Google Trends Crisis Sentiment and Bank-Specific Conditions in Indonesian Deposit Dynamics
DOI:
https://doi.org/10.59261/bustechno.v7i4.776Keywords:
Bank Deposits, Bank-Specific Factors, Digital Crisis Sentiment, Google Trends, IndonesiaAbstract
Background: Depositor confidence can respond rapidly to crisis-related information, while bank-specific conditions shape banks’ capacity to retain funding. Digital search behavior provides a timely proxy for public attention that is not captured by conventional bank fundamentals alone.
Objective: This study examines whether Google Trends crisis sentiment and bank-specific conditions are associated with bank deposits in Indonesia and whether internal bank conditions moderate the relationship between digital sentiment and deposits.
Methods: A quantitative explanatory panel design uses quarterly observations from 35 publicly listed Indonesian banks over 2018–2023, yielding 840 bank-quarter observations. Six panel regression specifications were estimated using the Random Effects Model after panel-model selection tests. Google Trends indices for “financial crisis,” “bank liquidation,” and “failed bank” were combined with Net Interest Margin, Equity Ratio, Return on Assets, Cost to Income Ratio, and bank size.
Results: Crisis-related search intensity is negatively associated with deposits in several specifications, particularly for “financial crisis” and “failed bank.” Bank size and Return on Assets are consistently positive, whereas Net Interest Margin and Equity Ratio are negative in several models. Selected interaction terms are significant, indicating that internal bank conditions can alter the deposit response to digital crisis sentiment.
Conclusion: The findings identify digital search intensity as a complementary behavioral signal for deposit dynamics and show that its effect depends partly on bank-specific conditions. The study contributes by integrating real-time crisis attention with bank fundamentals in a multi-model Indonesian panel setting, extending depositor-behavior analysis beyond either digital sentiment or internal financial ratios considered separately.
References
Abu Al-Haija, E., Al-Haraizah, A., Lataifeh, A. S., Meqdade, M., & Yousef, N. (2026). The impact of digital banking transformation (DBT) platforms on the profitability and efficiency of Islamic banking. Journal of Islamic Marketing, 17(3), 1080–1100. https://doi.org/https://doi.org/10.1108/JIMA-06-2024-0241
Al Khatib, A. Y., Malahim, S. S., Khanji, I. M., & Jaradat, A. A. (2023). Examining the causal factors of banking achievements for Islamic banks in Jordanian Islamic banks: An analytical study. International Journal of Applied Economics, Finance and Accounting, 16(2), 264–273. https://doi.org/10.33094/ijaefa.v16i2.979
Beloglavec, S. T., & Šebjan, U. (2015). Is Trust in Banks in Slovenia Put to the Test? Naše Gospodarstvo/Our Economy, 61(3), 41–50. https://doi.org/10.1515/ngoe-2015-0012
Broekhoff, M.-C., van der Cruijsen, C., & de Haan, J. (2024). Towards financial inclusion: Trust in banks’ payment services among groups at risk. Economic Analysis and Policy, 82, 104–123. https://doi.org/https://doi.org/10.1016/j.eap.2024.02.038
Chand, S. A., Goundar, A., Tora, T., Kaur, S., Deo, A., & Maharaj, M. (2026). Bank Efficiency and Its Determinants in a Small Island Developing Economy: Evidence from Fiji Using Data Envelopment Analysis and a Two-Limit Tobit Approach. Journal of Risk and Financial Management, 19(9), 672. https://doi.org/https://doi.org/10.3390/jrfm19090672
Choi, H., & Varian, H. R. (2012). Predicting the Present with Google Trends. Economic Record, 88(s1), 2–9. https://doi.org/10.1111/j.1475-4932.2012.00809.x
Duan, Y., El Ghoul, S., Guedhami, O., Li, H., & Li, X. (2021). Bank systemic risk around COVID-19: A cross-country analysis. Journal of Banking & Finance, 133, 106299. https://doi.org/10.1016/j.jbankfin.2021.106299
Egan, M., Lewellen, S., & Sunderam, A. (2017). The Cross Section of Bank Value. In NBER Working Paper Series. National Bureau of Economic Research. https://doi.org/10.3386/w23291
Egan, M., Lewellen, S., & Sunderam, A. (2022). The cross-section of bank value. The Review of Financial Studies, 35(5), 2101–2143. https://doi.org/https://doi.org/10.3386/w23291
Fecht, F., Thum, S., & Weber, P. (2019). Fear, deposit insurance schemes, and deposit reallocation in the German banking system. Journal of Banking & Finance, 105, 151–165. https://doi.org/10.1016/j.jbankfin.2019.05.005
Gounder, N., & Sharma, P. (2012). Determinants of bank net interest margins in Fiji, a small island developing state. Applied Financial Economics, 22(19), 1647–1654. https://doi.org/10.1080/09603107.2012.674202
Habibdoust, A., Seifaddini, M., Tatar, M., Araz, O. M., & Wilson, F. A. (2024). Predicting COVID-19 new cases in California with Google Trends data and a machine learning approach. Informatics for Health and Social Care, 49(1), 56–72. https://doi.org/https://doi.org/10.1080/17538157.2024.2315246
Hanson, S. G., Ivashina, V., Nicolae, L., Stein, J. C., Sunderam, A., & Tarullo, D. K. (2024). The Evolution of Banking in the 21st Century: Evidence and Regulatory Implications. Brookings Papers on Economic Activity, 343–389. https://doi.org/https://doi.org/ 10.1353/eca.2024.a943918
Hidayat, A., Liliana, Gustriani, Shodrokova, X., & Hakim, M. N. (2024). Covid-19 pandemic: Impact on net interest margin of Indonesian banking industry. Sriwijaya International Journal of Dynamic Economics and Business, 8(1), 23–44. https://doi.org/10.29259/sijdeb.v8i1
Khawatida, A., Wahyudi, S., & Muharam, H. (2024). Analisis pengaruh Capital Adequacy Ratio, Non-Performing Loan, dan Equity Ratio terhadap kinerja keuangan bank di Indonesia. Jurnal Ekonomi
Kunwar, B., & Jnawali, G. (2023). Impact of Macroeconomic and Bank-Specific Variables on the Profitability of Commercial Banks in Nepal. The Lumbini Journal of Business and Economics, 11(2), 80–93. https://doi.org/10.3126/ljbe.v11i2.64729
Levine, R., Lin, C., Tai, M., & Xie, W. (2021). How Did Depositors Respond to COVID-19? The Review of Financial Studies, 34(11), 5438–5473. https://doi.org/10.1093/rfs/hhab062
Maddodi, S., & Kunte, S. R. (2024). Precision forecasting in perilous times: stock market predictions leveraging google trends and momentum indicators during COVID-19. Managerial Finance, 50(10), 1747–1772. https://doi.org/10.1108/MF-02-2024-0128
Mavragani, A., & Gkillas, K. (2020). COVID-19 predictability in the United States using Google Trends time series. Scientific Reports, 10(1), 20693. https://doi.org/10.1038/s41598-020-77275-9
Naatu, F., Abendin, S., & Serwaah, P. (2025). Social Influence on Sustainable Consumption in Sub-Saharan Africa: A Case of Ghana. Journal of African Business, 1–25. https://doi.org/https://doi.org/10.1080/15228916.2025.2565535
Narteh, B., & Owusu-Frimpong, N. (2011). An analysis of students’ knowledge and choice criteria in retail bank selection in sub-Saharan Africa: The case of Ghana. International Journal of Bank Marketing, 29(5), 373–397. https://doi.org/10.1108/02652321111152909
Preis, T., Moat, H. S., & Stanley, H. E. (2013). Quantifying Trading Behavior in Financial Markets Using Google Trends. Scientific Reports, 3(1), 1684. https://doi.org/10.1038/srep01684
Priyarsono, D. S., & Laelia, S. M. (2023). Google Trends as a predictor of inflation: The case of Indonesia. Indonesian Journal of Economics and Management, 3(2), 264–274.
Ranjan, R. (2025). Behavioural Finance in Banking and Management: A Study on the Trends and Challenges in the Banking Industry. Asian Journal of Economics, Business and Accounting, 25(1), 374–386. https://doi.org/10.9734/ajeba/2025/v25i11657
Rathke, B. H., Yu, H., & Huang, H. (2023). What Remains Now That the Fear Has Passed? Developmental Trajectory Analysis of COVID-19 Pandemic for Co-occurrences of Twitter, Google Trends, and Public Health Data. Disaster Medicine and Public Health Preparedness, 17, e471. https://doi.org/10.1017/dmp.2023.101
Rech, J. (2007). Discovering trends in software engineering with Google trend. ACM SIGSOFT Software Engineering Notes, 32(2), 1–2. https://doi.org/10.1145/1234741.1234765
Rida, S. H. (2026). The effect of inflation rate on deposits: a study on One Bank PLC. Bina Bangsa International Journal of Business and Management.
Saif-Alyousfi, A. Y. H. (2024). Bank depositors in Arab economies amidst the COVID-19 pandemic. Forum for Economic and Financial Studies, 2(1), 338. https://doi.org/10.59400/fefs.v2i1.338
Saputro, N., Pamungkas, P., Trinugroho, I., Mahulette, Y. C., Sergi, B. S., & Goh, L. T. (2024). Google Trends, bank popularity and depositors’ fears in Indonesia. Managerial Finance, 50(6), 1089–1100. https://doi.org/10.1108/MF-03-2023-0144
Sinay, L. J., Hatane, S. E., & Widjaja, S. (2022). Pengaruh faktor spesifik bank dan makroekonomi terhadap risiko kredit perbankan di Indonesia. Jurnal Akuntansi Dan Keuangan, 24(2), 89–102.
Sudrajat, A. R., & Sumiyati. (2019). The Effect of Consumer Interest on Islamic Bank and Conventional Bank Mobile Banking: An Analysis Using Google Trends. IOP Conference Series: Materials Science and Engineering, 662(6), 62019. https://doi.org/10.1088/1757-899X/662/6/062019
Tran, D. V. (2022). How do depositors respond to bank dividend policy? Evidence from market discipline, global financial crisis and COVID-19 pandemic. Asian Academy of Management Journal of Accounting and Finance, 18(2), 21–39. https://doi.org/https://doi.org/10.21315/aamjaf2022.18.2.2
Tümmler, M. (2022). Completing banking union? The role of national deposit guarantee schemes in shifting member states’ preferences on the European deposit insurance scheme. JCMS: Journal of Common Market Studies, 60(6), 1556–1572. https://doi.org/https://doi.org/ 10.1111/jcms.13318
Ullah, I., Rashid, N., Babar, S., & Iqbal, N. (2026). Exploring the relationship between trait emotional intelligence and performance in the context of SME software engineering. Journal of Software: Evolution and Process, 38(1), e70076.
Venugopal, S. K. (2023). Do Systematically Important Banks Pursue Low-Cost Deposits: Insights from a Difference-in-Differences Estimation. Theoretical Economics Letters, 13(5), 1289–1306. https://doi.org/10.4236/tel.2023.135072
Wang, Y., Song, G., & Lu, Y. (2025). Geopolitical risk, bank regulation, and systemic risk: A cross-country analysis. Finance Research Letters, 76, 106893.
Werner, R. A. (2016). A lost century in economics: Three theories of banking and the conclusive evidence. International Review of Financial Analysis, 46, 361–379. https://doi.org/10.1016/j.irfa.2015.08.014
Wu, D., Xu, Z., & Bach, S. (2023). Using Google Trends to predict and forecast avocado sales. Journal of Marketing Analytics, 11(4), 629–641.
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