Analysis of Big Data-Based Financial Technology and AI on Financial Inclusion in Indonesia

  • Sari Asrini Universitas Pembangunan Pancabudi
  • Dwita Sakuntala Universitas Pembangunan Panca Budi
  • Lia Nazliana Nasution Universitas Pembangunan Panca Budi
Keywords: Big Data, Artificial Intelligence, Fintech, Financial Inclusion, Panel Model

Abstract

This study aims to analyze the effect of implementing Big Data and Artificial Intelligence (AI)-based financial technology on increasing financial inclusion in Indonesia during the period 2019–2024. The background of this study is based on the rapid increase in digital transformation in the financial sector triggered by the adoption of fintech, but there is still a gap in financial access, especially among low-income groups and disadvantaged regions. This study uses a quantitative approach with a panel data model, involving independent variables of Gross Regional Domestic Product (GRDP), education level, average internet access, fintech loan recipient entities, and the number of mobile banking users on the dependent variable of the Financial Inclusion Index. The data was obtained from official publications of the Financial Services Authority (OJK), Bank Indonesia (BI), and the Central Statistics Agency (BPS). The results of the analysis show that Big Data and AI have a positive and significant contribution to expanding financial inclusion through increased credit distribution efficiency, expanded access to digital services, and personalized financial products. However, their influence is still limited by gaps in digital literacy, infrastructure, and trust in data security. The findings of this study are expected to provide strategic input for regulators, fintech industry players, and academics in formulating technology-based inclusive policies to achieve sustainable national financial inclusion targets.

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Published
2026-10-22
How to Cite
Asrini, S., Sakuntala, D., & Nasution, L. (2026). Analysis of Big Data-Based Financial Technology and AI on Financial Inclusion in Indonesia. EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi Dan Bisnis, 14(4), 5837-5850. https://doi.org/10.37676/ekombis.v14i4.11208
Section
Articles