Oradian has published a deep dive on Fintech News Network about one of the most critical challenges facing digital banks across Southeast Asia: the gap between AI ambition and infrastructure reality. Read the full article to discover how this shift is happening. Here’s what we found.
The AI paradox
Southeast Asia’s digital banking growth is explosive. Transaction volumes in payments networks like InstaPay, PESONet, and QRIS are hitting billions annually, and investment in AI is surging. Yet most AI initiatives at digital banks across the region are stalling out.
The models work perfectly in testing, yet they hit production and break. The problem isn’t ambition or funding. It’s what’s underneath.
Why legacy systems are becoming the real bottleneck
Most digital banks in Southeast Asia grew by prioritising speed. Launch fast, refine later: that approach worked brilliantly in the early years. But as volumes scaled, something happened. Complexity accumulated silently underneath.
Systems evolved into silos. Data fragmented across multiple versions of truth. Infrastructure that was never designed for real-time decisioning now needs to support intelligent operations at scale. Banks are now spending up to 70% of their IT budgets just maintaining legacy systems, leaving little room for innovation.
When AI enters this environment, it doesn’t fail gracefully. It exposes every weakness in the foundation.
Regulators are raising the stakes
At the same time, regulatory expectations have shifted dramatically. Authorities across Southeast Asia now treat system failures as material financial risks, not operational inconveniences.
Recent enforcement actions make this unmistakable:
- Banks experiencing disruptions face higher capital requirements
- Administrative penalties are in the millions
- Expansion is restricted until systems prove reliable
The message is clear: speed without resilience is no longer acceptable.
The solution: Core banking modernisation
This is where the conversation has shifted. It’s no longer “How do we deploy AI faster?” but “How do we build systems that institutions and regulators can trust?”
The answer requires modernising the core by moving to cloud-native, API-first platforms that:
- Provide a single source of truth for data
- Enable real-time decisioning instead of batch processing
- Embed compliance into operations
- Give institutions the auditability regulators now demand
When this foundation exists, everything changes. AI models work with clean data. Innovation happens within guardrails. Growth doesn’t compromise reliability.
Read the full analysis
We’ve published a comprehensive breakdown of how this shift is happening, what’s driving it, and why the institutions that get ahead of it now will have a significant advantage as Southeast Asia’s digital banking market grows towards £88 billion by 2034.
Read the full article on Fintech News Network
The article covers:
- Why “pilot purgatory” is the real obstacle to AI adoption
- The cost of fragmented infrastructure and the financial impact
- How regulators are reshaping competitive dynamics
- What modern core banking looks like in practice
- Why the next phase will favour resilience over raw speed
Related resource
For a deeper dive into how AI transforms digital banking operations, download our latest whitepaper:
Digital bank guide: AI and artificial intelligence in 2026
The future of banking in Southeast Asia isn’t about who can move fastest. It’s about who can move sustainably and intelligently.
