Evolusi Penelitian Credit Scoring: Analisis Bibliometrik Tren, Kolaborasi, dan Artificial Intelligence - Arief Budiman; Rachmat Agus Santoso; Fitriana Fitriana (Forum Kerjasama Pendidikan Tinggi, 2026)
The rapid development of digital transformation, financial technology (fintech), and artificial intelligence has significantly reshaped credit assessment systems within the financial industry. Although research on credit scoring has grown substantially, comprehensive studies mapping the evolution of this literature remain limited. This study aims to examine the development of credit scoring research based on Scopus-indexed publications from 1976 to 2026 using a Biblioshiny-based bibliometric approach. The dataset was obtained through a systematic screening process, resulting in 447 articles that met the inclusion criteria. The analysis focuses on publication characteristics, international collaboration patterns, topic evolution, and the most influential documents in the field. The findings reveal that credit scoring research has experienced steady growth with an annual growth rate of 5.42% and increasing international collaboration. The United Kingdom, China, and the United States emerge as the leading contributors to the global literature. The trend topics analysis indicates a substantial shift from traditional statistical approaches toward the adoption of machine learning, deep learning, artificial intelligence, alternative data, and fintech. The novelty of this study lies in its comprehensive bibliometric mapping that integrates publication trends, scientific collaboration networks, topic evolution, and the transformation of artificial intelligence applications within credit scoring research over the last five decades. This study contributes theoretically to understanding the evolution of credit scoring literature and practically to the development of technology-based credit assessment systems.