SVM AND XBRL BASED DECISION SUPPORT SYSTEM FOR CREDIT RISK EVALUATION

This article presents a framework for an intelligent system for credit risk evaluation and a model for its implementation in cross-platform and database-independent way. This framework supports widely applied Support Vector Machines (SVM) technique as basis for intelligent evaluation and eXtensible Business Reporting Language (XBRL) standard which is widely developed, implemented and supported by governments and regulatory authorities. It also examines current SVM frameworks which can be used for new hybrid method development and the possibilities to implement them in a credit risk decision support system. A framework for a distributed credit risk evaluation system is presented together with its architecture and model for implementation.