ARTIFICIAL INTELLIGENCE AS A DRIVER OF INNOVATION IN MODERN FINANCIAL SYSTEMS
DOI:
https://doi.org/10.59864/Oditor12602MJKeywords:
artificial intelligence, financial systems, AI adoption, digital innovation, risk managementAbstract
Artificial intelligence (AI) has become an important driver of innovation and digital transformation in modern financial systems. This study empirically examines patterns of AI adoption across key banking functions and geographical regions using descriptive and comparative analysis of secondary quantitative data obtained from recent industry reports and market analyses. The findings indicate that AI adoption is highest in fraud detection (60–65%) and risk management (approximately 60%), while adoption in credit scoring remains comparatively lower (45–50%). The regional analysis reveals substantial disparities, with North America recording the highest adoption rate (65%) and Africa and the Middle East the lowest (40%). The results also highlight increasing investment and market growth, confirming the strategic importance of AI for financial innovation. The study contributes to understanding current patterns of AI-driven transformation while emphasizing the need for responsible implementation, regulatory adaptation, data protection, and transparent AI governance.
Downloads
References
Ahmed, F., & Iqbal, A. (2025). The role of artificial intelligence in enhancing credit risk management: A systematic literature review of international banking systems. Pakistan Journal of Humanities and Social Sciences, 13(1), 478-492. https://doi.org/10.52131/pjhss.2025.v13i1.2727
AIFreaksHQ. (2025). AI in finance / Industry report 2025: Market size and adoption. Retrieved from https://aifreakshq.com/reports/ai-in-finance/
Ayari, H., Guetari, P. R., & Kraïem, P. N. (2026). Machine learning powered financial credit scoring: A systematic literature review. Artificial Intelligence Review, 59, 13. https://doi.org/10.1007/s10462-025-11416-2
Bello, O. A. (2023). Machine learning algorithms for credit risk assessment: An economic and financial analysis. International Journal of Management Technology, 10(1), 109-133. https://doi.org/10.37745/ijmt.2013/vol10n1109133
Bučalina Matić, A., Stanojević, Lj., & Milić, S. (2025). Uticaj generativne veštačke inteligencije na proces kreiranja digitalnih sadržaja. Društveni horizonti, 5(10). https://drustveni-horizonti.fdn.edu.rs/storage/articles/pdfs/VnIBGrkCIYvvspVsMfwdwAyrCRco3zao7jgnSl0o.pdf
Bussmann, N., Giudici, P., Marinelli, D., & Papenbrock, J. (2021). Explainable machine learning in credit risk management. Computational Economics, 57, 203–216. https://doi.org/10.1007/s10614-020-10042-0
Chevuri, R. R. (2025). The role of explainable AI in promoting transparency in financial decision-making. World Journal of Advanced Research and Reviews, 26(1), 1294–1301. https://doi.org/10.30574/wjarr.2025.26.1.1160
CoinLaw. (2025a). AI in fintech market statistics 2026: Growth, trends & innovations. Retrieved from https://coinlaw.io/ai-in-fintech-market-statistics/
CoinLaw. (2025b). AI in banking statistics 2026: Adoption, savings & customer impact. Retrieved from https://coinlaw.io/ai-in-banking-statistics/
Dašić, B., Pavlović, N., & Savić, M. (2024). Technological progress and digitization in the function of the development of e-education in Serbia. Akcionarstvo, 30(1), 257-280. https://doi.org/10.65772/ak2024112
ElectroIQ. (2025). AI in finance statistics, trends and facts 2025: Adoption, use cases and market overview. Retrieved from https://electroiq.com/stats/ai-in-finance-statistics/
Gojković, B., Obradović, Lj., Kecman, A. V., & Stojanović, M. (2025). The impact of artificial intelligence on contemporary business: A scoping review. Oditor, 11(3). https://doi.org/10.59864/Oditor92503BZ
Ionescu, S. A., & Diaconita, V. (2023). Transforming financial decision-making: The interplay of AI, cloud computing and advanced data management technologies. International Journal of Computers Communications & Control, 18(6), Article 5735. https://doi.org/10.15837/ijccc.2023.6.5735
Leo, M., Sharma, S., & Maddulety, K. (2019). Machine learning in banking risk management: A literature review. Risks, 7(1), 29. https://doi.org/10.3390/risks7010029
Limajatini, L., Suhendra, S., Pangilinan, G. A., & Ilham, M. G. (2025). Integration of artificial intelligence in the financial sector: Innovation, risks and opportunities. International Journal of Cyber and IT Service Management, 5(1), 58-70. https://doi.org/10.34306/ijcitsm.v5i1.165
Oko-Odion, C. (2025). AI-driven risk assessment models for financial markets: Enhancing predictive accuracy and fraud detection. International Journal of Computer Applications Technology and Research, 14(4), 80-96. https://doi.org/10.7753/IJCATR1404.1007
Olanrewaju, A. G. (2025). Artificial intelligence in financial markets: Optimizing risk management, portfolio allocation, and algorithmic trading. International Journal of Research Publication and Reviews, 6(3), 8855-8870. https://doi.org/10.55248/gengpi.6.0325.12185
Rashwan, A. R. M. S., & Kassem, Z. A. E. A. (2021). The role of digital transformation in increasing the efficiency of banks’ performance to enhance competitive advantage. In The big data-driven digital economy: Artificial and computational intelligence (pp. 325-335). Springer International Publishing. https://doi.org/10.1007/978-3-030-73057-4_25
Rustandi, R., & Arifin, A. H. (2024). AI in finance: A systematic literature review. Proceeding International Collaborative Conference on Multidisciplinary Science, 1(2), 323-338. https://doi.org/10.70062/iccms.v1i2.66
Sargiotis, D. (2024). Ethical AI in information technology: Navigating bias, privacy, transparency, and accountability. Advances in Machine Learning & Artificial Intelligence, 5(3), 1-14. https://doi.org/10.33140/AMLAI.05.03.03
Savić, M. (2025). Digitalizacija i njen uticaj na efikasnost bankarskog sektora. Akcionarstvo, 31(1), 147–155. https://doi.org/10.65772/ak2025112
Tebenko, V., Kutsai, N., Shashyna, M., Omelianenko, O., & Bakushevych, I. (2024). Digital transformation in business: The impact of technology on efficiency, innovation and competitiveness. Economic Affairs, 69(Special Issue), 307-315. https://doi.org/10.46852/0424-2513.1.2024.32
Vuković, D. B., Dekpo-Adza, S., & Matović, S. (2025). AI integration in financial services: A systematic review of trends and regulatory challenges. Humanities and Social Sciences Communications, 12, 562. https://doi.org/10.1057/s41599-025-04850-8
West, J., & Bhattacharya, M. (2016). Intelligent financial fraud detection: A comprehensive review. Computers & Security, 57, 47–66. https://doi.org/10.1016/j.cose.2015.09.005
Zong, Z., & Guan, Y. (2025). AI-driven intelligent data analytics and predictive analysis in Industry 4.0: Transforming knowledge, innovation, and efficiency. Journal of the Knowledge Economy, 16(1), 864-903. https://doi.org/10.1007/s13132-024-02001-z
