The Assessment of Client Creditworthiness Using Predictive Methods Based on Multivariate Discriminant Analysis

Objective – Trade credit is the most important source of external finance for many companies. It appears on every balance sheet and represents more than 50 percent of company's short-term liabilities and a third of all company's total liabilities in OECD countries. Late payment of invoices may suffer firm's solvency. The European economies are now putting the years of financial turmoil and debt crisis behind them and several macro-economic indicators are pointing towards a brighter future. The aim of this paper is to assess creditworthiness of companies. Methodology/Technique – Assessment of client creditworthiness carried out using predictive methods based on multivariate discriminant analysis Findings – The situation in the enterprise can be characterized as stable. An enterprise that chooses this client to provide it a trade credit should also consider supplementing the predictive models by complex financial and economic analysis and review of available. If the firm provides trade credit to more clients, it is necessary to consider that the terms of trade credits may not be the same for everyone but also it is not in the power of company to approach to each client individually. Novelty – The study suggests that client groups can be created by using cluster analysis. Thus, the company may increase efficiency in the provision of trade credit. Type of Paper: Review