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AI Returns Arrive Faster Than Expected

While many global companies struggle to turn their artificial intelligence investments into measurable profit, DBS — Southeast Asia’s largest bank — says the payoff has already begun. According to CEO Tan Su Shan, the bank’s AI strategy is no longer conceptual. It is delivering real, quantifiable financial impact.

“We’re past the stage of waiting. The value is already here, and it’s only accelerating,” Tan said during Singapore Fintech Week.

DBS expects AI-driven initiatives to boost revenue by more than 1 billion Singapore dollars in 2025, up from SG$750 million in 2024, marking one of the strongest AI monetization stories in global finance. These gains are being generated from an expanding portfolio of more than 370 AI use cases and 1,500 operational models built into the bank’s infrastructure.

A Decade-Long AI Foundation

DBS quietly began building its AI backbone over ten years ago — long before the recent boom in generative AI. This multi-year preparation gave the bank an important advantage: clean, well-structured data and robust internal analytics systems.

This foundation allowed DBS to adopt agentic AI and generative models faster than its competitors.
Agentic AI allows software to make independent decisions, plan tasks, and execute workflows with minimal human involvement — a capability the bank now uses in trading operations, risk management, compliance monitoring, and customer support.

Rather than experimenting with standalone pilots, DBS fully integrated AI into multiple divisions, from consumer banking to institutional banking to cybersecurity. The bank reports that these systems have improved decision-making speed, reduced operational friction, and increased automation at scale.

Institutional Banking Transformed

One of the strongest revenue drivers has been DBS’s institutional banking division. AI now collects, contextualizes, and analyzes client data in real time, allowing teams to deliver highly personalized solutions.

These enhancements, according to Tan, have made DBS’s institutional banking teams “faster, more resilient, and more adaptive,” directly contributing to stronger deposit growth compared to regional competitors.

The bank also recently launched DBS Joy, an AI-powered corporate banking assistant capable of answering complex, client-specific business queries around the clock. Joy leverages the bank’s internal knowledge base, transactional history, and financial models to provide tailored recommendations instantly.

The Banking Sector’s AI Reality Check

DBS’s success stands in stark contrast to broader industry challenges.
A widely cited MIT report released in July found that 95 percent of 300 publicly announced AI initiatives — many involving $30–$40 billion in generative AI spending — have yet to produce substantial returns.

But in banking, there are signs of change. JPMorgan Chase, which spends about $2 billion annually on AI, recently reported that its investment is now breaking even. CEO Jamie Dimon called this milestone “only the beginning,” signaling a shift in how major financial institutions are evaluating AI.

DBS, however, is already past the breakeven point.

The Next Phase: AI as a Personal Financial Advisor

DBS is now working toward a more ambitious goal: fully personalized AI-driven financial advisory.

The bank already deploys more than 100 AI algorithms analyzing customer behavior to create personalized nudges — from balance shortfall alerts to product suggestions, budgeting insights, and spending analysis.

In the future, Tan envisions DBS’s generative AI evolving into a trusted digital advisor for every customer. Retail clients may soon interact with smarter, more autonomous AI agents through the DBS mobile app, receiving tailored investment recommendations, improved financial planning, and predictive risk alerts.

Investing in People Alongside Technology

Despite the rapid automation, DBS emphasizes that AI is not a replacement for its workforce. Instead, it is reshaping how employees work.

This year, the bank launched several large-scale AI training and reskilling programs. It even introduced an AI-powered coaching platform to help staff learn new digital skills and adapt to evolving workflows.

“We’re not freezing hiring,” Tan said. “But we are reskilling — continuously. This is an ongoing transformation, not a one-time shift.”

The bank expects AI to automate repetitive and administrative tasks, allowing employees to spend more time building relationships and providing high-value client support.

A Bank Positioning Itself for the Future

DBS’s aggressive, long-term AI strategy sets it apart in an industry where many institutions remain cautious or uncertain about returns. With billions in potential efficiency gains, growing deposit inflows, increasing revenue from AI-driven solutions, and a clear roadmap for generative AI’s future, the bank is positioning itself as one of the region’s most advanced digital financial institutions.

For DBS, the AI question is no longer “if” or “when.”
It’s already happening — and it’s only the beginning.