Evolusi Penelitian Credit Scoring: Analisis Bibliometrik Tren, Kolaborasi, dan Artificial Intelligence
DOI:
https://doi.org/10.47065/arbitrase.v7i1.3252Keywords:
Bibliometric Analysis; Artificial Intelligence; Credit Scoring; Credit Risk; Financial TechnologyAbstract
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.
Downloads
References
Abdou, H. A., & Pointon, J. (2011). Credit Scoring, Statistical Techniques And Evaluation Criteria: A Review Of The Literature. Intelligent Systems In Accounting, Finance And Management, 18(2–3), 59–88. Https://Doi.Org/Https://Doi.Org/10.1002/Isaf.325
Ala’raj, M., & Abbod, M. F. (2016). Classifiers Consensus System Approach For Credit Scoring. Knowledge-Based Systems, 104, 89–105. Https://Doi.Org/Https://Doi.Org/10.1016/J.Knosys.2016.04.013
Anisa, A. S., Santoso, R. A., & Fitriana, F. (2025). Bibliometric Analysis Of Auditor Switching Development With Vosviewer. Golden Ratio Of Auditing Research, 6(17), 284–295. Https://Doi.Org/Doi Https://Doi.Org/10.52970/Grar.V6i1.1462
Baesens, B., Van Gestel, T., Viaene, S., Stepanova, M., Suykens, J., & Vanthienen, J. (2003). Benchmarking State-Of-The-Art Classification Algorithms For Credit Scoring. Journal Of The Operational Research Society, 54(6), 627–635. Https://Doi.Org/10.1057/Palgrave.Jors.2601545
Bahrul, B., Fitriana, F., & Santoso, R. A. (2024). Aiming For The Future Of Bibliometric Forecast Research In Fraud Prevention: A Review Of Digital Economy Exploration. Al-Kharaj: Journal Of Islamic Economic And Business, 5(4). Https://Doi.Org/10.24256/Kharaj.V5i4.4451
Bartlett, R., Morse, A., Stanton, R., & Wallace, N. (2022). Consumer-Lending Discrimination In The Fintech Era. Journal Of Financial Economics, 143(1), 30–56. Https://Doi.Org/Https://Doi.Org/10.1016/J.Jfineco.2021.05.047
Bellotti, T., & Crook, J. (2009). Credit Scoring With Macroeconomic Variables Using Survival Analysis. Journal Of The Operational Research Society, 60(12), 1699–1707. Https://Doi.Org/10.1057/Jors.2008.130
Berg, T., Burg, V., Gombovi?, A., & Puri, M. (2020). On The Rise Of Fintechs: Credit Scoring Using Digital Footprints. The Review Of Financial Studies, 33(7), 2845–2897. Https://Doi.Org/10.1093/Rfs/Hhz099
Desai, V. S., Conway, D. G., Crook, J. N., & Overstreet Jr, G. A. (1997). Credit-Scoring Models In The Credit-Union Environment Using Neural Networks And Genetic Algorithms. Ima Journal Of Management Mathematics, 8(4), 323–346. Https://Doi.Org/10.1093/Imaman/8.4.323
Firdausi, Q., Safitri, S., Manulang, N., Daclan, F., & Santoso, R. A. (2025). A Bibliometric Analysis Of Internal Audit Research In Indonesia. Golden Ratio Of Finance Management, 5(1), 208–218. Https://Doi.Org/Https://Doi.Org/10.52970/Grfm.V5i1.996 Website:
Halawa, D., Fitriana, F., & Santoso, R. A. (2024). Analisis Bibliometrik Atas Penelitian Belanja Perpajakan Menggunakan Aplikkasi Vosviewer. Jurnal Akuntansi Dan Pajak, 24(02), 1–7. Https://Doi.Org/Http://Jurnal.Stie-Aas.Ac.Id/Index.Php/Jap Jurnal
Jazadi, F. R., Santoso, R. A., & Fitriana, F. (2024). Memetakan Lanskap: Analisis Bibliometrik Atas Audit Report Lag. Jurnal Ekonomi, Koperasi & Kewirausahaan, 14(8). Https://Doi.Org/Https://Doi.Org/10.59188/Covalue.V14i8.4012
Kurniawan, S. A., Mayuri, N. K. L., Fitriana, F., & Santoso, R. A. (2025). Bibliometric Analysis Of The Development Of Forensic Audit Research Based On Vos-Viewer. Golden Ratio Of Finance Management, 5(1), 145–154. Https://Doi.Org/Https://Doi.Org/10.52970/Grfm.V5i1.1013 Website:
Lianawati, W., Fitriana, F., & Santoso, R. A. (2024). Studi Tata Kelola Keuangan Perusahaan Dengan Analisis Bibliometrik. Jurnal Review Pendidikan Dan Pengajaran (Jrpp), 7(1), 681–690.
Madu, D. H., Fitriana, F., Santoso, R. A., & Rusdiansyah, N. (2023). Analisis Bibliometrik Tren Kolaborasi Penelitian Antar Peneliti Terkait Dengan Audit Eksternal Suatu Bisnis Serta Instansi Pemerintah Di Indonesia (Tahun 2018-2023). Jurnal Aktiva: Riset Akuntansi Dan Keuangan, 6(1), 10–16. Https://Doi.Org/Https://Doi.Org/10.52005/Aktiva.V6i1.223
Malhotra, R., & Malhotra, D. K. (2003). Evaluating Consumer Loans Using Neural Networks. Omega, 31(2), 83–96. Https://Doi.Org/Https://Doi.Org/10.1016/S0305-0483(03)00016-1
Nazara, D. S., Fitriana, F., & Santoso, R. A. (2023). Analisis Bibliometrik Perkembangan Financial Statement Fraud Dengan Vosviewer. Jurnal Review Pendidikan Dan Pengajaran (Jrpp), 6(4), 2793–279.
Nazara, D. S., Fitriana, F., & Santoso, R. A. (2024). Analisis Bibliometrik Dengan Vosviewer Terhadap Perkembangan Penelitian Forensic Audit. Jurnal Sains Dan Teknologi, 5(3), 714–719.
Nurachman, I. A., Heryana, R. P., Luthfi, D., Fitriana, F., & Santoso, R. A. (2025). The Trend Of Audit Quality Development: A Scopus-Based Bibliometric Analysis. Golden Ratio Of Social Science And Education, 5, 230–237. Https://Doi.Org/Doi Https://Doi.Org/10.52970/Grsse.V5i1.1086
Rahmat, F., Santoso, R. A., & Fitriana, F. (2025). Analisis Bibliometrik Terhadap Perkembangan Penelitian Perpajakan Digital Dengan Vosviewer Berdasarkan Data Scopus 2018-2025. Jurnal Ilmu Ekonom, 8(3), 1304–1312. Https://Doi.Org/Https://Doi.Org/10.57178/Paradoks.V8i3.1422
Safitri, S., Firdausi, Q., Fitriana, F., & Santoso, R. A. (2024). Analisis Peran Audit Internal Terhadap Pencegahan Fraud Berdasarkan Literature Review Terindeks Sinta. Jurnal Revenue: Jurnal Ilmiah Akuntansi, 5(1), 145–157.
Santoso, R. A. (2022). Trends In Audit And Good Corporate Governance Research: A Bibliometric Analysis From 1994 To 2022 Based On Scopus Data. Golden Ratio Of Data In Summary, 2(2), 97–106. Https://Doi.Org/Https://Doi.Org/10.52970/Grdis.V2i2.660 Website:
Santoso, R. A., Rukhviyanti, N., & Hayati, N. (2023). Pemetaan Lanskap Riset Human Development Index Dan Technology Menggunakan Data Scopus Dengan Analisis Bibliometrik. Media Jurnal Informatika, 15(2), 123.
Serrano-Cinca, C., & Gutiérrez-Nieto, B. (2016). The Use Of Profit Scoring As An Alternative To Credit Scoring Systems In Peer-To-Peer (P2p) Lending. Decision Support Systems, 89, 113–122. Https://Doi.Org/Https://Doi.Org/10.1016/J.Dss.2016.06.014
Suandani, R., Dachlan, F., & Santoso, R. A. (2024). Deteksi Kecurangan Laporan Keuangan Dengan Metode Bibliometrik. Jurnal Review Pendidikan Dan Pengajaran, 7(1), 2684–2690.
Sudharmawan, S., Fitriana, F., & Santoso, R. A. (2025). Analisis Bibliographic Coupling Terkait Perilaku Audit Menggunakan Vosviewer. Jurnal Pendidikan, Akuntansi Dan Keuangan, 8(2), 113–129. Https://Doi.Org/Https://Doi.Org/10.47080/Y2hves23
Thomas, L. C. (2000). A Survey Of Credit And Behavioural Scoring: Forecasting Financial Risk Of Lending To Consumers. International Journal Of Forecasting, 16(2), 149–172. Https://Doi.Org/Https://Doi.Org/10.1016/S0169-2070(00)00034-0
Wang, G., Ma, J., Huang, L., & Xu, K. (2012). Two Credit Scoring Models Based On Dual Strategy Ensemble Trees. Knowledge-Based Systems, 26, 61–68. Https://Doi.Org/Https://Doi.Org/10.1016/J.Knosys.2011.06.020
Yazid, H., Santoso, R. A., Ismail, T., & Taqi, M. (2023). Islamic Banking Adoption Indexed
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Evolusi Penelitian Credit Scoring: Analisis Bibliometrik Tren, Kolaborasi, dan Artificial Intelligence
ARTICLE HISTORY
How to Cite
Issue
Section
Copyright (c) 2026 Arief Budiman, Rachmat Agus Santoso, Fitriana Fitriana
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
