Credit Worthiness Research Articles

Predicting Financial Solvency of Commercial Borrowers: The Case of Non-Banking Financial Companies

Credit risk can be effectively managed by evaluating and predicting the credit worthiness of a customer or a corporate. Credit scores are calculated to assess the credit worthiness. It helps the financial institutes to know the amount and dimensions of risk involved in different credit transactions. Credit scoring helps the financial institutes to decide whether or not to lend. It also helps in deciding the price of a particular exposure, the appropriate credit facility and different risk tools. This research paper focuses on identifying the triggers of credit default. It also focuses on checking and predicting the financial solvency of the borrowers of non-banking financial companies and assigning the credit worthiness to these companies. The data is collected from a Mumbai based NBFC. The data for the study are extracted from balance sheet and profit &loss statement of these companies. The data includes the financial ratio variables for forty companies. Altman's Z-score is used to find credit worthiness and DuPont technique is used to find the main causes of financial distress. The results of this research highlights that the borrowing companies having a lower return on equity (ROE) are prone to be in distress zone. This research would help the financial institutions to identify the most likely defaulter companies and to segment the clients/companies in safe, grey and distressed zones. The results are robust to sub-samples.

Development finance 2.0: do participation and information technologies matter?

This essay critically examines the discourse of participation in development finance directed at the poor in the Global South from national and international development agencies. This discourse, often termed financial inclusion, posits the ability of development actors to reach the poor involving them in important economic decisions affecting their lives, provides access to products that improve their material conditions, and ensures their credit worthiness through highly nuanced information technology and social media tools. The paper presents evidence from two ethnographically inspired studies undertaken by the author in India and Kenya to ascertain the ways in which the participatory discourse in finance is understood among societal participants themselves. The paper presents relevant epistemes for analyzing what 'grassroots' actors understand as their participation in development-oriented financial inclusion projects. The study forwards two major conclusions: (1) 'habits of authority' among various development actors thwart effective participation; (2) technology platforms that allow for successive innovations and interconnections from businesses and other organizations encourage financial inclusion.

Lord, Errol. The Importance of Being Rational. Oxford: Oxford University Press, 2018. Pp. 288. $60.00 (cloth).

Lord, Errol. <i>The Importance of Being Rational</i>. Oxford: Oxford University Press, 2018. Pp. 288. $60.00 (cloth).

Do environment, social and governance performance impact credit ratings: a study from India

PurposeThe purpose of this study is to determine the impact of environment, social and governance (ESG) disclosure on credit ratings of companies in India.Design/methodology/approachFirms under study are listed on the Bombay Stock Exchange (BSE) 500 and represent almost 93 per cent of the total market capitalization on BSE. This study considers a sample of 122 firms from a population of 500 to examine the relationship between ESG scores and Credit Rating. The scope of this study is confined to those firms listed on the S&P BSE 500 which have made ESG disclosures and were rated by various credit rating agencies like Crisil, ICRA and CARE. Data were sourced from Bloomberg. Ratings were given in ascending order. In the first model, credit rating was used as predicted variable; ESG score as predictor variable and market capitalization, net debt to equity, and total debt to asset as control considering the ordered nature of dependent variable in the study, ordered logistic regression was applied. It was repeated taking individual scores on environment rating, social rating and governance rating as predictors. The authors further segregated the 122 selected firms into large, medium and low capital firms and assessed separate logistic regression models taking credit rating as the predicted variable and overall ESG score as the predictor.FindingsIt was found that overall ESG performance and performance of individual components (environment, social and financial variables such as market capitalization, and debt to equity ratio) had significant positive indicators of creditworthiness as measured through credit rating. Governance score had a positive and insignificant relation with credit rating. Market capitalization was observed to have significant direct relationship with credit worthiness. On the other hand, number of independent directors in companies showed significant inverse relationship with creditworthiness. ESG significantly impacted credit rating in the desired direction only for small- and middle-level firms; for large firms which already had higher credit rating, ESG showed no effect. It was also found that credit rating itself determined significantly the extent of overall ESG reporting and disclosure of its components.Originality/valueThis is unique study that covers the aspects of ESG reports and its impact on credit rating.

Financial Performance of Kangra Central Cooperative Bank Ltd: An Analysis

Cooperative banks differ from other banks by their organization, their goals, their values and their governance. In most countries, they are supervised and controlled by banking authorities and have to respect prudential banking regulations, which put them at a level playing field with other banks. The present paper as an attempt to examine the financial health of the Kangra Central Co-operative Bank in Himachal Pradesh with the help of ratio analysis. This paper evaluates the performance of Kangra Central Cooperative banks for the period 2004-2013. Financial ratios are used to measure the profitability, liquidity and credit performance of Kangra Central Cooperative bank in Himachal Pradesh. The study found that overall bank performance improved considerably in the years of the analysis. A significant change in trend is noticed during the study period, such as fall in the long term financial position and profitability of the bank, which may resulted into deteriorating credit worthiness of the Kangra Central Cooperative Bank.

Bhushan Steel: a creditworthy company turned insolvent

Learning outcomes The purpose of this paper is to illustrate how a well-performing company can turn into a loss-making company on account of adverse industry cycle and poor management of risks in the business. The importance of factors like optimal level of leveraging, the ability of the management to deal with external and internal risks, and importance of corporate governance in the process of credit appraisal is understood from this case. Case overview/synopsis The case relates to the credit appraisal by the banks of a prominent steel company in India. The company, Bhushan Steel Limited, was doing very well. The banks lent aggressively to the company, based on their credit appraisal. However, the company soon turned insolvent on account of poor assessment of risks and deteriorating external factors. While this case may be analysed and studied through the eyes of both the Management and the lenders, the focus is currently on the latter. In a real-world scenario, the challenge for the lender is to sieve through the financial as well as non-financial data and make a valid conclusion on the level of credit worthiness of the borrowing company. This includes the topics of operational efficiency and synergies, commodity price cycles, external credit ratings, operating and financial leverage, regulatory risks and corporate governance. Complexity academic level Post graduate business management programmes – Finance specialisation. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Subject code CSS 1: Accounting and Finance

PENERAPAN ALGORITMA C4.5 UNTUK PENENTUAN KELAYAKAN PEMBERIAN KREDIT (Studi Kasus : Koperia - Koperasi Warga Komplek Gandaria)

&lt;p&gt;&lt;em&gt;Current credit giving in KOPERIA (Koperasi Warga Komplek Gandaria) is still based on an objective process. Difficulties in determining the feasibility of giving credit are often experienced by cooperative managers, so that problems arise in the cooperative is a default payment of credit installments of customers in KOPERIA. This study aims to form a decision tree classification model to determine the customer's credit worthiness. In this study the application of C4.5 Algorithm, based on the Sets and Attributes used in this study, namely, the amount of income divided into 2 categories&amp;gt; 5 million and 3-5 million, the amount of balance divided into three, namely&amp;gt; 3 million, 1-3 million and &amp;lt;1 Million, The Loan Amount is divided into three, namely 1-4 Months, 5-8 months, and 9-12 Months and Requirements with attributes of Business Capital, buying goods and others. In this study determine the appropriate root nodes, the classification results using C4.5 Algorithm shows that the accuracy of 97.5% is obtained, based on the results obtained shows that the c4.5 algorithm is suitable to be used to determine the feasibility of lending customers to KOPERIA.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Data Mining, C4.5 Algorithm&lt;/em&gt;&lt;em&gt;, loan feasibility&lt;/em&gt;&lt;/p&gt;

Fuzzy Relational Model to Establish Credit Worthiness of Sacco Members in Kenya

Fuzzy Relational Model to Establish Credit Worthiness of Sacco Members in Kenya

The value of political connections in opaque firms: Evidence from China's file 18

We examine the value of political connections in opaque firms under the setting of China's File 18. The Chinese central government has enforced File 18 since 2013 and exogenously constrained firms' political connections through independent boards. We find that the value of firms with politically-connected independent directors has significantly declined after the enforcement of File 18 only for firms with relatively higher degrees of information asymmetry. The value decline is greater among opaque firms with greater external financial dependence or lower credit worthiness, and is manifested in the drop of external financing, investments and sales growth among opaque firms. Our findings are consistent with that political connections are more conductive for firms that are more opaque by providing external financing support.

Investigating the Challenges Faced by Microfinance Institutions in Ghana: Evidence from Takoradi

Micro Finance Institutions (MFIs) contribute immensely to the economy of every nation. Particularly, within the informal sector, MFIs constitute the pivot around which many financially disadvantaged individuals rely on in terms of access to finance for their businesses. MFIs play a tremendous role in the poverty reduction and employment creation agenda of many nations including Ghana. Notwithstanding the immense role MFIs play in the economies of nations, there is a wide recognition of the fact that the institutions can perform better if they are able to overcome the challenges they face in their operations. However, in order for MFIs to effectively tackle the challenges they encounter, it is important for them to first identify and appreciate these challenges and the threats they pose to the effectiveness of their operations. Within this context, this study sought to explore the challenges MFIs in Ghana face, with particular emphasis on those operating in Takoradi. The study was quantitative, with descriptive survey as the design. Managers and employees of MFIs located in the city licensed by the Bank of Ghana were involved in the study. Simple random sampling method was used to select 114 respondents for the study and questionnaire was relied upon for data collection. The researchers used frequencies, percentages, an independent samples t-test and ANOVA as tools for data analysis. The study observed that increased competition in the industry, low repayment rates, higher cost of information technology, low level knowledge of operators, inadequate and expensive infrastructure base, high capital requirements, unfavourable regulation and supervision, inadequate employee incentives, and erosion of public confidence in MFIs were ranked as major challenges in the industry. A significant difference existed in the perception of male and female respondents on the challenges MFIs in the city faced. However, there was no statistically significant difference in educational qualifications of respondents and their views on the challenges MFIs in Takoradi faced. It is recommended that MFIs in the city should invest in staff development for all levels, from senior level to junior level. Also, Managements of MFIs should put in place adequate measures to educate their clients on the need to pay their loans and also institute appropriate sanctions to deal with loan defaulters. This will also require MFI to ensure credit worthiness of clients before granting them loans. Again, the Managements of MFIs should come out with appropriate measures to incentivize their employees so as to avoid possible cases of poaching. Key Words: Challenges, Development, Financial Institutions, Microfinance, Financial System, Poverty DOI : 10.7176/RHSS/9-10-13 Publication date :May 31 st 2019

Integrating Climate Risks into Credit Risk Assessment - Current Methodologies and the Case of Central Banks Corporate Bond Purchases

Climate change and the transition to a low-carbon economy to mitigate it engender significant economic costs. These costs are ultimately borne by households and firms, affecting their cash flows and wealth, which are key determinants of their credit worthiness. Climate-related costs are thus a source of credit risk. An accurate assessment of all credit risks, including climate credit risk, is central for creditors including central banks. If they underestimate it, they are exposed to financial losses and to the risk of holding assets of inadequate credit quality. Assessing climate risks requires methodologies based on forward-looking scenarios, on complex cause-and-effect linkages and on data that has not been observed in the past. Such models are at their infancy, but already offer meaningful insights. This note provides an overview of key components that such models are built on and illustrates them with examples of the analytics that are already available. It also applies one of the available methodologies to assess transition risk to the corporate bond holdings of the European Central Bank.

Optimizing contractor’s selection and bid evaluation process in construction industry: Client’s perspective

DOI: 10.7764/RDLC.18.3.445 Construction in developing countries is often encountered with multifarious challenges including contractor’s performance due to lack of qualification and resources. The lowest bid criterion is binding in public procurements. However, contractors exploit the loopholes in the bid process management system. This paper scrutinizes the prevalent rules for the bid evaluation and investigates the criterion used by both clients and consultants in selecting the contractors during the bids evaluation phase of construction projects in Pakistan. The current research uses the relative importance index and severity index approach to analyze the data. It was discovered that proper planning, credit worthiness, transition plans, plant and equipment holding, financial stability, past performance, and quality, are the most imperative factors, influencing the contractor’s selection procedures used by clients and consultants. Likewise, a high probability of success is presaged if the contractors are selected using the multi-criteria method. The study contributes to the body of knowledge by revealing the significant factors impacting the contractor’s selection and bid evaluation process, especially in a developing country. Its results and methodology can also be generalized with caution in other developing countries having similar work environment.

Sustainability of Small Merchants Through Digital Technologies

In the last two years, there has been an attempt to move towards a cashless society and create a Digital India. The Government of India is encouraging use of a variety of payment systems post demonetization in November 2016. The focus of this paper was to understand the use of point-of-sale (POS) systems installed by merchants and service providers for receiving payments from customers for transactions involving sale of goods and services to the public. The primary focus of the paper was to understand the adaptability, affordability, and sustainability of the payments system as seen from the point of view of small merchants. The paper is based on a study conducted in 2017, aimed at understanding the different types of payment systems that are available to the small merchants. It also looked at the difficulties faced by them and their effect on their businesses. A total of 221 responses were collected in Chennai, capital city of Tamil Nadu in South India. The results showed that cash remained the most preferred mode for business. Cash was required for working capital, payment of employee remuneration, wages, and others. With regards to the use of payment systems like POS, more awareness needs to be created about the benefits in having non-cash transactions. It seemed that the merchants would be convinced if it could improve credit worthiness and eligibility to receive loans from banks.

A Simple Factoring Pricing Model

In a simplified setting, we show how to price invoice non-recourse factoring taking into account not only the credit worthiness of the debtor but also the assignor's one, together with the default correlation between the two. Indeed, the possible default of the assignor might impact the payoff by means of the bankruptcy revocatory, especially in case of undisclosed factoring.

Interventions in Markets with Adverse Selection: Implications for Discount Window Stigma

AbstractI study the implications for central bank discount window stigma of a workhorse model of adverse selection in financial markets. In the model, firms (banks) need to borrow to finance a productive project. There is limited liability and firms have private information about their ability to repay their debts, which gives rise to the possibility of adverse selection. The central bank can ameliorate the impact of adverse selection by lending to firms. Discount window borrowing is observable and it may be taken as a signal of firms' credit worthiness. Under some conditions, firms borrowing from the discount window may pay higher interest rates to borrow in the market, a phenomenon often associated with the presence of stigma. I discuss these and other outcomes in detail and what they suggest about the relevance of stigma as an empirical phenomenon.

Sistem Pendukung Keputusan Kelayakan Pemberian Kredit Motor Honda dengan Mengunakan Metode Profile Matching

Determination of the credit worthiness of motorcycle are often inaccurate, As a result in the risk of bad debts are carried by the aplicant. It required an application decision support system that aims to analyze the applicant was eligible for the credit. The benefits obtained with this system is helping to company in determining the feasibility of granting credit. Profile matching is method of decision support system that can be used in this system. Applicants who apply for credit will be assessed based on the criteria set by the company. Then the value of the profile which is owned by an applicant will be matched by the value of the achievement of pre-defined profiles. The outcome of this process is rank wich can be used as a arecommendation for the decision maker to determine an applicant eligible to receive the credit . This software is made by using the programming language PHP and database using Mysql.

Assessing the credit worthiness of Italian SMEs and mini-bond issuers

A number of innovations have been introduced in the last five years to counter the devastating impact of credit rationing in Europe, particularly from traditional bank lending. This is a major problem for the small and medium size firms' sector in Europe, which has also suffered from bank regulatory concerns of capital adequacy, heightened emphasis on default risk of bank counterparties and the general malfunctioning of credit extension and private sector growth. In Italy, some of these less traditional sources of funding for SMEs have started to become more popular and the development of the mini-bond market is a clear example. We believe “mini-bonds” can be a success in Italy as long as the market supplies an attractive risk/return tradeoff to investors as well as affordable and flexible financing for borrowers. Assessments of credit risk must be convincing and objective, providing complements to the traditional rating agency process. In this study, we develop a new innovative model to assess SMEs' creditworthiness and we test it on the companies that have issued mini-bonds so far. Our findings confirm that the amount of information asymmetry is still high in the market and is affecting the level of risk/return trade off potentially reducing the number of investors and small businesses that would be interested in using this new channel to fund their business growth.

DATA MINING PADA PENENTUAN KELAYAKAN KREDIT MENGGUNAKAN ALGORITMA K-NN BERBASIS FORWARD SELECTION DATA MINING ON CREDIT FEASIBILITY DETERMINATION USING K-NN ALGORITHM BASED ON FORWARD SELECTION

Along with the development of economic and banking services, the term credit is one of the banking products, in determining credit worthiness required data, information about creditworthiness is an interesting issue to be in carefully. In line with business growth, the leasing or crediting sector (credit), has complex and complex problems and problems in which the data are grouped into two classes, good credit and bad credit. In banking activities the feasibility of credit determination is often the problem of bad debts caused by the failure of partial return of loans provided to the borrowers for it required accurate data prior to lending or credit. So it is appropriate to use data mining classification techniques. This study discusses the Data Mining on the determination of creditworthiness using the K-nn-based Forward Selection algorithm. K-nn algorithm applied to consumer data using credit financial services with the help of Forward Selection. The experimental results show that K-nn in classifying credit risk has accuracy value for K-nn at K = 11 accuracy = 68,30%, and for Forward Selection at K = 9 which accuracy level = 73,60%, using feature Forward Selection can produce a good degree of accuracy, so it can be applied to determine the risk of credit risk eligibility.

Predicting Credit Worthiness of Bank Customer with Machine Learning over Cloud

Predicting Credit Worthiness of Bank Customer with Machine Learning over Cloud

Counterparty Credit Risk and the Effectiveness of Banking Regulation

We investigate how counterparty credit risk influences the prices of over-the-counter CDS contracts using confidential transaction level data for practically all Dutch trades. We confirm our prior of a significant negative relationship between the credit worthiness of the CDS seller and the price of the CDS contract. We find that an increase of 100 basis points in the credit spread of the seller, decreases the price of the CDS contract by 7.2 basis points. Also, the larger the size of the CDS contract the lower the price of the CDS contract. Finally, we find that regulatory exemptions have a statistically significant but economically negligible impact on CDS pricing: Transactions exempted from banking capital requirements for Credit Valuation Adjustment risk – mostly banks transacting with non-financial institutions, sovereigns and pension funds – trade 0.14 basis points lower, all else equal.