Over the past few decades, financial institutions have invested heavily in modernizing their technology landscapes, introducing new platforms to meet evolving business and regulatory requirements. Yet many banks continue operating the same fragmented balance sheet management model underneath. Replacing servers, renewing applications, or migrating to the cloud improves the technology landscape, but it does not necessarily simplify the way Asset & Liability Management (ALM), Funds Transfer Pricing (FTP), Regulatory Reporting, and Financial Planning operate together.
This article examines a representative five-year use case comparing four independent on-premises balance sheet management platforms with a single integrated SaaS operating environment. Rather than focusing only on technology costs, it explores where the savings actually originate and why simplifying the operating model can generate value well beyond infrastructure modernization.
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Infrastructure is often the starting point for technology investment decisions because hardware, software licenses and maintenance costs are relatively easy to quantify. The broader economic picture is more difficult to measure. When balance sheet management activities operate across independent platforms, institutions also assume the cost of maintaining the connections between them, including data integration, operational support and recurring change across multiple environments.
Technology modernization projects usually begin with the most visible costs, such as infrastructure refreshes, software license renewals, cloud migration and maintenance contracts. Because these investments are relatively easy to identify and quantify, they naturally become the starting point for evaluating a modernization initiative.
The economics of balance sheet management, however, extend much further. ALM, FTP, Regulatory Reporting, and Financial Planning are closely connected disciplines that exchange information, share common methodologies, and contribute to a shared view of the balance sheet. When they operate on independent platforms, data moves through separate interfaces, methodologies evolve independently, and regulatory or business changes often need to be implemented multiple times before they are reflected consistently across the operating environment.
As a result, the investment case extends beyond technology expenditure. Consolidating platforms reduces more than infrastructure costs. It also simplifies data management, operational support and change implementation, creating a more efficient operating model across Finance, Risk and Treasury.
To understand how these costs accumulate, consider a representative large financial institution operating four specialized on-premises platforms supporting:
Asset & Liability Management
Funds Transfer Pricing
Regulatory Reporting
Financial Planning
This type of environment is common among institutions that have expanded their capabilities over time. Specialized systems are introduced over time to meet regulatory expectations, business requirements, and functional priorities. Each implementation may deliver value independently, yet the resulting landscape often consists of interconnected platforms with separate technology foundations and operating models.
In the legacy scenario, each platform has its own infrastructure, licensing arrangements and support requirements. Data is stored and processed through independent repositories, pipelines and interfaces, while regulatory adaptations, methodology changes and major upgrades follow separate development, testing and deployment cycles.
The comparison evaluates this fragmented model against a single integrated SaaS environment supporting the same functional scope over five years. It is designed to isolate the economic impact of consolidation rather than attribute value to changes in analytical capabilities or business activity.
The model covers the principal costs associated with running and evolving the operating environment:
On-premises infrastructure
Software licensing
IT support resources
Data management and feed support
Regulatory adaptation
Major platform upgrades and implementation
Together, these categories provide a more complete view of Total Cost of Ownership than infrastructure or licensing expenditure alone.
When the full operating model is evaluated over five years, the financial impact is substantial. The representative legacy environment generates a five-year TCO of €30.93 million, compared with €9.39 million for the integrated SaaS environment.
The resulting business case delivers:
€21.54 million in net savings over five years
€16.2 million in Net Present Value, using a 10% discount rate
229% Return on Investment
An Internal Rate of Return above 500%
Payback within the first year
These results answer the headline question, but the total saving tells only part of the story. The distribution of the benefits is equally important because it shows that the business case is not dependent on a single technology assumption.
Infrastructure is the largest contributor, yet almost two-thirds of the savings arise elsewhere. Support resources, data management, licensing and regulatory adaptation collectively account for the majority of the financial improvement.
The five-year savings are distributed across five main categories:
On-premises infrastructure: €7.93 million, or 37% of total savings
IT support resources: €6.75 million, or 31%
Software licensing: €2.96 million, or 14%
Data management and feed support: €2.70 million, or 13%
Regulatory adaptation: €1.20 million, or 6%
Major platform upgrades and the initial SaaS implementation are broadly comparable in the model, with the legacy environment allocating €0.58 million to a major version upgrade cycle and the integrated scenario €0.60 million to implementation. The negligible difference reinforces an important point: the business case is not driven by one-off migration costs, but by the recurring costs of operating a fragmented environment.
The breakdown shows that infrastructure accounts for just over one-third of the total savings, while the remaining value comes from simplifying the people, processes and recurring activities required to support the operating model.
Software licensing has also been normalized across both scenarios to isolate these structural cost drivers. By assuming comparable licensing costs before consolidation, the analysis focuses on the economic impact of reducing operational complexity rather than differences in vendor pricing.
The legacy environment assumes a three-year infrastructure investment cycle. The ALM, Regulatory Reporting and Financial Planning platforms each require €1.5 million per cycle to support high-availability servers, storage and database licensing, while the FTP platform requires €500,000 because of its lower computational demands. Together, these investments generate annualized infrastructure costs of approximately €1.67 million, or €8.33 million over five years.
Moving to an integrated SaaS operating environment reduces this category to €0.40 million, generating €7.93 million in savings. This is the most visible component of the business case, eliminating much of the infrastructure associated with servers, storage, databases and disaster recovery while reducing exposure to recurring refresh cycles.
Even so, infrastructure accounts for just 37% of the total savings. The remaining value comes from simplifying the operating model itself, reducing the resources, processes and ongoing effort required to support, connect and evolve multiple independent platforms.
Maintaining four independent platforms requires dedicated teams to keep each application available, connected and functioning correctly.
In the representative legacy scenario, each system requires 2.5 dedicated IT full-time equivalents. Across four platforms, this produces a total support requirement of ten FTEs.
These resources are responsible for activities such as:
Operating system and application maintenance
Integration and connector management
Monitoring and incident resolution
System availability and technical administration
Coordination with vendors and internal technology teams
Using a fully loaded annual cost of €135,000 per FTE, IT support expenditure reaches €6.75 million over five years.
The integrated SaaS scenario assumes that two FTEs remain responsible for internal platform oversight, while their cost is included within the wider operating model rather than recorded as a separate IT support line. The resulting reduction in dedicated support requirements accounts for 31% of total savings.
The significance of this category extends beyond headcount. Supporting four environments means managing four sets of dependencies, incidents, integrations, access controls and release schedules. Consolidation reduces the number of operational relationships that need to be coordinated, allowing specialist resources to focus on higher-value platform governance and analytical support.
Data management is another major source of recurring cost in fragmented operating models. The legacy environment assumes 1.5 dedicated data management FTEs per platform, resulting in a total of six FTEs supporting data loading, feed validation, core banking integrations, transformation processes and reconciliation activities.
This duplication arises because each platform maintains its own data pipelines, processing rules and operational controls, even when consuming similar source information or supporting related balance sheet activities. As data moves across ALM, FTP, Regulatory Reporting and Financial Planning, it is often extracted, transformed and validated multiple times before outputs can be compared or combined.
Over five years, the legacy environment generates €4.05 million in data management costs. The integrated operating model reduces this to €1.35 million, generating €2.70 million in savings by consolidating these activities within a shared data foundation rather than replicating them across multiple systems.
Regulatory adaptation is smaller than infrastructure or support in absolute terms, but it illustrates how fragmentation increases the cost of change.
Major regulatory initiatives can require modifications to calculation engines, reporting templates, data structures and underlying methodologies. Recent examples include CRR3 and CRD6, revised IRRBB reporting requirements, DORA, FRTB and ESG-related capital developments.
For an on-premises environment, each regulatory wave may involve:
Gap assessments
Methodology interpretation
Application development
Data and reporting changes
Testing and validation
Release coordination
Supervisory or audit review
Within the model, these costs are allocated primarily to the Regulatory Reporting platform, which has the greatest direct exposure to evolving supervisory requirements. Annual regulatory adaptation expenditure is estimated at €200,000, producing €1.20 million over the modeled period.
The use case is deliberately conservative. ALM, liquidity, FTP and planning systems may also require changes when regulatory methodologies, internal models or reporting expectations evolve. These broader effects are not fully allocated across the four legacy platforms.
In an integrated SaaS environment, regulatory and platform updates can be incorporated within a common service model. This reduces the need for separate adaptation projects and limits the repetition of development, testing, and deployment activities across independent systems.
Major on-premises version upgrades often become projects in their own right. They can take six to eighteen months and involve integration reviews, custom development changes, output validation, user testing and training. External consulting alone may cost between €100,000 and €400,000 per system, before accounting for internal technology and business resources.
The five-year model assumes one major upgrade cycle affecting all four legacy platforms. In the SaaS scenario, updates are delivered as part of the service, avoiding four separate migration initiatives.
Although the direct financial difference between upgrades and implementation is relatively small, the operational impact is not. Large upgrade projects consume specialist resources, introduce compatibility risks and require coordination across multiple interconnected systems. An evergreen SaaS model replaces these periodic transformation projects with continuous platform evolution.
Technology modernization is often justified through infrastructure savings because they are the easiest costs to quantify. Infrastructure represents only 37% of the total financial benefit.
The remaining value comes from simplifying the operating model itself. Reducing duplicated support structures, streamlining data management and avoiding repeated regulatory adaptations lowers the five-year TCO from €30.93 million to €9.39 million, generating €21.54 million in net savings, a 229% ROI and payback within the first year.
The central lesson is that the economic value of consolidation depends as much on the operating model as on the underlying technology. By bringing ALM, FTP, Regulatory Reporting and Financial Planning together within a single SaaS operating environment, Mirai helps financial institutions reduce complexity, strengthen consistency and focus more resources on analysis and decision-making.
Inside "The Cost of BSM Fragmentation in Banking," you will explore the complete five-year use case, including assumptions, cost categories and methodology, for CFOs, CTOs and Heads of Treasury/ALM evaluating platform consolidation. Download the whitepaper
How much can banks save by consolidating balance sheet management platforms?
A five-year model comparing four on-premises platforms with one integrated SaaS environment shows €21.54 million in net savings, a 229% ROI, and payback within the first year.
Where do the savings actually come from?
Infrastructure accounts for 37% of the total. The rest comes from reduced IT support, consolidated data management, lower licensing costs, and fewer repeated regulatory adaptation projects.
Does consolidation only apply to large institutions?
The use case models a large financial institution, but the underlying driver — recurring cost of running separate platforms for ALM, FTP, Regulatory Reporting and Financial Planning — scales down proportionally for smaller institutions with fewer specialized systems.
Is the business case dependent on infrastructure savings alone?
No. Software licensing was normalized across both scenarios specifically to isolate the impact of operational complexity rather than technology pricing, so the case holds even where licensing costs are similar.
How is regulatory adaptation cost affected by consolidation?
In a fragmented environment, each regulatory change (e.g. CRR3, IRRBB, DORA) may need separate gap assessment, development and testing per platform. A shared service model absorbs these into a common update cycle instead.