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International Journal of Advanced Artificial Intelligence Research

Open Access Peer Review International
Open Access

Machine Learning and Artificial Intelligence Deployment in Financial Services: An Advanced Structural and Performance Evaluation Model for Sector-Wide Adoption

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Dr. Nguyen Thanh Huy 1 , Dr. Le Thi Mai Anh 1 ,
4 Faculty of Information Technology, Vietnam National University, Hanoi, Vietnam
4 School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam

Abstract

The rapid integration of Artificial Intelligence (AI) and Machine Learning (ML) in financial services has fundamentally transformed decision-making, risk assessment, customer engagement, and operational efficiency across global banking and financial ecosystems. This study proposes an advanced structural and performance evaluation model for sector-wide adoption of AI and ML technologies in financial services. The research synthesizes existing literature on AI-driven financial transformation, identifies critical adoption determinants, and develops a conceptual framework for evaluating technological, organizational, and regulatory readiness.

Drawing on systematic literature from fintech innovation, algorithmic finance, and banking digitalization, this paper highlights the dual role of AI as both an enabler of financial efficiency and a source of governance complexity. Prior research emphasizes that AI enhances predictive accuracy in credit scoring, fraud detection, and portfolio optimization while simultaneously introducing challenges related to transparency, bias, and regulatory compliance (Cao, 2020; Duan et al., 2019). Furthermore, AI’s strategic implications in financial systems are strongly influenced by public policy frameworks and institutional readiness (Bredt, 2019).

The proposed model integrates structural dimensions (data infrastructure, algorithmic capability, and system interoperability) with performance dimensions (efficiency, accuracy, scalability, and risk mitigation). The study contributes to the growing discourse on AI-driven financial transformation by offering a consolidated analytical framework that supports both academic understanding and practical deployment strategies.

 

Keywords

Artificial Intelligence, Machine Learning, Financial Services, FinTech

References

B. Bredt, “Artificial Intelligence (AI) in the financial sector—potential and public strategies,” Frontiers in Artificial Intelligence, vol. 2, Oct. 2019.
D. Bianchi, M. Büchner, and A. Tamoni, “Bond risk premiums with machine learning,” The Review of Financial Studies, vol. 34, no. 2, pp. 1046–1089, Jan. 2021.
M. Biallas and F. O’Neill, “Artificial intelligence innovation in financial services,” International Finance Corporation, vol. 85, no. 6, pp. 1–8, 2020.
L. Cao, “AI in finance: a review,” SSRN Electronic Journal, 2020.
Y. Cao and J. Zhai, “A survey of AI in finance,” Journal of Chinese Economic and Business Studies, vol. 20, no. 2, pp. 125–137, Apr. 2022.
Y. Duan, J. S. Edwards, and Y. K. Dwivedi, “Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda,” International Journal of Information Management, vol. 48, pp. 63–71, 2019.
P. K. Donepudi, M. H. Banu, W. Khan, T. K. Neogy, A. B. M. Asadullah, and A. A. A. Ahmed, “Artificial intelligence and machine learning in treasury management: a systematic literature review,” International Journal of Management (IJM), vol. 11, no. 11, pp. 13–22, 2020.
O. H. Fares, I. Butt, and S. H. M. Lee, “Utilization of artificial intelligence in the banking sector: a systematic literature review,” Journal of Financial Services Marketing, vol. 28, no. 4, pp. 835–852, 2023.
L. Fourie and T. K. Bennett, “Super intelligent financial services,” Journal of Payments Strategy and Systems, vol. 13, no. 2, pp. 151–164, 2019.
A. Geetha, “A study on artificial intelligence (AI) in banking and financial services,” International Journal of Creative Research Thoughts (IJCRT), vol. 9, no. 9, pp. 110–114, 2021.
A. Ghandour, “Opportunities and challenges of artificial intelligence in banking: systematic literature review,” TEM Journal, pp. 1581–1587, 2021.
Z. Golić, “Finance and artificial intelligence: the fifth industrial revolution and its impact on the financial sector,” Proceedings of the Faculty of Economics in East Sarajevo, vol. 8, no. 19, pp. 67–81, 2020.
Y. Han, J. Chen, M. Dou, J. Wang, and K. Feng, “The impact of artificial intelligence on the financial services industry,” Academic Journal of Management and Social Sciences, vol. 2, no. 3, pp. 83–85, 2023.
J. Huang, J. Chai, and S. Cho, “Deep learning in finance and banking: A literature review and classification,” Frontiers of Business Research in China, vol. 14, no. 1, 2020.
IDC, “New IDC spending guide shows continued growth for digital transformation in 2020, despite the challenges presented by the COVID-19 pandemic,” Business Wire, 2020.
J. Jagtiani and C. Lemieux, “The roles of alternative data and machine learning in fintech lending: Evidence from the LendingClub consumer platform,” Financial Management, vol. 48, no. 4, pp. 1009–1029, 2019.
N. Kaur, S. L. Sahdev, M. Sharma, and L. Siddiqui, “Banking 4.0: ‘The influence of artificial intelligence on the banking industry and how AI is changing the face of modern-day banks,’” International Journal of Management, vol. 11, no. 6, pp. 577–585, 2020.
L. Kruse, N. Wunderlich, and R. Beck, “Artificial intelligence for the financial services industry: What challenges organizations to succeed,” in Proceedings of the Annual Hawaii International Conference on System Sciences, 2019.
L. Lakhchini et al., “Artificial intelligence & machine learning in finance: a literature review,” 2022.
L. Lakhchini et al., “Artificial intelligence & machine learning in finance: a literature review,” 2022.
A. Lee, “Banking on artificial intelligence,” SSRN Electronic Journal, 2017.
M. Leo, S. Sharma, and K. Maddulety, “Machine learning in banking risk management: a literature review,” Risks, vol. 7, no. 1, 2019.
A. Lui and G. W. Lamb, “Artificial intelligence and augmented intelligence collaboration: regaining trust and confidence in the financial sector,” Information & Communications Technology Law, vol. 27, no. 3, pp. 267–283, 2018.
A. Machkour and A. Abriane, “Industry 4.0 and its implications for the financial sector,” Procedia Computer Science, vol. 177, pp. 496–502, 2020.
A. Malali and S. Gopalakrishnan, “Application of artificial intelligence and its powered technologies in the indian banking and financial industry: an overview,” IOSR Journal of Humanities and Social Science, vol. 25, no. 6, pp. 55–60, 2020.
S. Mishra, “Exploring the impact of AI-based cyber security financial sector management,” Applied Sciences, vol. 13, no. 10, 2023.
N. Milojević and S. Redzepagic, “Prospects of artificial intelligence and machine learning application in banking risk management,” Journal of Central Banking Theory and Practice, vol. 10, no. 3, pp. 41–57, 2021.
R. Murugesan and V. Manohar, “AI in financial sector – a driver to financial literacy,” Shanlax International Journal of Commerce, vol. 7, no. 3, pp. 66–70, 2019.
M. Nazareth and R. Reddy, “Financial applications of machine learning: A literature review,” 2023.
V. Padmanabhan and P. V. Metilda, “An impact of artificial intelligence in indian banking industries,” International Research Journal of Education and Technology, vol. 1, no. 4, pp. 39–45, 2021.
S. B. Patel, P. Bhattacharya, S. Tanwar, and N. Kumar, “KiRTi: a blockchain-based credit recommender system for financial institutions,” IEEE Transactions on Network Science and Engineering, vol. 8, no. 2, pp. 1044–1054, 2021.
L. Ryll et al., “Transforming paradigms: a global AI in financial services survey,” SSRN Electronic Journal, 2020.
K. T. Sayari, “Digitalization of the financial sector,” in Revolutionizing Financial Services and Markets Through FinTech and Blockchain, IGI Global, 2023, pp. 78–98.
G. D. Sharma et al., “Sailing through the COVID-19 crisis by using AI for financial market predictions,” Mathematical Problems in Engineering, 2020.
A. Smith and H. Nobanee, “Artificial intelligence: in banking a mini-review,” SSRN Electronic Journal, 2020.
V. D. Soni, “Role of artificial intelligence in combating cyber threats in banking,” International Engineering Journal for Research & Development, vol. 4, no. 1, pp. 1–7, 2019.
S. Subanidja, M. Legowo, and F. Sorongan, “The impact of fintech on the financial and banking sustainable performance: disruption or collaboration,” 2021.
M. H. Thowfeek, S. S. Nawaz, M. B. Fathima, and Sanjeetha, “Drivers of artificial intelligence in banking service sectors,” Solid State Technology, vol. 63, no. 5, pp. 6400–6411, 2020.
J. Truby, R. Brown, and A. Dahdal, “Banking on AI: mandating a proactive approach to AI regulation in the financial sector,” Law and Financial Markets Review, vol. 14, no. 2, pp. 110–120, 2020.
S. Tripathi, R. Garg, and K. Varshini, “Role of artificial intelligence in the banking sector,” International Journal of Research Publication and Reviews (IJRPR), vol. 3, no. 9, pp. 433–442, 2022.
B. Velev and A. Zahariev, “Challenges of bank service digitalization by artificial intelligence: the case of Bulgaria,” 2022.
M. Xie, “Development of artificial intelligence and effects on financial system,” Journal of Physics: Conference Series, vol. 1187, no. 3, 2019.
Y. Xu, C.-H. Shieh, P. V. Esch, and I.-L. Ling, “AI customer service: task complexity, problem-solving ability, and usage intention,” Australasian Marketing Journal, vol. 28, no. 4, pp. 189–199, 2020.

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