Around this time two years ago I published a blog announcing my case study report “DBS Bank’s Billion-Dollar AI Banking Dream”. It detailed how this Singaporean bank built and directed its AI capabilities to benefit its customers, business lines, employees, and shareholders. The total economic value the bank had derived that year (i.e. end of FY 2023) stood at S$370 million. A year before that, then CIO Jimmy Ng stated, “We aspire to achieve S$1 billion in the next five years (see page 34, CIO Statement, DBS Bank’s Annual Report, 2022). That moment has come early…

In a recent interview published by Business Times, DBS Bank’s chief data and transformation officer Nimish Panchmatia announced that the bank hit a record $1 billion in economic value from artificial intelligence (AI) initiatives in 2025, underscoring the accelerating impact of AI across the bank’s operations.

How DBS Measures AI Impact

Unlike vague projections, DBS uses a rigorous benchmarking approach to quantify AI-driven value. Customer outcomes from AI-powered solutions are compared against control groups, ensuring that the S$1 billion figure reflects tangible, measurable benefits rather than theoretical estimates.

In plain accounting terms, as I described in my case study 2 years ago, that value can be traced to three general areas that combine to produce banking profit: increased revenue, cost savings, and risk avoidance. Since the revenue is generated through various lines of business (LOB), grouped under consumer and institutional banking, the bank keeps developing and deploying AI use cases custom-built for each LOB to boost their interest income, fees, and commissions (the three main sources of income). Likewise, in terms of costs and risk-weighted losses, a deliberate focus on specific AI use cases that offload costs and avoid risks help to produce tangible economic value.

Moreover, DBS Bank tracks economic benefits accrued by customers, manifested through their financial wellness as a result of growing their savings, reducing debt, and increasing investments. In terms of soft metrics, the bank looks at customer and employee satisfaction and engagement attributable to their use of AI-powered tools and services.

The Next Frontier: Agentic AI

While generative AI models like ChatGPT and Google Gemini have dominated headlines, DBS is moving toward the next frontier: agentic AI. These systems go beyond text generation—they can reason, plan, and execute tasks autonomously with minimal human intervention.

Forrester’s take on Agentic AI is that it will reshape enterprises and usher new business and operating models that might disrupt entire industries (stay tuned to my upcoming research on fully autonomous, AI-powered telecoms).

Why This Matters

DBS’s S$1 billion milestone isn’t just a number—it’s a signal of how AI can transform banking at scale. As AI capabilities mature and scale, this could lead to disruptive banking services model where AI is seamlessly integrated with all internal operations and external customer-facing platforms, producing significant economic benefits at substantially lower cost.