DBS reported net profit of SGD 11.0 billion (about $8.1 billion) for financial year 2025 on total income of SGD 22.9 billion (about $16.9 billion) while benchmark interest rates declined materially across the year. Average Singapore Overnight Rate Average (SORA) and Hong Kong Interbank Offered Rate (HIBOR) each fell by almost two percentage points, compressing lending spreads even as activity levels across deposits and fee-based businesses expanded. The results therefore did not primarily reflect expansion in credit demand. Loan growth was moderate at about 6% while deposits increased by SGD 64 billion (about $47.3 billion), shifting balance sheet structure towards liquidity deployment rather than loan extension. Net interest income remained stable at SGD 14.5 billion (about $10.7 billion) because funding growth and hedging offset margin compression. Net interest margin declined to 1.93% in the fourth quarter while customer-driven non-interest income reached SGD 7.04 billion (about $5.2 billion), combining fee income and treasury customer sales. Fee income increased 18% to SGD 4.9 billion (about $3.6 billion), led by wealth distribution, while treasury customer sales rose 14% and trading income increased 49%. Earnings contribution therefore came from different mechanisms: retail funding inflows, advisory distribution, transaction services and treasury flows. At the same time allowances rose following classification of a long-monitored real estate exposure as non-performing, and tax expense increased by about SGD 400 million (about $295 million) due to implementation of the global minimum tax. Profit before tax still reached SGD 13.1 billion (about $9.7 billion) with return on equity at 16.2%. Allowances increased to SGD 791 million (about $585 million) mainly from a previously watch-listed real estate exposure that was subjectively classified as non-performing, while general allowances previously set aside were written back. It therefore raises a question: whether the bank’s earnings are now carried less by lending spreads and more by flows — deposits, distribution, payments and market activity — and how retail behaviour, renminbi (RMB) settlement infrastructure and artificial intelligence (AI) capabilities connect to that change. Tan Su Shan, Chief Executive Officer, and Chng Sok Hui, Chief Financial Officer, addressed these dynamics across segments including retail, wealth, institutional banking and treasury. Tan explained that deposit growth outpaced loan growth, leading surplus liquidity to be deployed into high quality liquid assets rather than credit expansion. Income therefore came from volume and activity rather than spread expansion. Retail funding, wealth distribution and changing customer behaviour Tan described the year’s operating environment as one in which deposit gathering mattered more than credit expansion. Deposits grew faster than loans and surplus liquidity was deployed into high-quality liquid assets, supporting income even as margins narrowed. Retail inflows contributed materially to this shift, including migration of funds back from treasury bills into deposits. Current and savings accounts formed more than two-thirds of the increase, including seasonal retail inflows and funds moving back from treasury bills into deposits. Liquidity coverage ratio stood at 155% and net stable funding ratio at 117%. Retail therefore functioned less as a lending engine and more as a funding anchor. The bank observed strong current and savings account growth in both Singapore-dollar and foreign-currency balances. Over two-thirds of deposit growth came from current and savings accounts rather than fixed deposits. Wealth distribution became closely linked to this funding base. Assets under management increased to SGD 488 billion (about $360 billion) and net new money inflows reached SGD 39 billion (about $28.8 billion). Investment product and bancassurance sales offset the decline in net interest margins, indicating that customer relationships generated income through advisory activity rather than borrowing demand. Customers shifted from saving behaviour toward investment participation, reflected in stronger investment product and bancassurance sales while borrowing demand remained moderate. Tan described a “wealth continuum” in which customers progress from Treasures to Treasures Private Client to Private Bank. This progression allows deposit relationships to evolve into advisory and distribution relationships rather than purely lending relationships. The bank also observed uneven economic conditions across customer segments. Tan referred to a K-shaped environment where stronger customers expanded while some small and medium enterprises remained under pressure. The bank therefore increased monitoring and selectively reduced risk in unsecured consumer lending while continuing to support small and medium-sized enterprises (SMEs) through restructuring and early engagement. Some SME exposures required closer monitoring and selective de-risking, particularly in unsecured consumer lending segments. Retail behaviour therefore changed in two ways: balances accumulated rather than being borrowed, and advisory activity substituted for interest income. Retail became a source of liquidity and distribution rather than credit expansion. Renminbi clearing and treasury flow deepening The bank was designated a RMB clearing bank in Singapore in December 2025. Tan explained the role as linked to diversification of settlement currencies rather than displacement of the United States dollar, which still accounts for the majority of global trade financing. The clearing role is expected to generate mandates and operating balances as clients settle trade and investment flows in RMB. Rather than replacing existing flows, it deepens relationships by embedding settlement activity within the bank’s transaction infrastructure. This connects directly to treasury customer sales, which rose alongside wealth and corporate activity. Currency diversification by clients creates additional hedging and settlement requirements that translate into treasury flow income. Tan described increasing intra-regional trade — particularly between North Asia and ASEAN and between Asia and the Gulf Cooperation Council — as supporting demand for non-dollar settlement. RMB therefore functions as an additional operating currency rather than a substitute reserve currency. The clearing designation also aligns with the bank’s strong deposit base. Operating balances linked to settlement activities can reinforce liquidity growth, which in turn supports income through liquidity deployment rather than loan expansion. The role therefore links transaction banking and treasury: settlement infrastructure produces balances, balances produce flows and flows generate hedging and advisory income. Responding to questions on trade flows, Head of Institutional Banking Group Han Kwee Juan described financing linked to AI infrastructure, including short-dated supplier financing connected to data centre construction and semiconductor supply chains. AI and operating capacity Tan described AI primarily as an operating model transformation rather than a discrete revenue product. The bank implemented AI tools in credit memo preparation, customer service responses and know-your-customer processes. More than 60% of staff actively use internal generative AI (Gen AI) tools. Rather than immediate cost reduction, the bank expects capacity expansion: processes that previously required months can now be completed in weeks. Chng noted that traditional machine-learning models allowed value measurement through A/B testing of revenue growth or loss reduction. With Gen AI embedded broadly across operations, isolating direct financial contribution becomes more difficult because improvements manifest as productivity and speed rather than separate income lines. AI affects multiple businesses simultaneously — retail servicing, wealth advisory, credit underwriting and institutional processing — reinforcing flow-based earnings rather than directly replacing labour. The bank described this as ecosystem financing, where lending follows supply networks rather than individual borrowers. Staff roles are being redesigned so employees shift toward higher-order activities while automated systems handle routine processes. The bank described this as augmenting capacity rather than reducing headcount. AI therefore supports the structural shift: faster processing enables higher transaction volumes and advisory interactions without proportional cost increases. Institutional banking, AI investment cycle and trade outside the United States Institutional Banking Group activity reflected expansion in technology investment and regional trade patterns. Tan referred to “trade outside the US” (TOTUS) growth, including intra-Asia supply chains and flows between Asia and the Middle East. Financing demand arose from data centre construction, semiconductor investment and ecosystem financing linked to AI infrastructure. These loans are often short-dated and tied to supplier networks rather than long-term capital expenditure lending. Investment banking also benefited from revival of capital market activity in Hong Kong and Singapore, increasing fee income. The bank reported growth in loan structuring mandates and event-driven financing including mergers and acquisitions. The bank also supports “queen bee” programmes where large corporations expand regionally with their supplier ecosystems. This produces network lending rather than individual borrower lending. These activities reflected ecosystem financing where supply chains rather than individual borrowers drive lending demand. Trade diversification therefore produces transaction flows rather than traditional trade finance growth. The bank finances operating companies generating cash flows rather than speculative market positions, particularly in Indonesia. Institutional banking thus mirrors retail behaviour: income derives from activity and connectivity rather than balance sheet expansion. Fourth quarter developments and 2026 outlook Fourth-quarter profit declined sequentially due to seasonal activity patterns and portfolio rebalancing. The bank also recognised a non-performing loan from a previously monitored real estate exposure. Allowance coverage remained at 130% or 197% including collateral. The fourth quarter also included portfolio rebalancing after stronger trading earlier in the year and seasonal reduction in client activity, while expenses declined partly due to integration synergies rolling off dual roles. The bank expects total income in 2026 to remain around 2025 levels assuming a SORA of about 1.25% and further rate cuts. Wealth management income is expected to grow at mid-teens levels while overall non-interest income should grow in high single digits. Loan growth is projected at mid-single digits while deposit growth remains strong. Some general allowances may be written back depending on macroeconomic conditions. Net profit is expected to be slightly below 2025 levels given the rate environment assumptions. Tan expects customers to seek stability during volatility, increasing diversification across currencies, markets and supply chains. The bank positions itself as a stable intermediary in that environment. A flow-driven bank The year’s performance suggests the bank is becoming less dependent on interest margins and more dependent on movement: liquidity flows, advisory distribution, settlement infrastructure and transaction activity. Retail deposits funded treasury deployment, wealth advisory generated fees, RMB clearing deepened operating balances and institutional banking followed supply chain networks rather than credit cycles. AI underpins this structure by increasing processing capacity rather than replacing revenue sources, allowing activity growth without proportional cost growth. The earnings model therefore shifts from lending spreads to participation in financial movement. Credit remains important but no longer dominates how income is generated. The bank’s strategy now depends on connectivity — between customers, currencies and markets — more than on balance sheet expansion.
