Digital Banking Rivalry in Indonesia: ML-Powered Analysis and Forecasting Using Search Data for Top 5 Banks

Authors

  • Asep Koswara Master of Management, Faculty of Economics and Business, IKOPIN University, Jatinangor, Indonesia

DOI:

https://doi.org/10.20961/akumulasi.v4i1.2360

Keywords:

consumer behavior, digital banking, Google Trends, Indonesia, machine learning

Abstract

The growing adoption of digital banking in Indonesia has heightened competition among financial institutions, prompting the need for data-driven insights to understand consumer behavior. This research investigates public interest in Indonesia’s five leading digital banks: SeaBank, Bank Jago, Bank Neo Commerce (BNC), blu by BCA Digital, and Allo Bank. The analysis utilized Google Trends data from 2019 to 2024. The primary goal is to explore how search behavior reflects market competition, regional adoption, and potential strategies for stakeholder decision-making. To achieve this, this research employed a quantitative approach using descriptive analysis, time-series forecasting, and clustering. ARIMA and Prophet models were applied to forecast future interest trends, while clustering techniques identified similarities in regional and temporal patterns. ARIMA is found to be more accurate for stable trends, whereas Prophet effectively detects seasonal variations. Google Trends data, while innovative and timely, has limitations as a proxy for actual consumer behavior. However, it provides valuable directional insights. For instance, SeaBank and Bank Jago show sustained interest due to their integration with ecosystem like Shopee and Gojek, respectively. In contrast, Allo Bank's popularity appears to be mostly driven by events, making it more short-lived. This research, theoretically, contributes to the fields of fintech and consumer analytics by demonstrating that search interest reflects engagement with digital banking. Practically, it provides strategic recommendations for geo-targeted marketing, ecosystem partnerships, and identification of underserved areas. These findings can help digital banks enhance their regional outreach and establish a strong brand presence in Indonesia's evolving financial landscape.

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Published

2025-06-30

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How to Cite

Digital Banking Rivalry in Indonesia: ML-Powered Analysis and Forecasting Using Search Data for Top 5 Banks. (2025). AKUMULASI: Indonesian Journal of Applied Accounting and Finance, 4(1), 56-75. https://doi.org/10.20961/akumulasi.v4i1.2360

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