Banks of every size are making balance sheet decisions on fragmented foundations, and the cost is measured in wasted time, conflicting numbers and missed strategic opportunities. That is the warning from ALMIS, which argues that asset and liability management (ALM) will only deliver real value once institutions fix both their data and their culture.
Drawing on more than two decades of experience across balance sheets ranging from £2bn to £2tn, ALMIS product strategy Julie King observes that the systems underpinning ALM rarely perform as well as they should.
The causes vary: poor data quality, ageing infrastructure, regulatory demands, vendor limitations, competing priorities or rigid organisational structures. In most cases, it is a mix of several. There is no quick fix, but ALMIS believes two practical changes can sharply reduce complexity and sharpen decision-making.
The first is establishing a single source of truth. According to ALMIS, effective ALM begins not with sophisticated modelling but with data. In many institutions, Capital, Liquidity, IRRBB and Financial Planning teams each source and manage their own data, gradually building separate assumptions, calculations and reporting processes. The outcome is a cycle of reconciliations that adds little value. Many practitioners will recognise the awkward ALCO meeting where different teams present different versions of the balance sheet, prompting the inevitable question: “Which number is correct?”
ALMIS argues that a shared data strategy shifts the conversation. When ALM, Risk and Finance work from common data, the focus moves from validating figures to understanding what they mean for the business.
The second change is harder because it is cultural. Many institutions still treat capital, liquidity, interest rate risk and financial planning as distinct disciplines. Each team may perform well, yet decisions are often made within functional boundaries rather than across the enterprise. ALMIS points out that bringing Finance into the ALM conversation exposes the real trade-offs, such as whether a high-yielding product remains attractive once capital and liquidity costs are included, or whether encouraging deposit growth makes sense when there are few profitable ways to deploy that funding. Because these factors are interconnected, considering them separately tends to produce sub-optimal outcomes.
ALMIS also cautions against ALM becoming an exercise in measurement alone. Tracking ratios, liquidity metrics and rate sensitivities matters, but the goal is to use that insight to drive strategy. A common data model combined with ALM and Finance expertise gives institutions a holistic view of the balance sheet and better allocation of scarce resources.
Technology plays a role, ALMIS notes, but it is not a cure on its own. The most successful institutions are not necessarily those with the biggest budgets, but those willing to align data, dismantle silos and share ownership of balance sheet decisions. Technology enables transformation, while people drive it.
ALMIS closes with a challenge for leaders: do your teams use the same underlying data, how much time goes on reconciling rather than analysing, and are strategic decisions based on a fully integrated view? Any discomfort with the answers may signal an opportunity hiding in plain sight.
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