ALM Functions: An Organizational Approach in a Context of Uncertainty

Financial institutions currently operate in an environment characterized by heightened uncertainty. This perception is reinforced by the Global Risks Report 2026 published by the World Economic Forum, which, based on a survey of global leaders and experts, indicates that the majority of respondents expect uncertainty and turbulence to increase over the next two years, while only 1% anticipate a more “calm” global environment.

This volatility in key market risk factors, especially interest rates and liquidity conditions, has increased the relevance of Asset & Liability Management (ALM) functions within these institutions.

This article reflects on how ALM functions are organized within banks, based on observed organizational practices, and on the role of technology as a key element in structuring and supporting these functions. 

   Audio Article

Ongoing geopolitical tensions, market volatility, and an active debate around the appropriate level of regulatory complexity are shaping the way banks manage their balance sheets. In particular, there is discussion around whether regulation should become simpler or remain highly detailed, with different approaches observed across jurisdictions. In this context, ALM-related activities typically involve several key functions within the institution, including Treasury, Financial Management, Risk Management, and Finance.

These ALM functions play a central role in managing interest rate risk, liquidity risk, balance sheet structure, and, more broadly, the stability of the institution.

The Purpose of an Organizational Perspective on ALM Functions

The objective of analyzing ALM from an organizational perspective is not to define a single “correct” structure, but to understand how different functions interact in practice. ALM sits at the intersection of several areas—typically Treasury, Risk, and Finance—and requires coordination between:

• Liquidity management,
• Interest rate risk management,
• Balance sheet and banking book management,
• Risk control and internal reporting,
• Accounting consistency and regulatory compliance.

Ensuring that these functions are properly coordinated is essential for making daily decisions in an effective way, particularly in volatile environments.

Observed Organizational ALM Models in Practice

A review of how banks describe their internal organization reveals that, while structures are broadly similar, there are notable differences in how responsibilities are allocated. These differences can be grouped into three high-level organizational models.

Model A: Separated ALM Functional Structures

In some institutions, ALM-related responsibilities are clearly separated:

• Liquidity management is handled by one unit
• Interest rate risk management is handled by another
• Management of banking book portfolios may sit in a different area
• Risk control functions operate independently as part of the second line of defense

This structure reflects a strong functional specialization, but requires coordination mechanisms to ensure a consistent view of the balance sheet.

Model B: Integrated ALM Structure under a Single Head

In other organizations, ALM-related activities are grouped more tightly:

• Liquidity, interest rate risk, and banking book management are brought together under a single leadership
• Decision-making is more centralized from a balance sheet perspective
• The second line of defense remains separate, focusing on oversight and control

This approach places greater emphasis on having a unified view of balance sheet risks and management actions.

Model C: Mixed or Hybrid ALM Structures

There are also cases where institutions combine elements of both approaches:

• Functions may be separated at an operational level
• Coordination is achieved through committees, shared processes, or governance forums
• Responsibilities are distributed, but decision-making relies on structured interaction between teams

These hybrid structures reflect the diversity of organizational choices observed across institutions.

The Role of ALCO

Regardless of how ALM responsibilities are organized across the institution, decision-making ultimately converges at the same point. Across all organizational models, the Asset & Liability Committee (ALCO) plays a central role as the main forum where ALM-related decisions are discussed, assessed, and agreed.

Its responsibilities typically include:

• Reviewing liquidity and interest rate risk positions
• Assessing the impact of balance sheet strategies
• Evaluating different management actions and their consequences
• Ensuring alignment between management actions and the institution’s risk framework
• Coordinating with commercial needs and business strategies, facilitating their execution while ensuring consistency with the balance sheet positioning

In this sense, ALCO functions as the core decision-making body for ALM-related matters, providing a structured setting in which different perspectives on balance sheet management are brought together and translated into concrete actions.

4 Key Challenges in ALM Organization

Several challenges emerge when integrating ALM into the broader risk management and strategic planning framework:

1. The need to coordinate multiple functions with different objectives
2. Increasing regulatory expectations around control, reporting, and governance
3. The difficulty of managing balance sheet risks in volatile and uncertain market conditions
4. The requirement to ensure consistency between management views, risk control metrics, and regulatory reporting, with a focus on complying with regulatory requirements and supervisory expectations, and ensuring these are appropriately reflected through regulatory reports

These challenges place pressure on both organizational structures and supporting processes.

Balancing Profitability and Risk Control

One of the central issues in ALM is balancing profitability objectives, such as net interest income, in line with the institution’s defined risk appetite—expressed through its control metrics—and incorporating the efficient use of capital, together with risk control measures, including interest rate and liquidity risk limits.

This balance requires understanding of what management actions are available, how these actions affect both profitability and risk, and how outcomes change under different market conditions.  

Rather than focusing solely on decisions taken at a specific point in time, the emphasis is on understanding the range of possible actions and their impacts.

From Reaction to Preparation

A recurring theme is that effective ALM is about being prepared in advance, not only about reacting when events occur. This preparation starts with having detailed visibility over all future cash flows associated with the balance sheet, which, when combined with the institution’s commercial strategies and actions, becomes the primary input for analyzing potential future scenarios.

Based on this foundation, institutions can assess in advance what actions could be taken and evaluate the likely impact of those actions before they are needed. 

Given that several areas are involved in ALM-related activities, effective preparation also depends on proper coordination across functions.

While organizational structures may differ, a key element for coordination is that all relevant areas work on a common and consistent information base. This does not imply a loss of independence: each function must continue to operate within its own responsibilities, obligations, and degree of independence, but with a shared understanding of the underlying information.

When an actual event occurs, the situation may not exactly match any predefined scenario. However, having carried out prior analysis using a common information base allows institutions to react more quickly and with greater confidence, adjusting predefined actions to the specific circumstances they face. 

Technology as a Supporting and Structuring Element of ALM Functions

Technology plays a critical role in supporting ALM functions. In particular, integrated platforms can help to:

1. Centralize data loading processes, optimizing costs
2. Ensure consistent use of data across functions
3. Support scenario analysis and simulations
4. Allow different teams to work with the same information base 

Beyond the technological architecture itself, the completeness and quality of data stored in repositories or data lakes are critical for these capabilities to function effectively. Having reliable, consistent, and high-quality data is therefore a fundamental prerequisite for technology to deliver its full value in supporting ALM processes.

When technology and analytical support are robust, the areas responsible for ALM management can focus their efforts on what truly adds value: generating, analyzing, and interpreting the critical information required for decision-making, rather than spending time on data manipulation or reconciliation. This information must be properly embedded in the institution’s key decision-making processes, ensuring that it systematically feeds into the relevant governance forums.

In this context, high-quality analysis and reporting become an integral part of the daily decision flow across the organization, supporting discussions at forums such as ALCO, risk committees, and senior management committees.

The value of technology, therefore, lies not in simplifying the inherent complexity of ALM decisions but in enabling more effective, informed, and coordinated decision-making across all relevant functions while remaining aligned with regulatory expectations regarding model transparency and control.

Looking Ahead

Looking forward, ALM functions will continue to operate in an environment shaped by regulatory debate, market volatility, and ongoing technological change. The challenge here is not only to adapt to uncertainty but also to take advantage of new technological capabilities to reinforce coordination across the different areas involved in ALM, while preserving their respective independence, responsibilities, and accountability.

There is no single organizational model that fits all institutions. Different banks adopt different structures depending on their size, complexity, and strategic priorities. What consistently emerges, however, is the importance of having a common framework that connects data, analysis, and decision-making, enabling the various functions to work in a coordinated manner on a shared and reliable information base.

A well-structured technological platform can act as a unifying element, helping to organize processes, simplify the preparation of information, and ensure consistency across functions. In this sense, solutions such as those offered by Mirai Risktech illustrate how the use of artificial intelligence and advanced analytics can support this objective, facilitating coordination across areas and allowing ALM teams to focus on generating and analyzing the critical information required for decision-making.  

In an uncertain environment, the ability to prepare high-quality information efficiently and to understand in advance what actions are available, and their potential impacts, remains a key strength of effective ALM functions. 

Turn ALM Coordination Into a Structured Advantage 

See how the Mirai RiskTech platform helps banks centralize ALM data, align Treasury, Risk, and Finance, and support ALCO decisions with consistent, forward-looking analysis. 

👉 Book a demo and explore how advanced analytics and AI can support more informed balance sheet management.