enterprises (SOEs) and monopoly industry enterprises, but intensifies in high-tech enterprises. Further mechanism analysis notes that the inhibitory effect is partly transmitted by weakening the internal and external financing capacities of companies. [ABSTRACT FROM AUTHOR]

This paper empirically evaluates the impact of ownership structure on the cost of credit in US banks. It does so by comparing their grouped option-adjusted credit spreads on the outstanding debt issues. As the overall risk of the creditors is reflected in the yield spread of the firms' outstanding bonds, separately classifying bank-holding companies and stand-alone banks and controlling risk ratings, maturities, and issue sizes enables us to compare the yield spreads tied to ownership structure. After computing the option-adjusted yield spreads of outstanding operating and holding company bonds, we used these values in a master regression equation to test the statistical and economic significance of the binary variable separating the option-adjusted spreads of the two sets. Our work finds that when the S&P ranks and maturities are controlled, US bank-holding companies finances with higher cost of credit compared with stand-alone banks, although holding companies add a layer of liability protection due to the legal separation between the assets and the owners. This suggests that certain characteristics of US bank-holding companies, such as higher leverage and higher systematic risk levels, make them riskier compared with traditional stand-alone banks, offsetting the benefits of forming a holding company. [ABSTRACT FROM AUTHOR]

This paper measures the output costs of sovereign risk by combining a sovereign debt model with firm- and bank-level data. An increase in sovereign risk lowers the price of government debt and has an adverse impact on banks' balance sheets, disrupting their ability to finance firms. The resulting fall in credit supply impacts firms directly, as they need to borrow at higher interest rates, and indirectly through general equilibrium effects on the price of inputs and other goods. Importantly, firms are not equally affected by these developments: those that have greater financing needs and that borrow from banks that hold more government debt are mostly affected by the change in borrowing rates, while firms that do not borrow are only impacted indirectly. We show that these direct and indirect effects can be recovered using a firm-level regression, which we estimate using Italian data. We calibrate our model to match the measured firm-level elasticities and find that heightened sovereign risk was responsible for one-third of the observed output decline during the Italian debt crisis. [ABSTRACT FROM AUTHOR]

Money supply adapts to the demand of credit and has a crucial impact in determining production levels. However, at the same time, under certain conditions the issuance of money may also boost inflation. In this article, with the help of Shaikh's 'classical theory', we explain the main reasons for the recent hyperinflation experienced in Venezuela. On the supply side, we analyze the context of loss of competitiveness due to the overvaluation of the national currency. On the other hand, we explore how the credit to the oil company (PDVSA) has led to an exponential growth in aggregate demand. [ABSTRACT FROM AUTHOR]

More victims of identity theft report to private institutions, such as credit card companies and banks, than to law enforcement. Internationally, fraud victims have experienced difficulty receiving assistance from institutions, yet little research has examined the outcomes of identity theft and fraud victims in North America. This article presents findings about Canadian victims' experiences reporting identity theft, drawn from 20 interviews with victims of identity theft in Ontario. Although some victims had positive experiences with institutions and were assisted promptly, many were let down: Some had to hound for help or were transferred repeatedly, while others felt no closure or that the process of reporting was unclear. Moreover, victims' experiences varied even when characteristics of the identity theft incidents appeared similar, such as the type of fraud experienced and the number of accounts misused. This article closes by discussing the implications of these findings in the context of victim assistance. [ABSTRACT FROM AUTHOR]

To analyze whether the occurrence of elections affects access to credit for firms, we perform an investigation using firm‐level data covering 44 developed and developing countries. The results show that elections impair access to credit. Specifically, firms have lower access to credit in election years and pre‐election years as elections exacerbate political uncertainty. While higher borrower discouragement is a tangible negative effect of elections, their occurrence per se does not seem to affect loan acceptance by banks. We also document that the negative relationship between elections and credit access is shaped by country and election characteristics as well as firm characteristics. [ABSTRACT FROM AUTHOR]

This paper examines the impact of trust on informal financial development. We isolate the inherited component of trust for 19 countries using US census data and relate it to firms' access to trade credit. We discover that trust disproportionately elevates the use of trade credit by companies that face obstacles to obtaining funds from formal channels. Further analyses show that the effect is more pronounced in finance‐dependent industries and that better access to trade credit promotes sales growth. Our results are robust to alternative samples, different estimations of inherited trust and various model specifications. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this article is to review the literature on cultural aspects of trade credit use. Specifically, it examines the issue of trade credit use in the context of trust, religion, and national culture. Design/methodology/approach: A literature review was conducted to identify the key cultural issues addressed in previous studies on trade credit and to summarize the research on the use of trade credit in three focus areas: trust, religion, and national culture. Findings: A literature review confirms that cultural factors, such as trust, religion, and national culture, play crucial roles in the provision and receipt of trade credit. Therefore, future research on trade credit should adopt a more comprehensive approach that extends beyond a purely financial perspective. Practical implications: Given the significance of trade credit in business operations, a thorough understanding of its cultural underpinnings can prove vital for the parties involved in a trade credit agreement. Originality/value: Despite the crucial importance of trade credit for companies and the extensive research devoted to it, the cultural dimension of its use remains an underexplored field. This article addresses this issue by providing an overview of the current state of research on trade credit concerning three cultural aspects: trust, religion, and national culture. Furthermore, the article outlines several potential directions for future research in the subject of the study. The article's subject matter falls within the expanding domain of culture and finance. [ABSTRACT FROM AUTHOR]

Banking sector is one such field where the company needs more accurate results after analysis. There are many people applying for bank loans from banks or other finance companies each day. But the banks cannot provide loan to every individual who is applying for loan. There is a very complex task that the bank employees do to study an analyze if the applicant is genuine or not. To find this out, there are a lot of factors to be considered. Going through this huge amount of data can be a really difficult task and yet one cannot be sure if the applicant will be able to pay back the loan within the given time or not. Objective of the paper is to make thorough analysis of the test data and make predictions if the applicant is genuine or not. For this process, we are using Machine Learning where the trained data is used to make predictions. [ABSTRACT FROM AUTHOR]

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]

The paper examines the task of managing the finances of a company with branches when funds are saved on the central company account, from which payments for the expenses of the branches are made. The dynamics of these expenses may have similar dynamics, which makes it possible to build a single model for the entire group. This article is devoted to the construction of theoretical concepts of the nonlinear dynamics approach and the formalization of criteria for combining time series into a single model. We introduce the concept of series with the same type of symmetrical seasonality, based on phase portraits, which allows formalizing the similarity criterion based on symmetry transformations. Considering time series that are recognized as similar, we bypass nonstationarity by considering the series included in the group as realizations of a random process. Finally, the use of new concepts allows solving an important practical problem, reducing the analysis to grouping by seasonal similarity and statistical characteristics of deviations when symmetry transformations are violated. [ABSTRACT FROM AUTHOR]

Today, supply chain finance is a very important topic. Traditional supply chains rely on banks to support the related financing activities and services. With the emergence of blockchain technology, more and more companies in different industries have considered using it to support supply chain finance. In this paper, we study supply chain financing problems in supply chains selling fashionable products. Modeling under the standard newsvendor problem setting with a single manufacturer and a single retailer employing a revenue sharing contract, we develop analytical models for both the traditional and blockchain-supported supply chains. We derive the optimal contracting and quantity decisions in each supply chain with Nash bargaining between the manufacturer and retailer. We analytically show how the revenue sharing contract can coordinate both types of supply chains. We then compare the optimal systems performances between the two supply chains. We prove that the blockchain-supported supply chain incurs a lower level of operational risk than the traditional supply chain. We have shown that if the service fees by banks are sufficiently high, adopting blockchain technology is a mean-risk dominating policy which brings a higher expected profit and a lower risk for the supply chain and its members. For robustness checking, we examine other commonly seen supply chain contracts and alternative risk measures, and analytically reveal that the results remain valid. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to analyze the phenomenon of digitization in financial-banking institutions, and how entrepreneurs active in various fields of activity have turned to digitization to continue their activities despite the restrictions imposed by the Covid-19 pandemic. We can say that digitisation is the future, because it doesn't just help us in times of pandemic or other crisis situations, digitisation is the future of the banking industry, because consumers want to work with banks that can offer remote and quality services, and all categories of customers want to work with those companies that find innovative solutions and can provide them with services through technology. Bankers and entrepreneurs need to find a balance between legislation and market regulation, between risk management and consumers. We can say that the future belongs to digitised, standardised banks that understand and comply with legislation and regulation and that place a high value on innovation. We can talk about the era of digitisation as having been accelerated by the pandemic, which is why a lot of measures have been taken to make information as easy as possible, with all banks, as well as other companies and financial-banking institutions, strengthening their websites and solutions for remote access to their banking offer or banking products, such as applications (banking). A good number of banks already offer the possibility to get basic products directly from websites or apps: current account opening, debit cards, credit or shopping cards, personal loans and even deposits. A secure and risk-free digital solution is certME. With the certME solution, customers no longer need to be physically present at the counters and interact with their own staff for the identification processes specific to digital onboarding and Know Your Customer procedures, enjoying many advantages. [ABSTRACT FROM AUTHOR]

The purpose of this study is to find out 5c credit analysis of bad debt of finance companies on the momentum of the holiday holiday. This study used descriptive analysis techniques designed and carried out by collecting data describing each variable before and after Hari Raya. The test results show that Character has a negative and significant effect on Astra Credit Companies (ACC) Non-Performing Financing (NPF). This can be proven by a calculated t of 4.999 greater than the table t (1.86) and a Sig value of 0.000 smaller than 0.05. Thus, it can be concluded that Hypothesis 1 (H1) is accepted that there is a negative and significant influence between the Character variable and the Non Performing Financing (NPF) of Astra Credit Companies (ACC). Conclusion based on the results of the study and the results of the analysis that has been carried out in previous studies, it can be concluded that the research data meets the criteria of data normality and is free from deviations from classical assumptions such as, Multicollinearity and Heteroscedasticity. So it has a high determination to be used as a prediction or forecasting. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate if mission statement comprehensiveness related to mean ROA and ROA growth. Websites from the 108 finance companies listed on the S&P SmallCap 600 were analyzed to determine if they had explicit mission statements, and if so, which of David and David's (2019) nine components were present: customer, products/services, markets, technology, survival, growth, and profitability, philosophy, self-concept, and concern for public image and employees. Few studies have investigated the relationship between mission statement components and economic performance within an industry. Finance company mean ROAs and ROA growth from 2018-2021 were examined based on if each component was present. The results are as follows: firms posting explicit mission statements on their websites had higher ROA means, firms including concern for public image had higher ROA growth, and firms including concern for employees had higher ROA means. However, mission statement comprehensiveness did not relate to firm performance. [ABSTRACT FROM AUTHOR]

Companies have increasingly used supply chain financing instead of bank financing when engaging with financially constrained suppliers. We investigate the effectiveness of different financing mechanisms at supporting supply chain responsibility. We consider a decentralized supply chain where a buyer sources from a financially constrained supplier who borrows from either a bank or the buyer to finance his production. The buyer audits the supplier for responsibility compliance and will refuse to accept and pay for the order if the supplier fails the audit. We find that under conventional bank financing, the bank is concerned with the supplier's audit failure and will raise the interest rate. This not only hinders the supplier's compliance effort but also hurts the profitability of every stakeholder. In contrast, under buyer financing, the buyer may offer the supplier a low interest rate to motivate him to be more compliant when the supplier's collateral is of low value. However, if the supplier's collateral is of high value, the buyer may be tempted to set a high interest rate to exploit the supplier—leading to a reduction in supplier's compliance and supply chain profitability. Thus, we conclude that buyer (bank) financing is more preferable for encouraging responsibility when the supplier has low (high) collateral. Our findings suggest that buyer financing may not always be an effective approach for encouraging supply chain responsibility. As such, we propose an alternative mechanism under which the buyer offers a reward to the supplier if he passes the audit while the supplier continues to borrow from a bank. We prove that this combination of bank financing and buyer reward always improves the compliance level and in most cases increases the total supply chain profit. It is even more effective than buyer financing in encouraging responsibility especially when the supplier's collateral is of low value. [ABSTRACT FROM AUTHOR]