Laying the foundation for data management in bank transformation

The ability to manage data effectively has become a strategic differentiator for banks dealing with increasing data volumes, technological change and complexities, competition, and regulatory pressures.  

However, achieving this is far from straightforward. Banks operate in an environment with high data volumes, entrenched legacy systems, and fast-changing regulatory requirements that vary across jurisdictions. As a result, the outcome is often a fragmented data landscape that undermines regulatory compliance, operational efficiency, and decision-making. 

In order to remain competitive, financial institutions must address these challenges head-on. Standardized data management offers a powerful solution—one that reduces complexity, enables seamless data integration, enhances reporting accuracy, and provides a foundation for digital transformation.  

This article explores why inconsistent data management based on fragmented data silos persists and the risks it creates, and why adopting a standardized approach can create operational and strategic advantages. 

The case for data management as the enabler of bank transformation 

As the banking industry navigates an era of increasing regulatory complexity combined with rapid technological advancement and competition from upcoming fintech players, effective data management has emerged as a critical enabler of transformation.  

Yet, this is difficult to achieve because of the sheer scale and ever rising volumes and diversity of banking data.  

Addressing these challenges through standardized data management is essential for driving cost efficiency, ensuring compliance, enabling innovation, and staying relevant in a very competitive market.

Why inconsistent data management is common 

According to a 2023 Precedence Research report, the banking sector is one of the most data-intensive globally. This industry manages vast amounts of data daily, reflecting every customer interaction and financial transaction.   

For instance,  

• The Bank of England processes 35 million rows of regulatory data daily and manages 30,000 statistical data series from over 300 institutions while handling approximately 200 reporting templates.  

• A multinational bank like UBS operates thousands of IT systems across its 1000+ global branches. Each of these systems is tailored to meet local regulatory and operational requirements. 

This complexity is compounded by the fragmented systems of record—the bank’s operational systems that track individual transactions—and the analytical platforms that process bank-wide data from diverse and often unaligned data models in the operational systems.  

Maintaining one data model with a single standardized version of the software and IT infrastructure is impossible. This is especially true for large banks due to the diversity of global regulatory requirements.  

A complex data integration architecture makes aligning operational and analytical systems difficult. It can potentially cause data inconsistencies in reporting, risk assessments, and regulatory compliance reporting. 

The consequences of inconsistent data management 

Inconsistent and unstandardized data management creates significant risks for financial institutions. These include: 

• Compliance risks: Legacy systems on outdated IT-Platforms and fragmented data management silos may fail to meet evolving regulatory standards. This increases the likelihood of errors and compliance breaches. For example, non-aligned data models can cause inaccuracies in financial disclosures, regulatory filings, or risk calculations. 

• Operational inefficiencies: The complexity of banks’ IT systems requires constant manual interventions to reconcile data inconsistencies, introducing operational risks and inefficiencies along with high maintenance costs. This also diverts resources from more value-adding activities, such as financial closing and liquidity forecasting, and slows down the ability to report on timely data. 

• Strategic implications: Senior bank leaders rely on data with a full view of the bank’s assets and liabilities to drive strategy. Without a single source of truth, decision-making is hindered, limiting the ability to manage risks or allocate capital effectively. For instance, liquidity risk management depends on accurately aligning short- and long-term liquidity data with daily balance sheets. Misalignment in these areas can lead to lending overreach or insufficient liquidity reserves. 

Standardized data management as the solution 

Standardized data management provides a clear pathway for addressing these challenges. By implementing consistent data models and processes, banks can create a robust foundation for transformation. Key benefits include: 

• Improved compliance: A standardized approach ensures that data meets regulatory requirements consistently across jurisdictions, reducing the risk of non-compliance. 

• Operational efficiency: Consolidating data systems and automating reconciliation processes minimizes manual intervention, reducing costs and errors. It also reduces the time lag between capturing data on transactions in the operational world and being able to analyze and derive insights on this data as part of finance, risk or regulatory reporting. 

• Enhanced decision-making: With harmonized timely data, banks can deliver accurate, transparent, and up-to-date insights on all assets and liabilities, enabling more informed strategic decisions. 

In order to achieve these outcomes, banks must prioritize investments in technology to reduce the integration complexity between operational and analytical systems. Standardization efforts that focus on creating a scalable bank-wide harmonized data architecture can support both global and local banking requirements.

Building a path to transformation 

In the banking sector, where the pressure to innovate is matched by stringent regulatory demands, standardized data management is not just a technological challenge—it is a strategic imperative. 

SAP Fioneer provides a way forward. Financial Services Data Management (FSDM) is a business-centric solution designed for banks. It consolidates fragmented data silos into a central data hub, establishing a single source of truth. With FSDM, banks can reduce operational complexity and data redundancy to enhance efficiency, compliance, and strategic decision making.  

By addressing data complexity with FSDM, banks can begin digital transformation, stay compliant, reduce operational risks and costs, and position themselves for long-term success. Only by investing in standardization today can banks overcome data complexity and build a foundation for tomorrow’s transformation. 

To find out how SAP Fioneer’s Financial Services Data Management (FSDM) solution can help banks transform their data management landscape contact your account representative or click below.