Getting bank transformation right: Tips for modern data management implementation

A successful bank transformation requires a structured approach to address the challenges of data management modernization. The increasing need for enhanced decision-making, improved regulatory compliance, and greater operational efficiency has led to a pressing need for banks to modernize their data management frameworks.

However, implementing a modern data management solution is not simply a technology upgrade. It’s a fundamental transformation requiring that banks overcome integration challenges, secure organizational buy-in, and shift data ownership from IT to business users. The lack of proper data management can increase the risk of regulatory scrutiny and fines—Citigroup, for example, received $136mn in fines from US regulators after having failed to fix cited data weaknesses.  

How can banks ensure a smooth transition and achieve their goals in this data-driven era?

This article explores the key challenges and best practices to ensure a successful bank transformation by focusing on how to use a structured approach to implementation.

Overcoming common hurdles with modern data management 

Switching to a new data management platform like SAP Fioneer’s Financial Services Data Management (FSDM) is a complex undertaking that goes beyond simply installing new software. It requires a significant shift in how an organization handles its data and involves overcoming several interconnected challenges. 

Integration complexity 

Integrating a modern platform with many new and legacy operational systems and homegrown solutions can be daunting.

FSDM reduces integration complexity. Its business-driven out-of-the-box data model and standardized interfaces bring consistency, ensuring that data from various sources is represented uniformly.

Change management 

Banks will require strategies for securing organizational buy-in when adopting a modern data management solution like FSDM. Since FSDM is a comprehensive solution that spans finance, risk, and regulatory reporting scenarios, it can address multiple stakeholders within the bank. 

With FSDM also comes a shift in responsibility from IT to business users. The business side must take ownership of the data and become more involved in data management and the use of data for analytical scenarios across the bank. This will require an upskilling of leaders and IT staff alike. 

Another significant change is the need for a consistent business-driven process for data acquisition and data modeling that is owned by business users. This requires moving from an IT-dependent model to an IT-empowered model where both sides of the business can collaborate.

Best practices for implementation 

Implementing a modern data management solution like FSDM can leave banks wondering where to start.

1. Take an incremental approach

We suggest banks begin implementation with a single high-impact area or use case, like finance. Once banks implement one area, they can scale incrementally to the next, such as risk management or regulatory reporting. This incremental approach ensures data consistency because each phase has a clear scope and is carefully planned and executed in sequence where each increment builds out synergies for the next.  

With a consistent data model and no data replication, a customer beginning with accounting (e.g. sub-ledger accounting for financial instruments) will have integrated much of the data needed, for example, in credit risk management, once the accounting scenario is complete. This means that most of the data needed for credit risk management is already available in the FSDM solution. With this phased approach, a customer can realize substantial synergies in the implementation of finance, risk and regulatory reporting. 

 2. Define, evaluate and align goals

Banks can begin implementing FDSM in a stepwise approach by setting clear goals that align with the bank’s broader business objectives in the finance, risk and regulatory reporting area. This includes identifying the relevant goals and current pain points for the business and determining how they contribute to the company’s broader goals. 

For example, many banks with legacy systems and siloed data struggle to keep up with evolving regulatory requirements. This challenge is especially evident in Environmental, Social, and Governance (ESG) reporting, where banks must disclose data, such as emissions from counterparties or financed assets, that may not yet exist in their operational systems.  Without a consistent data model to capture and enhance this information in a single location, banks will find it difficult to provide reliable data for analytical applications like ESG calculation engines for “financed emissions”. 

The need for consistent data is essential for ESG reporting. Banks can set ambitions for ESG reporting early in the implementation process to identify and close data gaps, track progress, and make informed, data-driven decisions. 

The bank must continuously monitor and review their business goals, ensuring that they align with sustainability goals and evolving regulatory frameworks. This ongoing evaluation of goals allows a bank to adapt and maintain alignment with long-term ESG objectives.

3. Building out integrations in a step-by-step approach

With FSDM, banks can benefit from standard integrations to accounting, risk and regulatory reporting applications. 

For example, if a bank has already set up an accounting integration connecting FSDM’s operational systems to a subledger accounting solution, such as SAP Fioneer’s Financial Product Subledger (FPSL), this can serve as a foundation for expanding into areas like risk scenarios (e.g. market-, credit-, liquidity risk) or regulatory reporting.  

Because the bank has already invested in building an end-to-end accounting integration, extending this to cover, for example, risk or regulatory reporting scenarios will be much faster and cost effective. This is thanks to the consistent data model and integration patterns that can then be reused across all reporting scenarios, avoiding the need to build everything from scratch.  

Implementing modern bank data management 

Successfully transforming data management requires more than just selecting the right platform—it demands a strategic, phased approach that aligns technology with business needs. Banks that start with high-impact use cases, define clear goals, and leverage the benefit of a stepwise approach can reduce complexity, accelerate adoption, and drive long-term value.  

By embedding data ownership within the business and fostering collaboration between IT and business teams, banks can unlock new efficiencies and insights. With a disciplined approach, they can turn data management from a challenge into a competitive advantage. 

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 the link below.