DBS delivered record first quarter 2026 total income of SGD 5.95 billion (about $4.4 billion). Tan Su Shan, chief executive officer of DBS, described conditions where "the short-term future doesn't look very clear," highlighting the importance of resilience, a strong balance sheet and a growing base of recurring income in navigating volatility. Net profit rose 1% year-on-year to SGD 2.93 billion (about $2.2 billion), while total income increased 1%. Return on equity was 17.0% and return on tangible equity was 18.7%. Gross fee income reached SGD 1.71 billion (about $1.3 billion), while customer-driven non-interest income rose to SGD 2.07 billion (about $1.5 billion), supported by sustained activity across wealth, treasury and transaction services. The main pressure point was interest income. The Singapore Overnight Rate Average (SORA) fell from 2.54% to 1.07%, compressing lending margins and leading to a 5% decline in net interest income to SGD 3.49 billion (about $2.6 billion). Chng Sok Hui, chief financial officer of DBS, said that "our strong deposit growth and hedging mitigated the headwinds," highlighting how balance sheet positioning cushioned the impact. Fee income, treasury customer sales and markets trading income supported overall earnings, while net interest income was "little changed on a day-adjusted basis." Asset quality remained stable, with new problem loan formation at the low end of the bank's range and more than offset by repayments. CASA growth anchors deposit momentum Total deposits rose to SGD 630 billion (about $466 billion), driven by inflows into current and savings accounts (CASA) from corporate and retail customers, reflecting active day-to-day usage. Tan emphasised capturing operating balances, with a focus on expanding low-cost CASA deposits rather than competing on pricing. This approach prioritises long-term relationships over short-term funding gains and creates a stable base for future activity. Deposit growth reflects sustained efforts to build operating account relationships and expand cash management mandates. Tan noted that momentum "speaks to the plumbing work that we've done over the years," highlighting how the bank has embedded itself in clients' transaction flows and attracted new-to-bank relationships. Loan growth, in contrast, remained more measured, reflecting cautious business sentiment and a more selective approach to borrowing. Deposits therefore anchor both funding and client flows, forming the base for transaction and fee generation. Wealth and transactions expand repeatable income Once customers are onboarded, their activity translates into repeatable income, which became the primary driver of earnings as interest income declined. Fee income expanded further, led by wealth management, alongside growth in transaction services and treasury-related activity. Chng explained that fee income and treasury customer sales are driven by demand for financial solutions, including payments, foreign exchange and hedging, with income generated through repeated engagement rather than one-off transactions. Tan highlighted that wealth management growth was broad-based, supported by strong banker activity and new-to-bank asset inflows, indicating that expansion is coming from both deeper relationships and new client acquisition. She described how these relationships evolve, noting that onboarding new clients leads to cash management, payments and investment flows that build into a "snowballing of recurring fee." Each additional relationship adds multiple income streams that accumulate over time, helping offset the impact of margin compression as lending spreads narrow. Institutional flows scale income generation The same model extends across corporate and institutional banking, where larger client flows generate higher volumes of transactions. Tan pointed to continued traction in sectors such as technology, media and telecommunications (TMT) and financial institutions, supported by stronger client activity and continued sector focus. In the TMT sector, revenue rose 14%, with fee income increasing 27%, supported by stronger client activity and deeper industry penetration. Tan highlighted continued focus on areas such as semiconductors, data centres and emerging artificial intelligence applications, where the bank is expanding coverage and identifying new industry winners. As coverage deepens, the bank is able to take on more complex roles, including structuring and syndicated loans, adding advisory and arrangement income on top of transaction flows. Risk discipline preserves earnings capacity While client flows drive income, resilience depends on protecting that income from credit losses. Asset quality remained stable, with non-performing assets declining and the non-performing loan ratio holding at 1.0%. Chng noted that new problem loan formation was limited and offset by repayments and write-offs, indicating that risk is being managed within expected parameters. Tan emphasised that resilience is built through continuous stress testing, with the bank repeatedly assessing scenarios involving higher oil prices and currency volatility to identify risks before they materialise. She also pointed to earlier decisions to reduce exposure to higher-risk segments, including unsecured consumer lending and selected small business portfolios, which have strengthened the balance sheet over time. AI expands capacity and strengthens control The ability to sustain this model at scale increasingly depends on how efficiently the bank can process, execute and control growing volumes of client activity. Artificial intelligence (AI) therefore functions as an enabling layer rather than a standalone capability. Tan described a "constant focus on innovation, AI, agentic AI" as part of how the bank underpins both growth and resilience. DBS has evolved from deterministic models to generative AI, and has begun developing an agent control plane to support enterprise use cases across areas such as technology and operations. These systems are embedded across workflows such as credit memo preparation, customer servicing and selected operational and technology use cases. Tan noted that AI "really crunches down the time-to-market for development and coding" while reducing human error, allowing staff to handle higher volumes of work with greater consistency. This expands operational capacity without requiring proportional increases in resources, directly supporting the growth of transaction-driven income. When asked about developments such as Anthropic's Mythos model under Project Glasswing, which shows how artificial intelligence can identify and combine software vulnerabilities at speed, Tan said these tools do not introduce entirely new forms of attack but "amplify the risk from both a speed perspective… and from a volume perspective," accelerating how vulnerabilities are identified and exploited. She added that such systems can "chain together a few vulnerabilities to broaden the attack path," reducing the time and effort required to execute attacks. The same capabilities can also be applied defensively, with banks using artificial intelligence to detect vulnerabilities faster, strengthen internal controls and reduce the risk of new vulnerabilities arising from higher digital activity. Tan emphasised the need for strong internal hygiene, timely patching and what she described as "layer defence to prevent chaining," reinforcing the need to "protect yourself faster than the attacker." Activity-based income sustains performance through uncertainty Interest rates are expected to remain around current levels, suggesting that margin expansion will not be a primary driver of earnings, while geopolitical and macroeconomic uncertainty continues to shape the operating environment. Tan described a "relentless focus on growing customers, deepening wallet share and focusing on recurring fee, while building a fortress balance sheet and maintaining cost discipline," highlighting the continued emphasis on both income generation and resilience. This reflects a deliberate balance. Client flows provide the engine for growth, while strong capital, liquidity and risk discipline ensure that the bank can absorb shocks and continue supporting customers. Tan noted that the bank is "ready for the worst-case scenario, but we hope for the best-case scenario," capturing an approach that combines preparedness with the ability to participate in upside. Performance will increasingly depend on the depth of client engagement and the bank's ability to intermediate those flows at scale, reinforcing a model where earnings are driven more by client flows and connectivity than by lending spreads as DBS navigates a more uncertain and lower-rate environment.
