Company Credit Research Articles

Moderating role of voluntary IFRS adoption on earnings management and credit score of private companies

Earnings management practices may be implemented to unduly improve the company's credit score, and in voluntary settings, a company's choice of adopting IFRS can influence the company's credit profile. We conduct an empirical analysis on a representative sample (n = 10,389) of Italian private companies and find that earning management practices improve, whereas a voluntary IFRS adoption worsen a company's creditworthiness profile. We also find that IFRS adoption cancels out the former undue credit profile benefits, further penalising the credit score. Future studies should replicate these analyses for other contexts and using alternative financial measures to improve the generalisability of these findings.

The Dilemmatic of the Absence of a Notary’s Deed in an Individual Company after the Enactment of the Job Creation Law as a Form of Legal Certainty

The existence of an Individual Company, which aims to ease abbreviate by reducing or simplifying the rules, raises a dilemma in its regulation which shifts the meaning of a company as a legal entity. The method used is normative legal research, with the legal approach used is conceptual and statutory approach. The existence of an Individual Company as a legal entity that can be recognized as a legal subject is only passed with a Statement of Establishment of an Individual Company and registered to the Ministry of Law and Human Rights based on the Job Creation Law. The convenience found was only based on an economic point of view. Practically speaking, there are more hazards in the society. As an example, the Individual Company credit facility, which is hesitant to be granted by the bank as the creditor because it is still categorized as individual credit. Although it has the status of a legal entity, its establishment by one person and without a Notary may not ensure certainty for all parties in the Individual Company.

Comprehensive Creditworthiness Assessment of Rio Tinto

This report examines Rio Tinto’s creditworthiness in relation to their request for an AU$1 million, three-year loan from the bank. In my capacity as the lending officer assigned to review this loan application, I will use four credit analysis techniques to determine the risks involved in giving the company credit and anticipate how to respond if business operations deteriorate or are unable to repay. A summary of the company’s financial situation, an analysis of its ability to repay debt, an appraisal of its business practices and industry prospects, and any relevant qualitative aspects influencing creditworthiness will all be included in the report. Informed choices about the loan application will be made through a thorough examination to minimize potential risks and guarantee the bank’s interests are protected.

Assessment of the Success of Digital Signature and Stamp Implementation in the National Economic Rescue (PEN) Application System at Credit Insurance Companies in Indonesia

Utilization technology in sector industry non-bank finance in Indonesia is increasingly widespread, including in the guarantee credit of state-owned companies. The company uses System Application Guarantee for transaction guarantee credit with produce Certificate Guarantee as proof of approval. The request can be active in the context of the COVID-19 pandemic and the Indonesian government's efforts to implement the company's National Economic Recovery (PEN) program guarantee. Implementation feature sign hand and digital stamp on the System Application PEN underwriting allows provision of document Guarantee Certificate in the form of legal and supportive softcopy restrictions contact physique during a pandemic. Study This aim is to measure the successful implementation features of the success models by Delone and McLean and analyze the connection between variables in research. The benefits cover assessment, evaluation, and strategy-based results evaluation using feature sign hand and digital stamp. Delone and McLean's original model was modified to eliminate variable intention to use. The research was conducted by analyzing the results of questionnaires from 108 officials' user systems throughout Indonesia. Process of data analysis using the method of Partial Least Square with device SMARTPLS software. Research results prove that quality systems will influence the satisfaction of future users who will be influential to benefit clean from the feature sign hand and digital stamp on the System Application PEN Guarante.

Financing Dilemma and Optimization Strategies of High-Tech Enterprises

In recent years, Chinas economic market has been developing rapidly and the number of enterprises has been increasing. However, the development of enterprises needs to rely on the support of capital, due to the high financing threshold of the capital market, ordinary commercial banks and private financial institutions can not fully meet the capital needs of all enterprises in the market. This has, to a certain extent, exacerbated the phenomenon of capital bottlenecks and stagnant development faced by Chinese enterprises, and many even went bankrupt due to poor capital turnover. This paper combines the views and conclusions put forward by a number of professional articles to analyze the status quo and predicament of the company's financing. It is found that high-tech enterprises have problems such as less application of financing methods, high financing costs and unreasonable financing structures. By optimizing the financing structure, improving the company's credit level to expand financing methods, and reducing financing costs, the government has introduced helping policies and other optimization strategies that can promote the healthy and stable development of high-tech enterprises.

Credit Scoring Modelling For Corporate Banking Institutions

This research aims to build a credit scoring modeling simulation of bank corporate loans. The credit scoring model is used in assessing creditworthiness in credit decisions. This model determines whether or not a company is eligible for the corporate credit facility it proposes. Observations were made of 100 companies included in the list of Kompas100 Index formers on the Indonesia Stock Exchange (IDX) that have the potential to apply for loans/credits to Bank Financial Institutions (IKB) in optimizing the corporate capital structure through bank debt facilities in the period 2022. Analysis was conducted on five financial aspects consisting of 14 research variables, including (i) liquidity aspects, including current ratio and quick ratio variables; (ii) solvency aspects, including debt asset ratio and equity ratio variables; (iii) profitability aspects including return on net assets, operating profit ratio, price to earnings ratio variables, (iv) activity aspects including total asset turnover, accounts receivable turnover, inventory turnover, current assets turnover, and (v) growth aspects including operating income growth rate, total assets growth rate, and operating profit growth rate variables. The analysis tool uses Logistic Regression through an assessment conducted on the company's credit rating as a proxy for the dependent variable, worth one if the credit application is feasible and worth 0 if the credit application is not feasible with a cut-off point of 0.5. The results show that credit scoring modeling for corporate credit is significantly formed from liquidity (CR) and solvency (DER) aspects. Out of 61 companies classified as not eligible for credit facilities, 58 companies were classified correctly, and out of 39 companies classified as eligible, 29 companies were classified correctly. The overall percentage shows 68.0, meaning that the logistic regression model has an accuracy of 68%.

ANALYSIS OF THE EFFECT OF MANAGEMENT OF RECEIVABLES RISK WITH CREDIT SCORING ON CREDIT COLLECTIBILITY

A good management of account receivable is needed to encourage company revenues to be able to fulfill financing needs. One way to manage receivables is to do credit scoring. This research was conducted to examine the effect, direction, and significance of credit scoring on credit collectability at PT Krakatau Steel in 2022 to 2023. In this study, the data used is secondary data, obtained from company archives. The population of this study is all consumers registered in the company, namely as many as 709 companies. The number of samples taken was 228 samples with the criteria of consumers who are still making transactions from 2022 to 2023. The results obtained using descriptive analysis show that credit scoring is in the good category and the company's credit collection is in the current category. Credit scoring has a positive and significant effect of 74.2% on credit collectability at PT Krakatau Steel with a significance level of 0.000

Empirical Research on Credit Evaluation of Real Estate Industry Based on Multi-source Data Fusion

In this paper, based on the evaluation of corporate credit risk using traditional financial indicators, we will combine with non-financial data, define whether the listed company has ST in its abbreviation as a default fact, and establish a logistic model to quantitatively analyze the credit risk. In this paper, 123 listed companies in the real estate industry are used as samples, and the financial data, number of employees, percentage of shareholding of the largest shareholder, and CEO's education disclosed in the 2019 and 2020 annual reports are obtained through the Guotaian and CNRDS databases. Using principal component analysis to extract principal component factors from 21 financial data and combining non-financial indicators, a logistic model based on financial indicators and a logistic model based on financial and non-financial data were constructed to study the impact of non-financial data on company credit risk. It is found that non-financial indicators reflecting company size as well as corporate governance ability have a certain degree of influence on the credit risk of the company, i.e., the prediction results of the logistic model based on financial and non-financial data are more effective.

Contagion Patterns Classification in Stock Indices: A Functional Clustering Analysis Using Decision Trees

This paper aims to identify the main determinants of the countries that present contagion during the period 2000–2021, based on the determination of the behavior patterns of 18 stock market indices of 15 of the main economies. To do that, first, the B-spline method and Bezier curves are used to smooth observations by minimizing the noise. Subsequently, the Functional Principal Component Analysis (FPCA) methodology is applied. Then, the K-means clustering algorithm is used to determine the main groups using the silhouette method and cross-validation, considering the sum of squares of the distances as the function to minimize. Finally, classification trees and macroeconomic and financial analyses are used to determine the rules of variables that give a direct explanation of the contagion (clustering) between the stock indices. The main empirical results obtained suggest that the most significant macroeconomic variables are the Gross Domestic Product, the Consumer Price Index, and Foreign Direct Investment, while in the financial aspect and the most representative are Domestic Credit and number of companies listed on the stock market. It is worth noticing that government spending does not have a significant effect at any time as a determinant of contagion. Finally, it is important to mention, and surprising, that Mexico’s IPC was not clustered in the same group of US stock market indices anytime, despite the strong commercial relationship and the geographical closeness.

Early Warning of Companies' Credit Risk Based on Machine Learning

With the advent of the big data era, information barriers are gradually being broken down and credit has become a key factor of company operations. The lack of company credit has greatly and negatively impacted the social economy, which has triggered considerable research on company credit. In this article, a credit risk warning model based on the XGBoost-SHAP algorithm is proposed that can accurately assess the credit risk of a company. The degree of influence of the characteristics of a company's credit risk and the warning threshold of important characteristics are obtained based on the model output. Finally, a comparison with several other machine learning algorithms showed that the XGBoost-SHAP model achieved the highest early warning accuracy and the most comprehensive explanatory output results. The experimental results show that the method can effectively provide a warning of the credit risk of a company based on the historical performance of the company's historical characteristics data. This method provides positive guidance for companies and financial institutions.

SWOT Based Analysis of the Impact of Prepayment Business Model on Brands and Consumers-Starbucks as an Example

The prepayment business model means that customers give retailers credit first, make payments in advance, and put off using the goods or services. This business strategy acquires clients by means of discounts on prepaid consumer cards, which is advantageous to the firms to withdraw cash and lock in customers. The limited edition prepayment physical card may be collaboratively customized with a variety of artistic and cultural works, promotional campaigns can be jointly launched using the prepayment business model.However, because this business model uses credit to advance product or service fees, consumers are in a weak position after payment and are vulnerable to infringement and fraud by bad businesses, so the reputation of this business model is polarized. Businesses typically offer significant discounts on prepaid consumption. In order to analyze the SWOT technique and the good and negative effects of the prepayment business model on enterprises, this article will use Starbucks as an example. According to the report, prepayment business models are used by retailers with solid financial standing and excellent company credit to build customer loyalty, secure a steady cash flow, and maintain a deposit pool. Under this consumption model, consumers might profit from the discount.

L’évaluation du crédit marchand à Montréal dans la seconde moitié du dix-neuvième siècle

This article examines one of the most prominent and powerful credit rating agencies in North America, the Mercantile Agency and its Montréal-based counterpart, Dun, Wiman & Co. The paper considers the context surrounding the first North American credit rating agencies, their managers’ profiles, the specific characteristics of the Montréal offices and, finally, the two primary methods of information transmission offered by the agency: the reference book and the credit report. I argue that issuing the reference book resulted in increasing access to credit for companies with high capitalization rates from creditors who possessed a subscription. Meanwhile, credit reports allow for greater flexibility in interpretation than a credit score. They thus offer additional leeway to debtor merchants who have little capitalization precisely because the creditor can interpret in various ways the content of the written evaluation. Foremost, the article provides an introduction to credit rating agencies as well as a general overview of the Montréal branch of the Mercantile Agency. Finally, the purpose of this research is to contribute to historiography by presenting an institution of credit regulation that has yet to receive much attention from the field of Canadian history.

Cultural aspects of the use of trade credit

Purpose: This paper aims to (1) provide insight into the cultural issues of the use of trade credit, focusing on the links between trade credit and trust, religion, and national culture, and (2) suggest potential directions for future research in this area. 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. Research limitations/implications: This review does not address all potential cultural factors that may impact the use of trade credit. In addition, the review is constrained by the limited research conducted in this area and the heterogeneity of the studies analyzed. 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. Keywords: trade credit, trust, religion, national culture, ethics. Category of the paper: Literature review.

EFEKTIVITAS PENGELOLAAN PIUTANG UNTUK MENINGKATKAN LABA PADA CV. GARUDA PERKASA HONDA MOTOR SIBOLGA

This research takes the title of the Effectiveness of Receivables Management to Increase Company Profits. The need to look for cash and credit sales on the influence of receivables that generate profits in the company. The aim of the research is to know the accounts receivable management policy implemented by the company as well as to know the effective management of accounts receivable and to find out what are the obstacles faced by companies in managing receivables. The type of research used is descriptive research with a case study approach. This research takes place at CV. Garuda Mighty Honda Motor Sibolga. which is on Jalan R. Junjungan Lubis No. 1-3 Sibolga City District. Data collection techniques are carried out by collecting methods through interviews and documentation. Analysis of the data used in this study by performing calculations in accordance with the existing problems. The results showed that the company's credit sales have increased significantly in the last five years, and the collection of accounts receivable has accelerated so that the collection results can be rotated by the company according to needs. . The existence of effective accounts receivable management is able to make the company earn more profits from year to year. Suggestions are that the company is expected to be better at collecting receivables and management is expected to be able to provide discounts on credit sales. Discounts that can be given by the company are in the form of installment discounts if the customer pays off sooner than the time period agreed by both parties. In addition, it is hoped that the results of the research will serve as a guideline for further researchers to develop this research to develop the results of the problems that have been discussed.

State ownership and corporate credit sales

An enterprise's sales return ability is an important indicator of its future development, and enterprises often want to transact with cash to ensure sufficient cash flow and thus sustain their normal development operations. This paper will use public data of Chinese listed companies from 2008 to 2021 to explore the relationship between the percentage of state ownership in a company and the company's credit sales policy, and concludes the following: the higher the percentage of state ownership in a company, the lower the percentage of credit sales in a company. This reflects that state ownership helps firms to occupy a favorable position in transaction negotiations and is conducive to improving firms' ability to pay back. In addition, this paper makes policy recommendations for reference in response to the research findings.

ESG Principles in International Business and Sustainable Contracts

The concept of sustainable development has captured the world. It is altering society, generating new social patterns, reorganizing business and management models, testifying to the ultimate connectedness of the world and, as a result, encourages rethinking the legal superstructure, adapting supernova normative arrays to the current legal taxonomy, which is not always possible with taking into account the positivist approach to law. ESG principles have today become a kind of model for sustainable business development, due to which the goals of companies’ involvement in solving environmental, social and management problems are achieved. They have not only a vector effect, but also a regulatory, reputational; they have also an increasing impact on international business in a variety of industries. In addition, they are updating relatively new rating mechanisms that form the basis of investment, financial, credit, trade, corporate, management and other policies of companies. At the same time, ESG principles are segmented, fragmented and, as a rule, objectified externally in the form of norms of nonstate, often industry regulation. Without legally binding force, ESG principles are quite comparable with law in terms of the degree of impact on public relations and in terms of the resulting legal and economic consequences. Cross-border contracting practices are also changing, leading to the incorporation of “sustainability” clauses into contracts, as well as the emergence of the concept of a sustainable contract. The pre-contractual stage becomes more complicated, it requires human due diligence procedures, the formation and assessment of supply chains, the development of strategies for the disclosure of non-financial information, the study of legal risks taking into account the global law enforcement practice, as well as the establishment of methods and a jurisdictional forum for the resolution of disputes. International Commercial Arbitration claims to be attractive in resolving ESG disputes. These and other issues, taking into account their relevance, are studied in this paper.

Possibilities of standardised evaluation of textual data of the management report in the context of qualitative creditworthiness analysis

Companies produce corporate publications due to legal requirements, but also in particular to reduce information asymmetries. Companies will have to prepare their financial statements taking sustainability aspects into account. This influence can be analysed in future analyses. The publication of this information often leads to a reaction from investors. Previously published studies have shown a correlation between the textual sentiment of corporate publications and securities returns. These studies have focused particularly on the US region. Consequently, this paper can selectively fill the research gap for the German-speaking region. Therefore, it is an academically relevant topic. In this study, companies from the Prime Standard stock market segment for 2018 were examined to determine whether there is a correlation between the textual sentiment of the management report and the company's credit rating. It is found that there is a significant relationship between the negative sentiment and the word count on credit risk.

A comparative study of corporate credit ratings prediction with machine learning

Credit scores are critical for financial sector investors and government officials, so it is important to develop reliable, transparent and appropriate tools for obtaining ratings. This study aims to predict company credit scores with machine learning and modern statistical methods, both in sectoral and aggregated data. Analyses are made on 1881 companies operating in three different sectors that applied for loans from Turkey’s largest public bank. The results of the experiment are compared in terms of classification accuracy, sensitivity, specificity, precision and Mathews correlation coefficient. When the credit ratings are estimated on a sectoral basis, it is observed that the classification rate considerably changes. Considering the analysis results, it is seen that logistic regression analysis, support vector machines, random forest and XGBoost have better performance than decision tree and k-nearest neighbour for all data sets.

Application of Data Mining Combined with Fuzzy Multicriteria Decision-Making in Credit Risk Assessment from Legal Service Companies

The purpose is to avert the systematic financial risks from the Internet financial bubble and improve the efficiency of legal service companies’ credit risk assessment ability. Firstly, this study analyzes the commonly used classification model, Support Vector Machine (SVM), and linear regression model, Logistic model, and then puts forward the integrated SVM-Logistic + Fuzzy Multicriteria Decision-Making (FMCDM) to evaluate and analyze the credit risk level of listed companies. In the proposed integrated model, the SVM model classifies the data sample from listed companies, and the Logistic model is used for regression analysis on the credit risk assessment. Based on the credit risk indexes and weight uncertain factors of sample companies, FMCDM based on fuzzy set is applied to obtain the evaluation indexes. Then, the Analytic Hierarchy Process (AHP) is used to obtain the weight of key indexes. Finally, the fit analysis is carried out according to the existing risk status of the sample company and the risk status results of the proposed integrated model. The results show that the integrated SVM-Logistic model is complementary and has high intensive evaluation. According to the fitness value obtained by FMCDM, the company's credit risk status can be accurately evaluated, and the intermediate threshold of corporate credit default risk measurement is 0.56152; if Fit is lower than the threshold, the company’s credit is low, and if Fit is higher than the threshold, the company’s credit is high. Therefore, the data mining technology based on integrated SVM-Logistic model + FMCDM has high precision and feasible application in the credit risk assessment from legal service companies. This study creates a new method model for legal service companies in the field of corporate credit risk assessment and can provide references and ideas for corporate credit risk assessment.

Brazilian Monetary Policy’s Influence on Investment Funds’ Allocation in Corporate Bonds

The aim of this paper is to understand how monetary policy influence investment funds’ allocation in corporate bonds. This assumption is in line with the perspective that several factors influence funds’ allocation process, especially changes in a country's economic scenario. The sample of this study is comprised of 352 equity funds and 1,085 multimarket funds, during the period from December 2009 to July 2020. I used multivariate regression with panel data for hypotheses testing. I noted a small percentage of funds’ investment in corporate bonds, in other words, only about 1.3% of total net of asset. In addition, multimarket funds used to invest more in debentures than equity funds. Concerning the regression model, the interest rate (Selic) had a positive association with funds’ amount allocated in corporate bonds. It is a result of Brazilian context, whose corporate bonds are indexed according to DI rate. As expected, I observed a positive relationship between inflation rate and funds’ investment in debentures, which reveals that the fear of deflation causes investors to increase the percentages invested in corporate debt securities. As respects funds’ features, time and minimum balance, do not guarantee more investment in corporate bonds. Thus, this paper contributes to the literature for bringing monetary policy closer to capital market and discussing an emerging country’s funds industry. In this way, it is relevant because it involves an important source of credit for companies, based on data from institutional investors.