Which KPIs treasury teams track in 2026

Corporate treasury now operates in a far more complex environment than just a few years ago. It is no longer only responsible for securing liquidity and steering funding processes, but increasingly also for making risks visible at an early stage, supporting governance requirements and providing robust decision-making input for management. Volatility in financial markets, geopolitical uncertainty, rising regulatory expectations and technological change all raise the bar for transparency, responsiveness and management quality. These developments are also reflected in the KPMG Treasury Survey, which highlights treasury’s growing strategic role and the increasing importance of data-driven management and decision support.

Against this backdrop, it is worth taking a critical look at commonly used treasury KPIs. In practice, the challenge is less a lack of metrics than KPI sets that have evolved over time and offer only limited management value. The survey findings likewise show that while many organizations collect KPIs, they are often not consistently aligned with decision-relevant management variables, governance requirements or key risk questions.

A treasury function that truly supports decision-making therefore does not rely on as many KPIs as possible, but on a clearly structured and decision-oriented KPI set. For treasury leaders, the central question is which KPIs actually drive management and how they can be used in a way that turns transparency into concrete actions.

The following section shows how such a KPI set can be structured along key steering dimensions and which metrics are particularly relevant for treasury in 2026.

The increasing demands placed on Corporate Treasury make it clear that KPIs today must deliver far more than simple transparency. They should not be reported in isolation but rather understood as part of an overarching management framework that supports decision-making, highlights risks at an early stage and reflects governance requirements.

The objective is therefore not to expand existing KPI sets but to classify them conceptually: which metrics actually contribute to effective steering and which remain purely descriptive? The focus is thus on how KPIs can be assessed systematically based on their ability to drive decisions.

In practice, this evaluation typically revolves around a few key questions: 

• Does the KPI support concrete management decisions?
• Does it capture relevant risk and governance dimensions?
• And is it based on reliable, consistent and timely available data? 

KPIs that meet these criteria provide a direct contribution to steering, while others often remain purely descriptive.

A robust KPI set is therefore characterized by clearly linking metrics to specific decision objectives, basing them on a stable data foundation and ensuring they can be interpreted consistently across entities, time periods and scenarios. This conceptual classification forms the basis for selecting and further developing KPIs in treasury.

The KPI selection below addresses key management questions in corporate treasury and is aligned with the findings of the KPMG Treasury Survey, which highlights current priorities and management needs in practice. The focus is on a KPI set structured along core management dimensions, embedding individual metrics in a consistent overall framework and explicitly orienting them toward decision-making.

What ultimately matters is not the individual metric but its integration into a coherent KPI set with a clear conceptual logic, transparent definitions and well-defined benchmarks and target values.

3.1 Liquidity Planning & Forecasting
Liquidity Planning & Forecasting is one of the central management areas in corporate treasury. The quality of liquidity planning is a key factor in ensuring that short-term solvency, medium- to long-term financing capacity and risk-oriented management decisions are built on a solid foundation. Particularly in an environment of heightened market volatility and uncertain refinancing conditions, it is no longer sufficient to simply produce cash flow forecasts on a regular basis. What matters is whether their reliability is systematically measured, challenged and used to inform concrete decisions. 

A key KPI in this context is Cash Flow Forecast Accuracy. It measures the deviation between forecasted and actual cash flows. This metric should not only be analyzed on an aggregated level, but also broken down by planning horizons, legal entities, currencies and major cash flow categories. Only then does it become clear whether deviations stem from structural weaknesses in the planning approach, data quality issues or exceptional events. For treasury managers, this KPI is particularly relevant because it directly affects the reliability of financing, investment and risk management decisions. 

In addition, the Liquidity Headroom shows the level of liquidity that is actually available to the company after taking expected peak outflows into account. It typically includes a) cash on hand and b) committed but undrawn credit lines, less c) short-term expected liquidity needs. This means that liquidity headroom is not just a static measure but also an early warning indicator of financial resilience. Its management value increases when it is not reported in isolation but linked to stress scenarios, refinancing decisions and management thresholds.

The Minimum Liquidity Days metric adds a time dimension to this perspective. It indicates how long a company can remain solvent under defined assumptions without accessing additional financing. It is therefore particularly useful for assessing short-term crisis resilience and can serve as a basis for decisions such as drawing credit lines, adjusting payment terms or prioritizing cash mobilization measures. However, this requires a clear definition of the underlying assumptions, for example regarding a) operating inflows b) fixed outflows c) available credit lines and d) potential restrictions on access to liquidity.

3.2 Cash Management & Payments
A high-performing cash management function ensures the smooth execution of payments while also enabling efficient use of liquidity across the group. KPIs in this area therefore focus on both efficiency and risk dimensions.

A key KPI for assessing group-wide liquidity mobilization is the Cash Pooling Participation Rate. It measures the share of available group liquidity that is actually integrated into cash pooling structures and thus provides insight into the effectiveness of internal liquidity utilization. Low participation rates often point to regulatory constraints, operational integration gaps or local particularities of individual entities. Its management value emerges especially when considered alongside financing and working capital questions, as liquidity that is not integrated often leads to avoidable external funding requirements. 

The Straight-Through-Processing Rate indicates the proportion of payments that are processed fully automatically without manual intervention. It serves as a measure of process standardization, the degree of automation and operational risk in payment processing. High STP rates generally indicate stable interfaces and clean data structures, but should not be interpreted in isolation. Manual exception processes or high-risk activities outside the standard flow can be obscured by a high STP rate, which is why combining it with error and exception indicators is critical. 

The Payment Error or Rejection Rate measures the share of payments that are erroneous or rejected by banks. It provides valuable insights into a) master data quality b) compliance with format requirements c) system stability and d) the effectiveness of bank connectivity. In the context of ISO 20022 and the Verification of Payee (VoP), this KPI is gaining additional importance. New structured data models and enhanced validation checks ensure that discrepancies are identified earlier. As a result, particularly during initial implementation phases or in cases of insufficient data quality, a temporary increase in rejected payments may become visible. Elevated rejection rates therefore often indicate weaknesses in data maintenance, in mapping and validation logic or in approval and control processes. As an early warning indicator, this KPI plays a key role in reducing operational, fraud and reputational risks. 

3.3 Financing
In the area of Financing, the focus is on the cost, flexibility and stability of external funding. KPIs in this context are used to make financing efficiency transparent and to identify risks at an early stage.

The Weighted Average Cost of Funding (WACF) aggregates financing costs across all instruments, maturities and currencies and is a key metric for assessing financing efficiency. Its value lies less in its standalone figure and more in the analysis of its underlying drivers, such as the structure of financing instruments, credit ratings, market conditions or collateralization. Changes in WACF provide important signals for adjusting the financing strategy.

In addition, Committed Facility Utilization provides insights into the use of external funding capacity. It relates drawn credit lines to committed facilities and shows the extent to which a company currently relies on external liquidity sources. High utilization may indicate limited internal liquidity buffers or increased market uncertainty and is therefore closely linked to refinancing and liquidity risks.

Covenant Headroom measures the distance to contractually defined financial covenants in loan agreements. It serves as a key early warning indicator for potential funding constraints and breaches. In practice, this KPI gains management value when it is closely linked to forecasts, scenario analyses and clearly defined management trigger points. 

3.4 Bank Account Management
Bank Account Management is often an underestimated yet governance‑critical management area within treasury. The associated KPIs address complexity, cost, and operational risk.

The Bank Accounts per Legal Entity metric measures the number of active bank accounts per legal entity and serves as an indicator of organizational complexity, KYC effort, and potential fraud risks. A high number of accounts reduces transparency, increases control effort, and ties up resources. This KPI therefore supports decisions around account rationalization and standardization.

To manage bank-related costs, the Annual Bank Fees vs. Budget KPI is commonly used. It compares actual bank fees incurred with planned costs and serves as an important basis for cost control and bank negotiations. Deviations provide insights into changes in transaction volumes, inefficient account structures, or pricing arrangements that are no longer in line with market standards.

The Automation Rate measures the share of account statement processing and reconciliation activities that are handled based on rules and without manual intervention. Its management value lies in making the actual level of automation in the core “accounting and treasury reconciliation” process transparent and in highlighting key sources of disruption, such as missing references, inconsistent booking texts, or incomplete master data. In the context of ISO 20022, structured CAMT formats improve the data foundation for matching and exception handling, as more structured fields are available for references and additional information. This does not automatically increase automation, but it creates the conditions for designing more robust rules and systematically reducing exceptions. 

3.5 Financial Risk Management
Financial Risk Management in corporate treasury encompasses the systematic identification, quantification, and management of financial risks. Against the backdrop of increasing market volatility, geopolitical uncertainty and dynamic interest rate developments, risk-oriented KPIs are becoming ever more important. In an environment shaped by VUCA factors (volatility, uncertainty, complexity and ambiguity) it is essential not only to make existing risk positions transparent but also to anticipate their potential impact on earnings, liquidity and financial stability at an early stage and actively manage them.

Cash Flow at Risk (CFaR) quantifies the potential negative impact of market movements on future cash flows within a defined planning horizon and confidence level. It therefore provides a probabilistic view of risk and supports, in particular, the design and managing of hedging strategies. As highlighted in the article ”At-Risk Measures in Treasury“ in KPMG Corporate Treasury News, At-Risk measures enable an integrated portfolio view that takes into account volatilities as well as diversification and correlation effects between risk factors, thereby offering significantly greater analytical value for decision-making.

Interest Rate Sensitivity measures the impact of changes in interest rates on net interest income, typically based on standardized shocks such as a plus or minus 100 basis points scenario. It illustrates the effect on annual interest expense and provides clear and intuitive transparency regarding the company’s exposure to interest rate movements. 

Counterparty Limit Utilization measures the current exposure to banks and other financial counterparties in relation to defined credit limits. This KPI creates transparency on the utilization of individual counterparties and ensures that established risk limits are adhered to. It thus serves as a key management indicator in counterparty risk management and enables the early identification of concentration risks.

KPIs only translate to real management impact when they are understood, accepted and consistently applied. Treasury leaders should therefore focus on clear KPI ownership, a shared understanding of definitions and the ability to interpret deviations correctly and translate them into concrete actions. In practice, the main challenge is often not the availability of KPIs but rather unclear responsibilities, inconsistent definitions and an inconsistent use in reporting and decision-making.

The key is to embed KPIs firmly into decision-making and management processes. A robust KPI framework links metrics with clear ownership, reliable and timely data sources as well as predefined response mechanisms. Deviations should be addressed systematically and translated into targeted management actions in order to fully unlock their management potential.

At the same time, systems and data processes play a central role. Treasury systems can consolidate data, support validations, and provide KPIs in a standardized and automated way. Modern TMS solutions increasingly integrate reporting and analytics functionalities with predefined data models, enabling faster KPI generation. However, what remains critical is the consistent design of upstream data collection, mapping, and validation processes, as well as their integration into the overall management logic. Without this foundation, even highly integrated analytics tools and dashboards will only create transparency without actually enabling effective management.

In this context, the effectiveness of treasury management depends largely on the underlying enabling factors. These include, in particular, high data quality as well as integrated and robust system landscapes. Only when data is available in a consistent and timely manner can KPIs be reliably interpreted and used for decision-making. The use of advanced analytics and artificial intelligence is also becoming increasingly important, as it enhances forecasting capabilities and supports decision processes. A solid foundation for data-driven treasury management only emerges when these factors are consistently embedded into the management logic.

In practice, treasury managers should therefore ensure that for each KPI it is clearly defined a) which decision it supports b) which threshold triggers an action and c) who is responsible for deriving and implementing the necessary measures. An effective KPI system is not characterized by the sheer number of metrics, but by their relevance and their clear linkage to decisions. Treasury leaders should also regularly challenge their KPI landscape: 

• Do existing KPIs support concrete management decisions?
• Do they adequately capture key risk and governance questions?
• Do deviations lead to clear and actionable responses?

Only when KPIs are consistently translated into decisions does reporting truly become effective treasury management.