INTELLIGENT METHODS FOR SUPPLIER EVALUATION IN TENDER MANAGEMENT SYSTEMS OF FINANCIAL ORGANIZATIONS

Kurkov Vladislav Nikolaevich, Palianov Maksim Evgenevich, Churilov Sergey Andreevich

The article presents the development of an intelligent supplier evaluation module designed for integration into the tender management system of a financial organization. The proposed model employs machine learning techniques to predict the likelihood of successful contract execution based on historical data. The system architecture is described, including data processing, classification algorithms, and result visualization. Testing results confirm the model’s high predictive accuracy and applicability in real-world procurement processes. The article also discusses prospects for functional expansion, integration of external data sources, and adaptation to related business domains.

Keywords:intelligent systems, machine learning, suppliers, tender, risk classification, predictive model, procurement