As Asia emerges as a powerhouse in global finance, our region finds itself at the crossroads of innovation and responsibility. The fast rise of AI, data, and digital tools offers huge benefits, but how we share those benefits will shape the future of finance across our region.

AI gives us powerful tools for personalization, automation, and smarter decision-making. But without a strong focus on fairness, it could widen the gap. To keep growing in the right way, financial institutions in Asia Pacific need to see digital transformation not just as a tech upgrade, but as a chance to create value for everyone. That means investing in strong data systems, flexible cloud platforms, and clear, responsible rules around how AI is used.

This also has big implications for the future of work. As automation grows, we must reskill teams, redesign roles, and make sure people grow alongside technology and not get left behind.

We need to start thinking of platforms as shared infrastructure, partnerships as a way to drive impact, and performance as something that includes everyone. The future of finance isn’t just smart and fast, it must also be fair.

Some years ago, when I worked in Citibank, Citibank then group CEO Mr. Michael Corbat said, “We see ourselves as a technology company with a banking license”.

Our Singapore DBS bank’s group CEO (2009-2025) Mr. Piyush Gupta said similar thing when he answered the question during interview why DBS was increasingly recognized as a global leader in digital transformation. He said, “We act less like a bank and more like a tech company”.

NVIDIA’s CEO Jensen Huang at the recent Consumer Electronics Show (CES) in Las Vegas this Jan said “In a lot of ways, the IT department of every company is going to be the HR department of AI agents in the future.” in his keynote.

I can’t agree any more on their insights. And personally, I believe not only banks, but every company might be an IT company, more or less, in the AI era. CIOs, CTOs, CDOs, CISOs, etc. would be playing the pivot enabling roles to facilitate every line of business in the company to unlock the potential value of emerging technology like AI in the safe, sound, secure and also compliant manner.

I am eager to see all these trends and insights about AI bringing to every industry, especially our financial industry, in the upcoming amazing IDC 20th Asian Financial Services Congress & Awards on 17 Jul at Singapore MBS. Will you join me?

As GenAI technologies rapidly evolve, we are witnessing a fundamental shift in the nature of IT work. Tasks once considered core to software engineering—like writing boilerplate code, building simple interfaces, or querying databases—are increasingly automated by tools like GitHub Copilot and low-code platforms. This has major implications for both hiring and talent development.

New IT hires can no longer be defined by general programming ability alone. Instead, two emerging profiles are in highest demand: GenAI-deep technologists who can fine-tune models, build pipelines, and manage LLMOps; and high-agility learners with strong analytical foundations who can adapt quickly to new AI tools and frameworks.

Equally important, existing IT professionals must evolve. The real value now lies not in repetitive tasks, but in working across disciplines—translating domain needs into AI applications, collaborating with non-technical teams, and managing AI-driven workflows and risks. This calls for investment in interdisciplinary fluency, not just technical upskilling or refreshing.

Looking ahead, most AI-driven work will be GenAI + human-in-the-loop—where human oversight, contextual understanding, and ethical judgment remain critical. Talent strategies must align with this hybrid future, reskilling workers to effectively guide, correct, and collaborate with intelligent systems.

As Southeast Asia’s financial ecosystem rapidly evolves, banks are moving beyond traditional lending—powered by Artificial Intelligence (AI) and Generative AI (GenAI). The year 2025 marks a pivotal shift where AI is no longer a back-office experiment but a frontline enabler of efficiency, compliance, and customer trust. For SEA’s dynamic banking sector, the question isn’t whether to adopt AI—but how fast and how ethically.

AI as a Strategic Imperative:

Banks in the region are deploying AI to reimagine credit decisioning, streamline operations, and expand financial inclusion. Advanced credit scoring models now go beyond bureau data—leveraging alternative data such as utility payments, mobile usage, and behavioural insights to assess borrower risk. This is a game-changer for unbanked and underbanked populations in SEA, unlocking new growth avenues.

GenAI, meanwhile, is automating loan documentation, underwriting summaries, and even generating personalized loan recommendations in local languages. Voice bots and AI-powered chat assistants are now engaging customers 24/7, ensuring faster responses and better transparency—especially for digital-first borrowers in fast-growing economies like Indonesia, Vietnam, and the Philippines.

Proactive Risk and Compliance:

AI’s real-time fraud detection and predictive analytics are helping banks identify delinquencies before they occur—allowing for early intervention strategies and reducing non-performing loan (NPL) rates. Moreover, automated compliance tools are simplifying regulatory adherence in complex, multi-jurisdictional environments, such as Malaysia and Singapore, where rules are evolving rapidly.

Responsible AI: A Growing Mandate

In SEA, regulators like the Monetary Authority of Singapore (MAS) are already driving responsible AI adoption through frameworks like FEAT (Fairness, Ethics, Accountability, Transparency). This signals a regional push for explainable, auditable, and fair AI—a trend banks cannot ignore.

The 2025 Mandate:

To succeed in 2025 and beyond, banks must:

• Build AI systems that integrate with core platforms and scale across markets.

• Focus on customer education and transparency around AI-driven decisions.

• Prioritize ethical AI to win regulatory approval and consumer trust.

While AI dominates boardroom agendas across Asia Pacific, there’s a growing concern beneath the surface—networks aren’t ready.

Expereo and IDC’s Enterprise Horizons 2025 report reveals that 94% of global tech leaders say network limitations are holding back AI and data initiatives. APAC leads the concern, with 23% of businesses citing poor internet connectivity as a barrier to AI deployment—the highest globally.

AI demands speed, visibility, and scale. But half of companies in APAC still rely on outdated networks, and 93% of those that didn’t upgrade in the past year have suffered real financial losses due to performance failures.

To ensure AI delivers impact, CIOs in APAC must:

Invest in AI-ready connectivity

Guarantee high-performance application responsiveness

Gain end-to-end visibility across distributed infrastructure

By strengthening their networks, enterprises can unlock AI’s full potential—driving innovation, productivity, and a competitive edge across the region.

Expereo is uniquely positioned to help. With global reach and deep regional expertise, our expereoOne platform delivers intelligent internet, SD-WAN, and SASE—built for performance, visibility, and scale.

We understand what it takes to support large-scale AI initiatives. That’s why leading enterprises trust Expereo to future-proof their infrastructure and turn ambition into action.

Go faster to the future with an AI-ready network. Download Enterprise Horizons 2025 report and together, we can overcome the challenges and seize the opportunities on the horizon. Enterprise Horizons – Expereo

As Gen AI gains momentum across financial services, CXOs must cut through the hype to separate signal from noise. A common myth is that Gen AI will displace large swaths of the workforce. In truth, its greatest value lies in augmenting human intelligence—empowering advisors, underwriters, and analysts with faster insights, automated summaries, and decision support.

Another misconception is that Gen AI is turnkey. CXOs must recognize it demands more than just data—it requires robust governance, ethical guardrails, and deep domain integration. Without this, risks like model hallucination, bias, or regulatory misalignment can outweigh benefits.

The real opportunity? Driving measurable outcomes—accelerated onboarding, enhanced fraud detection, and intelligent compliance. Leading firms are embedding Gen AI into specific workflows, not as standalone tools, but as force multipliers aligned with business objectives.

For technology and business leaders alike, success will come not from chasing novelty, but from anchoring Gen AI initiatives in strategy, stewardship, and scale.

In today’s highly regulated, fast-evolving financial landscape, the adoption of Generative AI is no longer a question of “if” — but “how responsibly and at what scale.” For the BFSI sector, the opportunity is immense: AI promises new efficiencies in fraud detection, credit risk analysis, customer engagement, and regulatory compliance. Yet, realizing this potential requires rethinking infrastructure from the ground up — not just for performance, but for trust.

BFSI organizations operate in one of the most compliance-intensive environments. As AI models grow more complex and data-hungry, issues around data governance, sovereignty, auditability, and secure model access become mission-critical. The infrastructure that supports GenAI must be purpose-built to meet these demands, not retrofitted as an afterthought.

This means designing environments where compliance is embedded into the architecture, not layered on top. It calls for infrastructure that supports private, hybrid deployments, robust role-based access, policy enforcement, and the ability to govern every aspect of the AI lifecycle—from data ingestion to inference. Just as financial institutions have long relied on core systems built for trust and resilience, GenAI infrastructure must meet the same bar.

Equally important is intelligence by design. This means performance at scale: GPU-accelerated systems that can train, fine-tune, and serve large models without latency bottlenecks. It also means flexibility—supporting a diverse range of AI workloads, from foundational models to domain-specific agents—all while remaining compliant with local and global regulations.

In an increasingly multi-polar world, BFSI firms must maintain control of their infrastructure while leveraging global innovation. The future of GenAI in financial services will not be powered by a single platform or provider—but by secure, sovereign, and scalable infrastructures that deliver on the dual promise of intelligence and integrity.

Rethinking AI infrastructure is no longer optional. It is the foundation upon which responsible transformation will be built—and sustained.