Given the volatile nature of interest rates, liquidity pressures, and staffing challenges, ALM integration is now a strategic necessity for community banks and credit unions.

Without it, institutions remain dependent on disconnected budgeting, profitability, and CECL systems, often powered by different cash flow engines and modeling logic. The result is inconsistent outputs from similar analyses, driving manual reconciliation and conflicting executive views of risk, performance, and strategy.

A unified platform for managing financial risk is the solution for surviving and thriving in an uncertain business environment. It provides teams with a shared platform for analysis and planning.

This guide highlights key insights to help you achieve an integrated ALM platform.

Tip: If you’re concerned about a lack of resources to do this successfully, check out our webinar on how to integrate Budgeting and ALM Without an In-House Model.

The Shift Toward Integrated ALM

For many community banks and credit unions, asset and liability management and budgeting operate separately. This means teams often use different assumptions when analyzing rates, growth, and risk. 

That’s changing: 32% of respondents in the Empyrean Trends in Financial Risk Management research already integrate ALM with budgeting tools, and another 28% plan to, signaling real momentum toward integrated risk–finance platforms.

The result is suboptimal outputs, inefficient use of time, and hours spent on manual processes before results can even be shared with executives. This ultimately creates unnecessary risk and slows decision-making.

ALM integration means unifying the processes with budgeting, planning, profitability, and CECL. The idea is to have all of these functions have a single source of truth for data. This eliminates the need to rebuild forecasts with multiple tools and instead allows teams to analyze risk from a single framework.

It also supports faster responses to rate shifts. Among respondents in the same research preparing for falling rates, 51% maintain their current strategy, 27% adjust their balance-sheet strategy, and 20% run dynamic forecasts. The kind of scenario mix that benefits from shared assumptions across teams.

Having an integrated financial risk management platform is critical for banks that already have limited staffing. Unified systems reduce manual processes, improve confidence in results, and free up time to focus on other tasks.

Why ALM and Budgeting Belong Together

 ALM and budgeting are now the standard. It will soon likely be considered a minimum requirement to ensure banks have the tools necessary to manage risk. This is especially true given the continued volatility and uncertainty of the business environment.

When ALM and budgeting don’t use the same dataset, the result is often forecasts that don’t accurately reflect market risk for rates, expected deposit behavior, or potential cash flow or liquidity issues. 

It’s also possible that asset-liability committee (ALCO) reviews depend on scenarios that aren’t fully translated to the final budget or forecast. This disconnect is a significant factor in the adoption of incorrect business decisions and strategies.

By integrating ALM and budgeting, shared assumptions about rates and other market risks can enable an institution to develop more realistic, more accurate forecasts. 

This includes factors such as growth, cash flow, and deposit behavior. Ultimately, all of this helps contribute to a faster, more informed decision-making process.

ALM as a Strategic Tool

While ALM has historically been seen as a compliance tool to meet regulatory requirements, it can also serve as a strategic tool when integrated with planning and profitability. 

Done correctly, it can provide institutions with data on factors that may affect growth rates across different business environments.

Having an integrated ALM platform allows banks and lending institutions to evaluate business decisions before they’re implemented, based on interest rate risk and margin impact. 

For instance, it supports a more effective margin strategy by revealing how changes in deposits, loan growth, and the funding mix can affect earnings. 

This allows decisions to be made with greater confidence, since liquidity and rate risks will have been analyzed alongside balance sheet projections. Scenario-driven decision support is the bottom-line goal. 

Integrated ALM allows banks to avoid static forecasts and instead evaluate multiple scenarios and view the potential impacts across areas such as risk, earnings, liquidity, and capital. This essentially transforms ALM into a forward-looking strategic tool to support better business decisions.

How to Integrate ALM Without an In-House Model

Contrary to what some may believe, integrating ALM can be done without having an in-house modeling team. A common approach is to use an outsourced model and gradually transition it in-house.

Using this approach, institutions gain instant access to expert modeling, governance, and scenario analysis. Teams can further prioritize efforts on interpreting model outputs and determining appropriate business decisions, rather than building or maintaining the model itself. 

Assuming the outsourced ALM model is brought in on the same platform as budgeting, CECL, and other systems, integration occurs on day one. Assumptions around rates, risks, and growth rates further remain consistent across all models.

Given more time or as resources grow, credit unions and banks can successfully bring ALM in-house. Since all underlying data and assumptions would already be on a single unified platform, no additional effort would be required for data migration or process redesign. 

All of this results in a low-risk approach that banks can take while still seeing value from day one.

One Data Model for Risk, Planning & Reporting

At its core, ALM integration is a unified model that supports risk analysis and planning. It eliminates the need for separate data sets and uses a single source of truth, so that all team functions work from the same information.

Doing so eliminates the need to manually reconcile differences in assumptions among teams. This applies to a variety of functions and data types, including interest rates, deposit behavior, prepayments, growth, liquidity, and more. 

Teams no longer need to deal with scenarios where explanations are required to understand why ALM might tell a different story than budgeting, or why CECL outputs don’t align with profitability projections.

ALM integration helps maintain data consistency, which directly impacts reporting quality. Reports to executives become clearer and easier to explain, with a lower risk of needing to evaluate data discrepancies. 

Furthermore, scenario results can be traced more easily through earnings forecasts, thereby driving greater confidence in strategic discussions. 

Integrated CECL and Profitability

CECL and profitability analysis are more effective when powered by the same cash flow engine as ALM and budgeting. Otherwise, functions tend to operate independently, forcing teams to recreate the same data sets and assumptions, tasks that introduce the risk of error and take longer to complete.

An integrated approach allows CECL and profitability functions to use the same underlying data for things like cash flow, balance sheet, and other economic scenarios. 

This creates better alignment for various financial estimates such as credit losses, earnings forecasts, and interest rate risk. Changes to assumptions also flow more seamlessly across models, reducing errors and enabling greater transparency.

Since manual processes can be significantly reduced, if not eliminated, integration allows teams to spend more time interpreting, validating, and determining next strategic steps. 

Perhaps more importantly, results are more easily transformed into an audit-ready state. This can further save teams time without having to take special steps to prepare for a regulatory review.

Overall, by integrating CECL and profitability, institutions can gain more reliable insights and forecasts while simultaneously improving compliance processes and confidence in the implementation of new business strategies.

Scenario Planning With Integrated ALM

Scenario planning is an area where integrated ALM can deliver immense value. Banks can run multiple scenarios to assess potential impacts across risk, liquidity, capital, and other areas. This is particularly valuable in evaluating funding strategies and deposit risk management.

With integrated ALM, banks no longer need to evaluate risk, earnings, deposits, credit, or growth strategies independently. Instead, banks can use the platform to determine how each will be impacted given various assumptions. 

For example, teams can determine how changes in rates can simultaneously affect margins, capital, and liquidity while also understanding impacts on CECL, profitability, and budgets.

For smaller banks, integrated ALM can improve their ability to provide valuable insights without changes in staffing or resources. 

Less time will also be needed to build and evaluate models, allowing reports to be built more quickly and more easily explained to executives, thanks to consistent assumptions across functional areas.

What to Look for in ALM Integration

When considering ALM integration solutions, institutions should look for features that reduce complexity while still providing valuable insight. The most effective platforms share the following characteristics:

• Direct ALM and budgeting integration: This connects financial planning and risk modeling behavior without duplicating workflows, processes, or data entry.
• Unified assumptions across CECL and profitability: Ensure consistency in both inputs and outputs when it comes to liquidity, balance sheet, and cash flow behavior.
• Outsourced option with in-house transition: Institutions can use an outsourced ALM platform model to scale at their own pace over a period of time.
• Automated board and ALCO reporting: This helps create consistent, clear, and easily supported outputs by leveraging a single data source.
• Minimal manual reconciliation: Save time by eliminating manual processes that are also more prone to human error and oversight.
• Bank-specific modeling logic: ALM integration solutions should be tailored to how banks and credit unions operate, rather than a generic model that fails to account for the nuances of an institution’s operating environment.

How Empyrean Delivers ALM Integration

Empyrean’s ALM integration solution is designed with the reality that banks and credit unions face. It is not a generic one-size-fits-all platform. Consider it a financial risk management platform that combines risk management, budgeting, planning, and performance in a single environment.

Integrated ALM by Empyrean delivers scenario-based modeling that unifies budgeting and planning. This ensures that assumptions and forecasts remain aligned. 

CECL modeling further uses the same engine to improve upon compliance and audit-readiness. Finally, profitability and FTP provide deeper insights, connecting risk-adjusted performance to pricing, strategy, and capital allocation.

Institutions that don’t have the staffing or resources to manage ALM internally can still utilize Empyrean’s outsourced ALM option. 

Doing so allows the bank to leverage ALM insights immediately while gradually transitioning to an in-house ownership model.Learn more about how Empyrean ALM works alongside risk management to help your institution produce more accurate results with a greater degree of confidence for strategic decision-making across your organization.

 FAQ: ALM Integration