An ontology-based portal for credit risk analysis
Credit risk analysis is an important topic in the financial risk management. Due to recent financial crises, credit risk analysis has been the major focus of financial and banking industry. An accurate estimation of credit risk could be transformed into a more efficient use of economic capital. Existing models for estimating credit risk are not semanticsbased. The objective of this work was to design an intelligent web portal to serve as service provider for credit risk analysis. The portal has been conceived to help users (e.g. credit managers working in banks) to detect bad payers. For this purpose, the knowledge of the financial domain has been represented by means of ontology, which has been used to guide the design of the application and to supply the system with semantic capabilities. The reasoning engine of the proposed system executes logic rules related with wellestablished financial variables. These rules characterize that a payer tends to become a bad one or not.
machine learning ontologies credit rating
S. B. Kotsiantis D. Kanellopoulos V. Karioti V. Tampakas
Educational Software Development Laboratory Department of Mathematics Greece Technological Educational Institution of Patras Greece
国际会议
北京
英文
2922-2926
2009-08-08（万方平台首次上网日期，不代表论文的发表时间）