European experience and Ukrainian realities in the policy of financial support entrepreneurial sector

Aim/purpose – We want to provide recommendations to bridge the gap in access to financing of the entrepreneurial sector in Ukraine based on the analysis of European experience, EBF approaches, financial funds for SMEs and the current state of the credit market in Ukraine. Design/methodology/approach – We used the general scientific methods of knowledge, conceptual tenets of the theory of market economy, abstract logical analysis and synthesis, induction and deduction, historical (to determine the nature and causes of bank investment in SMEs, refine categories and terms); formalization, systems analysis (to determine factors of investment banking, institutional and legal environment); statistical, retrospective analysis. The results of surveys conducted by the EBF on the issues of support and development of SMEs are used, own research of 120 Ukrainian SMEs, which was conducted during the period from January to July 2016. The nature of the research questions was reinforced by the decision to survey only SMEs. Independent reporting (from entrepreneurs or CEOs) was used to account for both business activity and the external sources of information. Findings – Policy initiatives should primarily be developed at the national level in the field of lending to SMEs based on the European experience and Ukrainian realities; it is necessary to develop an understanding of the need for access to certain types of information; SMEs are the main providers and the most valuable source of credit information. Research implications/limitations – When using the methods of calculation creditworthiness perhaps to take into account the methods for assessing the quality of management, the image of the enterprise, ISO certificates. Originality/value/contribution – Based on the cross-country comparison of the EU and Ukraine, highlight the necessity of focusing on some legal unification of SME lending procedures for the development of a culture of sustainable entrepreneurship on the European continent

Assessment of Community Banks in Nigeria

This study on community banks in Nigeria was undertaken in June 2004 by the FAO Investment Centre, with financial support from the Canadian International Development Agency (CIDA), the Department for International Development (DFID), the International Fund for Agricultural Development (IFAD), the Ford Foundation (FF), the United Nations Development Programme (UNDP) and the World Bank (WB), and in collaboration with the Central Bank of Nigeria (CBN). The objective of the study was to assess the past and present performance of community banks, in particular rural-based banks, and to propose a first framework for their support. --

Thinking Beyond Credit

Credit is often seen as an indispensable vehicle for the poor to get out of poverty, or as the tool that allows farmers to get access to new technologies, to increase productivity and their incomes. But many existing credit programmes often undermine farmers’ independence, tie them into dependency relationships, and oblige them to take all the risk. There are better ways to help farmers build their own resource base and independenc

Market for 33 percent interest loans. Financial inclusion and microfinance in India.

Financial inclusion is the process of building viable institutions that provide financial services to those hitherto excluded. These may include savings, insurances, remittances, and credit. Microfinance became the most dominant method for achieving financial inclusion. However, different microfinance schools of thought recommend opposite ways for attaining financial integration. India is a particularly insightful case study due to the sheer number of people excluded from formal financial services, as well as the spectrum of actors and approaches. The aim of this article is threefold. First, defining financial inclusion, depicting its status quo in India and comparing it to its South Asian and BRICS peers using recently released data from the Global Findex database. Second, focusing on microfinance as the dominant vehicle for achieving financial inclusion by scrutinizing its definitions, contrasting its two leading "schools of thought" and analyzing the central role of its dominant group-based approach. Third, the article will examine why people opt to take micro-credit at 33 percent interest rates

Credit financing of aquaculture programmes -- a review

A discussion is presented on the role of credit financing in the development of aquaculture programmes in Nigeria. The constraints militating against credit availability to aquaculture vis-a-vis the competition between aquaculture and other agricultural and industrial sectors for the allocation of available credit facilities are examined. Possible ways of enhancing preferential allocation of capital to the aquaculture industry from the various sources of credit available to the Nigerial agricultural economy are suggeste

Empirical analysis of credit relationships in small firms financing : sampling design and descriptive statistics

Despite the relevance of credit financing for the profit and risk situation of commercial banks only little empirical evidence on the initial credit decision and monitoring process exists due to the lack of appropriate data on bank debt financing. The present paper provides a systematic overview of a data set generated during the Center for Financial Studies research project on "Credit Management" which was designed to fill this empirical void. The data set contains a broad list of variables taken from the credit files of five major German banks. It is a random sample drawn from all customers which have engaged in some form of borrowing from the banks in question between January 1992 and January 1997 and which meet a number of selection criteria. The sampling design and data collection procedure are discussed in detail. Additionally, the project's research agenda is described and some general descriptive statistics of the firms in our sample are provided

The assessment of credit guarantee schemes for SME's: valuation and cost

Small and medium enterprises (SME' s) have important limitations from the financial viewpoint. Their reduced capability to generate resources (self-financing) and their high financial costs as compared to the profitability of investments, makes them highly dependent of short-term bank financing. Among the different mechanisms used to solve these financial problems we find credit guarantee schemes as the Loan Guarantee Associations (LGA). These (mutual or government granted) credit insurance systems were set to facilitate the access of SME ' s to the credit market covering part of the loss incurred when borrowers default on a loan. In spite of some legal differences, LGA in most European Union countries function in a fairly similar way, making therefore easier to compare their operational cost and impact on business. This study provides a model for the valuation of the costs and implicit benefits associated with the loan guarantee programs. Empirical results indicate that the use of LGA is likely to differ among SME' s depending on company size and debt financial cost. The relatively high cost of the loan guarantee, is not always fully compensated with a similar reduction of the interest rates of the financing entity, hindering, in many cases, the full development of the schemes

Forecasting creditworthiness in retail banking: a comparison of cascade correlation neural networks, CART and logistic regression scoring models

The preoccupation with modelling credit scoring systems including their relevance to forecasting and decision making in the financial sector has been with developed countries whilst developing countries have been largely neglected. The focus of our investigation is the Cameroonian commercial banking sector with implications for fellow members of the Banque des Etats de L’Afrique Centrale (BEAC) family which apply the same system. We investigate their currently used approaches to assessing personal loans and we construct appropriate scoring models. Three statistical modelling scoring techniques are applied, namely Logistic Regression (LR), Classification and Regression Tree (CART) and Cascade Correlation Neural Network (CCNN). To compare various scoring models’ performances we use Average Correct Classification (ACC) rates, error rates, ROC curve and GINI coefficient as evaluation criteria. The results demonstrate that a reduction in terms of forecasting power from 15.69% default cases under the current system, to 3.34% based on the best scoring model, namely CART can be achieved. The predictive capabilities of all three models are rated as at least very good using GINI coefficient; and rated excellent using the ROC curve for both CART and CCNN. It should be emphasised that in terms of prediction rate, CCNN is superior to the other techniques investigated in this paper. Also, a sensitivity analysis of the variables identifies borrower’s account functioning, previous occupation, guarantees, car ownership, and loan purpose as key variables in the forecasting and decision making process which are at the heart of overall credit policy