Web-Based Collector Performance Scoring System for Banking Institutions

Abstract

This study develops a web-based collector performance assessment system utilizing scoring methodologies aligned with confidential banking institutional parameters. The evaluation framework integrates quantitative metrics (personal performance and ratings), qualitative indicators (login discipline and productivity alignment), and supplementary measures (warning letters and complaint records). Developed using the Flask framework, the system underwent validation with operational data from approximately 1,000 collectors across multiple work units. The platform standardizes assessment workflows through automated data cleaning, adjustment procedures, and report generation with real-time visualization capabilities. User Acceptance Testing yielded satisfactory outcomes, confirming the system's effectiveness in minimizing human error, delivering accurate summaries for contract renewal decisions and Performance Improvement Plan monitoring, while ensuring consistent scoring methodology across organizational units.