In these digital times, customer trust needs to be high on the priority list of firms. Banks and digital financial services are transitioning into dependence on network effects. An increase in the number of users results in improved value in transfers and payments. On the other hand, once users feel that their data, money, or privacy is at risk, the network effects are quickly reversed and become negative. Revolut, a leading FinTech bank, faced a drastic increase in APP scams compared to its competition in the UK (Gani, 2024). The aforementioned setbacks lead to eroded trust of customers as their security confidence in the bank decreases, potentially leading to either closing their accounts or moving to competitors. Additionally, a negative feedback loop is bound to happen once a certain number of customers leave due to the reduced attractiveness of using the financial service.
From my point of view, cybersecurity and data protection are unforeseen network effects currently occurring in the financial industry. The network effect notion tells us that as users attract users, it is critical to mention that insecurity will push them away. It only takes one data breach to cancel years of digital growth; banks must view security as a growth strategy, not another cost. Companies should curate and give a platform for cybersecurity to maintain their customer base (Muhly et al., 2025). In the era of AI, where attacks are becoming quicker and more dangerous, banks can leverage this by marketing their superior security as a USP, contributing to its positive network effects.
While AI is making attacks more prominent, it has the power to protect through anomaly detections, better decision-making, and trend prediction (Kovačević et al., 2024). From my perspective, the first financial service incorporating AI in its cybersecurity solutions has a significant competitive advantage in continuing its network effects.
References:
Gani, A. S. (2024, September 11). Revolut Grapples With Surge in Scam Complaints That Threatens Its Ambitions. Bloomberg.com; Bloomberg. https://www.bloomberg.com/news/features/2024-09-11/revolut-grapples-with-surge-in-scams-that-threatens-its-ambitions?embedded-checkout=true
Kovačević, A., Radenković, S., & Nikolić, D. (2024). Artificial intelligence and cybersecurity in banking sector: opportunities and risks.
Muhly, F., Jordan, J., Cialdini, R. B., & Neidert, G. P. M. (2025, June 24). Create a Company Culture That Takes Cybersecurity Seriously. Harvard Business Review. https://hbr.org/2025/06/create-a-company-culture-that-takes-cybersecurity-seriously
Scherbina, A. (2024, May 3). How much do US businesses lose due to malicious cyber activity? The Hill; The Hill. https://thehill.com/opinion/cybersecurity/4641199-cyberattack-businesses-money-loss-malicious-cybersecurity/
Dear Matan,
I found your blog post to be quite interesting! I have never thought that network effects could be so present in our world. However, I need to ask you that network effects also is supposed to benefit the users and I would be curious to see how users of Revolut or other banks/financial services users benefit from having more and more people on using the same one.
Let me know what you think!
Hi Matan, interesting post. I like how you frame security as a part of the network effect itself. The Revolut example is interesting in that it shows how quickly trust issues can push users away. On the AI point, I see it less as who is first but more as a steady learning game. If security is so important for growth, it makes sense for banks to actually share their work. Banks could maybe share threat tips, and if one sees a new phishing tactic today and shares it, others can already block it? That would lift trust across the industry and make it harder for attackers to use the same tricks.
Piers