AI is powering the comeback of traditional banks

Updated: Dec 18, 2023

Bank of Spain Main Facade

The financial world is witnessing a transformative era where Artificial Intelligence (AI), Machine Learning (ML), and Generative AI are not just buzzwords but powerful tools reshaping the industry. While neobanks have been at the forefront of innovation, traditional or incumbent banks are staging a comeback, leveraging these technologies. This essay critically examines why incumbent banks are better positioned to harness these technologies compared to neobanks or challenger banks.

AI, ML, and Generative AI: A Brief Overview

AI, with its subsets like ML and Generative AI, is revolutionising customer experience, risk management, and personalisation in banking. Machine Learning, in particular, is driving predictive analytics, automated decision-making, and customer segmentation. Generative AI, on the other hand, is fostering creativity in financial solutions, scenario simulation, and product development.

AI is powering the comeback of traditional banks

Incumbent banks find themselves in a position of strength to leverage these technologies, and several factors contribute to this advantage:

Resources and infrastructure: Traditional banks have a rich history and substantial financial resources. They possess the necessary infrastructure and vast amounts of data that are crucial for implementing and benefiting from AI and ML. Neobanks, being relatively new, often lack this robust foundation.

Regulatory compliance: Navigating the complex regulatory landscape is a nuanced process. Incumbent banks have years of experience and established relationships with regulators. Integrating AI within compliance frameworks requires a deep understanding of legal nuances, something that traditional banks are well-equipped to handle.

Customer trust: Despite the allure of neobanks, traditional banks still command significant trust and credibility. By enhancing their services through AI and ML, they reinforce this trust, attracting both new and returning customers. Neobanks, while innovative, often have to work harder to build this level of trust.

Strategic partnerships: Traditional banks have the means and the network to form alliances with tech companies, research institutions, and fintech startups. These partnerships fuel innovation and technological adoption, something that neobanks may find challenging to forge given their limited resources and connections.

Neobanks: The Challenges

Neobanks, though agile and innovative, face challenges that may hinder their ability to fully capitalise on AI and related technologies:

Limited resources: Neobanks often operate with constrained resources, both financially and in terms of data. This limitation can impede their ability to invest in AI technologies, which require substantial investment in research, development, and implementation.

Regulatory hurdles: While neobanks are often more agile, they may lack the experience and relationships to navigate complex regulatory requirements associated with implementing AI. This can slow down their adoption of these technologies.

Market perception: Neobanks are still building their reputation and trust among consumers. While they may be seen as innovative, they may not yet command the level of credibility required to fully leverage AI in enhancing customer experience and personalisation.

Conclusion: The Unstoppable Comeback

The convergence of AI, Machine Learning, and Generative AI is a transformative force, and incumbent banks are leading this change. Their position of strength, rooted in resources, compliance expertise, customer trust, and strategic partnerships, places them ahead of neobanks in leveraging these technologies.

AI is powering the comeback of traditional banks in ways that we cannot even imagine; it's an unstoppable force driven by strategic foresight and adaptability. At iBerotech, we understand the complexities of this transformation and can guide financial institutions through Spain's multifaceted regulatory landscape. Our expertise can empower your institution to leverage these technologies for strategic growth in this exciting era of financial innovation.


Over the years, we have gained a reputation on strategic compliance guidance.

At iBerotech, we harness regulatory expertise and leverage key strategic partnerships to empower foreign financial services companies in adroitly traversing Spain’s multifaceted regulatory landscape for strategic growth.


Sources

Frost, J. (2021). The rise of neobanks: A global analysis. International Journal of Bank Marketing, 39(2), 239-254. Retrieved from https://www.emerald.com/insight/content/doi/10.1108/IJBM-06-2020-0280/full/html

Arner, D. W., Barberis, J., & Buckley, R. P. (2016). The Evolution of Fintech: A New Post-Crisis Paradigm? Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2676553

Bughin, J., & Meehan, K. (2017). Artificial intelligence: The time to act is now. McKinsey Global Institute. Retrieved from https://www.mckinsey.com/industries/industrials-and-electronics/our-insights/artificial-intelligence-the-time-to-act-is-now

Gerbert, P., Mohr, J., & Spira, M. (2021). The Next Frontier in Digital and AI Transformations. Retrieved from https://www.bcg.com/publications/2019/next-frontier-digital-ai-transformations

Whitwell, J., & Cellan-Jones, R. (2019). Revolut whistleblower had raised concerns over compliance culture. BBC. Retrieved from https://www.bbc.com/news/technology-47751945

Makortoff, K. (2022). Monzo faces FCA investigation over anti-money laundering rules. The Guardian. Retrieved from https://www.theguardian.com/money/2021/jul/30/monzo-under-investigation-by-fca-over-anti-money-laundering-rules#:~:text=The%20Financial%20Conduct%20Authority%20(FCA,October%202018%20and%20April%202021.

Kumar, B., & Blechta, M. (2022). Future of Neobanks in GCC's Finance Industry. Retrieved from https://www.bcg.com/publications/2022/future-of-neobanks-in-gcc-finance-industry

René M. Stulz. (2022). Fintech, Bigtech, and the Future of Banks. Journal of Financial Services Research, 59(1), 5-32. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1111/jacf.12492

Gomber, P., Koch, J. A., & Siering, M. (2017). Digital Finance and FinTech: current research and future research directions. Journal of Business Economics, 87(5), 537-580. Retrieved from https://link.springer.com/article/10.1007/s11573-017-0852-x