Authors : Fadipe, A. O.; Dawodu O. M.; Bassey, G. P.; Akinlade, O. O.

Volume/Issue : Volume 10 - 2025, Issue 8 - August

Google Scholar : https://tinyurl.com/58s7r4tb

Scribd : https://tinyurl.com/2s4aps4f

DOI : https://doi.org/10.38124/ijisrt/25aug767

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Note : Google Scholar may take 30 to 40 days to display the article.

Abstract : This study investigates the relationship between digital accounting technologies and the financial performance of licensed deposit money banks (DMBs) in Nigeria. It focuses on three core innovations — data analytics, automated bookkeeping, and cloud-based accounting systems — and how they collectively contribute to organisational performance. A survey research design was adopted, targeting DMBs with international authorisation licenses as of April 26, 2024. Out of Nigeria’s 44 licensed banks classified into seven licensing categories, seven major DMBs, Access Bank Limited, Fidelity Bank, First City Monument Bank Limited, First Bank Nigeria Limited, Guaranty Trust Bank Limited, United Bank for Africa Plc, and Zenith Bank Plc, were selected. These institutions collectively employed 38,748 staff members. Using the Taro Yamane formula, a sample size of 396 employees was determined, and stratified sampling was applied. Data collection was conducted through a self-administered questionnaire, which yielded a reliability coefficient of 0.741 as measured by Cronbach’s Alpha. Data analysis employed descriptive statistics and linear regression, which were processed using SPSS. Out of 396 distributed questionnaires, 379 were valid for analysis. Results revealed that data analytics, automated bookkeeping, and cloud-based accounting systems each had a statistically significant and positive effect on financial performance. The study concludes that embracing digital accounting innovations substantially improves operational efficiency and profitability in Nigeria’s banking sector. It recommends, among other measures, that DMBs enhance their data analytics capabilities to sustain competitive advantage.

Keywords : Automation, Banking Sector, Cloud Accounting, Data Analytics, Digital Technologies.

References :

1. Adeyemo, F. S., & Okoronkwo, G. (2024). Artificial intelligence and operational efficiency of deposit money banks in Lagos State, Nigeria. In Technology management and the challenges of sustainable development: A Festschrift for Professor Matthew Olugbenga Ilori (pp. 4–15).
2. Akai, N. D., Ibok, N., & Akinninyi, P. E. (2023). Cloud accounting and the quality of financial reports of selected banks in Nigeria. European Journal of Accounting, Auditing and Finance Research, 11(9), 18–42.
3. Al-Ababneh, H., Borisova, V., Zakharzhevska, A., Tkachenko, P., & Andrusiak, N. (2023). Performance of artificial intelligence technologies in banking institutions. WSEAS Transactions on Business and Economics, 20, 307–317. https://doi.org/10.37394/23207.2023.20.29
4. Al-Dmour, H., Saad, N., Basheer Amin, E., Al-Dmour, R., & Al-Dmour, A. (2023). The influence of the practices of big data analytics applications on bank performance: Field study. VINE Journal of Information and Knowledge Management Systems, 53(1), 119–141. https://doi.org/10.1108/VJIKMS-09-2021-0200
5. Ali, Q., Salman, A., Yaacob, H., Zaini, Z., & Abdullah, R. (2020). Does big data analytics enhance sustainability and financial performance? The case of ASEAN banks. The Journal of Asian Finance, Economics and Business, 7(7), 1–13. https://doi.org/10.13106/jafeb.2020.vol7.no7.001
6. Alley, I., Hassan, H., Wali, A., & Suleiman, F. (2023). Banking sector reforms in Nigeria: An empirical appraisal. Journal of Financial Regulation and Compliance, 31(3), 351–378. https://doi.org/10.1108/JFRC-10-2021-0101
7. Al-Matari, E. M., Al-Swidi, A. K., & Fadzil, F. H. B. (2017). The measurements of the firm performance dimensions. Asian Journal of Finance & Accounting, 9(1), 24–49. https://doi.org/10.5296/ajfa.v9i1.10258
8. Al-Okaily, M., Al-Okaily, A., Al-Kasasbeh, M., Al-Kasasbeh, R., & Gharaibeh, M. (2020). Digital transformation and financial performance of small and medium enterprises: An empirical study in Jordan. Journal of Open Innovation: Technology, Market, and Complexity, 6(4), 124. https://doi.org/10.3390/joitmc6040124
9. Alshehri, M., Drew, S., & Alfarraj, O. (2020). A comprehensive analysis of cloud computing adoption in the Saudi healthcare sector. Technology in Society, 61, 101254. https://doi.org/10.1016/j.techsoc.2020.101254
10. Boustani, N. M. (2022). Artificial intelligence impact on bank clients and employees in an Asian developing country. Journal of Asia Business Studies, 16(2), 267–278. https://doi.org/10.1108/JABS-02-2021-0065
11. Broby, D. (2021). Financial technology and the future of banking. Financial Innovation, 7(1), 1–19. https://doi.org/10.1186/s40854-021-00248-8
12. Burke, J. J., & Burke, J. J. (2021). Distributed ledger technology. In Financial services in the twenty-first century: The present system and future developments in Fintech and financial innovation (pp. 131–154). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-57628-9_9
13. Byrd, G. T., & Ding, Y. (2023). Quantum computing: Progress and innovation. Computer, 56(1), 20–29. https://doi.org/10.1109/MC.2022.3204715
14. Cai, Y., Li, Y., & Zhang, Z. (2019). Customisation and scalability of point-of-sale systems: A case study of a fashion retailer. Journal of Information Systems, 33(2), 31–48. https://doi.org/10.2308/isys-52147
15. Castonguay, J. J., & Stein Smith, S. (2020). Digital assets and blockchain: Hackable, fraudulent, or just misunderstood? Accounting Perspectives, 19(4), 363–387. https://doi.org/10.1111/1911-3838.12247
16. Cedersund, M. (2023). Artificial intelligence in banking: The future of the banking work environment.
17. Central Bank of Nigeria [CBN] (2024). List of deposit money banks as of April 26, 2024. Retrieved from https://www.cbn.gov.ng/Out/2024/CCD/LIST%20OF%20DEPOSIT%20MONEY%20BANKS%20AS%20AT%2026TH%20APRIL,%202024%20%281%29.pdf
18. Chakraborty, C., & Joseph, A. (2017). Machine learning at central banks.
19. Chao, C. M. (2019). Factors determining the behavioural intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10, 1652. https://doi.org/10.3389/fpsyg.2019.01652
20. Chatterjee, S., Moody, G. D., & Lowry, P. B. (2020). Strategic relevance of organisational virtues enabled by information technology in organisational innovation. Journal of Strategic Information Systems, 29(1), 101618. https://doi.org/10.1016/j.jsis.2020.101618
21. Davidson, R., Goodwin, J., & Kent, P. (2021). Internal governance structures and earnings management. Accounting and Finance, 61(2), 3067–3095. https://doi.org/10.1111/acfi.12710
22. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
23. Deniz, A., & Sean, S. (2018). Blockchain basics and hands-on guidance: Taking the next step toward implementation and adoption. The CPA Journal.
24. Eziefule, A. O., Adelakun, B. O., Okoye, I. N., & Attieku, J. S. (2022). The role of AI in automating routine accounting tasks: Efficiency gains and workforce implications. European Journal of Accounting, Auditing and Finance Research, 10(12), 109–134.
25. Fadhil, A. (2018). Could AI chatbots perform higher than humans in natural language processing? International Conference on Health Informatics and Medical Systems.
26. Faggella, D. (2020). The applications of machine learning in banking – 2020 and beyond. Emerj Artificial Intelligence Research.
27. Fan, W., & Bifet, A. (2013). Mining big data: Current status and forecast for the future. ACM SIGKDD Explorations Newsletter, 14(2), 1– https://doi.org/10.1145/2481244.2481246
28. Fares, O. H., Butt, I., & Lee, S. H. M. (2022). Utilisation of artificial intelligence in the banking sector: A systematic literature review. Journal of Financial Services Marketing, 1–18. https://doi.org/10.1057/s41264-022-00176-7
29. Farouk, M. A., & Hassan, S. U. (2018). Gender diversity in boardroom and financial performance of listed firms: Evidence from Nigeria. Journal of Accounting and Taxation, 10(5), 47–57. https://doi.org/10.5897/JAT2018.0313
30. Fijabi, L. K., & Lasisi, O. R. (2023). Accounting practices in a digitalised world: Nigerian perspective. African Journal of Accounting and Financial Research, 6(1), 63–82.
31. Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007
32. Gatuhu, R. N. (2013). The effect of credit management on the financial performance of microfinance institutions in Kenya (Doctoral dissertation, University of Nairobi).
33. Gaya, F., Omoro, N., & Kinyua, H. W. (2022). Digital banking and financial performance of listed commercial banks in Kenya. African Development Finance Journal, 4(3), 169–197.
34. Godwin, J., Kent, P., & Stewart, J. (2020). Corporate governance mechanisms and corporate performance. Accounting Research Journal, 33(1), 129–143. https://doi.org/10.1108/ARJ-08-2017-0137
35. Kumar, A. (2020). Security challenges in automated teller machines (ATMs) and their implications for digital accounting: A review. International Journal of Financial Crime, 5(1), 20–35. https://doi.org/10.1108/IJFC-06-2019-0074
36. Kumar, A., Anand, A., & Song, H. (2017). Big data and machine learning in health care and banking: A case for an industry‐academic partnership. In M2M and the Internet of Things: A Wiley-IEEE Press Book (pp. 137–157). Wiley-IEEE Press.
37. Kumar, P., Shah, H., & Shankar, R. (2020). Cloud-based point of sale (POS) systems: A review and future directions. Journal of Organisational and End User Computing, 32(1), 1–15. https://doi.org/10.4018/JOEUC.2020010101
38. Kumar, V., & Reinartz, W. (2018). Customer relationship management. Springer-Verlag GmbH, Germany.
39. Oladejo, M. O., Yinus, S. O., & Aina-David, O. A. (2020). Implementation of accounting technology and financial reporting quality of quoted deposit money banks in Nigeria. International Journal of Managerial Studies and Research, 8(2), 13–21. https://doi.org/10.20431/2349-0349.0802003
40. Olayinka, A. A. (2022). Financial statement analysis as a tool for investment decisions and assessment of companies’ performance. International Journal of Financial, Accounting, and Management, 4(1), 49–66. https://doi.org/10.35912/ijfam.v4i1.325
41. Omoge, A. P., Gala, P., & Horky, A. (2022). Disruptive technology and AI in the banking industry of an emerging market. International Journal of Bank Marketing, 40(6), 1217–1247. https://doi.org/10.1108/IJBM-03-2021-0112
42. Qasaimeh, G. M., & Jaradeh, H. E. (2022). The impact of artificial intelligence on the effective applying of cyber governance in Jordanian commercial banks. International Journal of Technology, Innovation and Management (IJTIM), 2(1).
43. Rahi, S., Ghani, M. A., & Ngah, A. H. (2019). Integration of unified theory of acceptance and use of technology in internet banking adoption setting: Evidence from Pakistan. Technology in Society, 58, 101120. https://doi.org/10.1016/j.techsoc.2019.01.003
44. Zhou, W., Zhang, Y., & Xue, Y. (2018). AI-based banking risk management model and its application in real-time fraud detection. IEEE Transactions on Industrial Informatics, 14(8), 3411-3420.