Tapping into data management and data lineage strategies for Banks and their Global Capability Centers (GCCs)

Data lineage is emerging as a vital tool for banks and GCCs to ensure transparency and trust.

In brief

• Regulators have been demanding banks and their Global Capability Centres (GCCs) to demonstrate data quality and accuracy for effective and comprehensive risk management.
• Banks and their GCCs are undergoing a transformation in how they perceive and manage data, reforming data lineage as a key strategic enabler.
• This article explores key aspects of effective data management and discusses how data lineage in banks can evolve to integrate with governance, technology, operations, and organizations’ culture. 

The journey from financial resilience to data maturity, is shaped by the aftermath of the 2008 financial crisis that underscored gaps in banks' information infrastructure—particularly their inability to understand, aggregate, and trust their own data. This had given rise to frameworks such as Basel Committee on Banking Supervision (BCBS) 239 which emphasized the need for effective data governance. Over the years, while banks have been developing their data infrastructure, regulators’ concerns over data accuracy have persisted, primarily due to the reliance on manual interventions, legacy siloed systems and inadequate quality controls.

The focus for banks continues to be effective data management including data quality and data governance. Effective data management involves establishing consistent standards, comprehensive metadata management, and close collaboration between IT, business units, and data leaders such as Chief Data Officer (CDO). The CDO and data stewards play a pivotal role in driving data initiatives and fostering a culture that values data as a strategic asset. A well-executed data management program supports transparency, integrity, and trust by incorporating practices such as maintaining comprehensive data dictionaries, documenting data lineage, and implementing strong data quality controls. For banks in particular, such governance is critical—especially for data used in key business processes or reports where inaccuracies could pose financial, regulatory, or reputational risks.

Data Lineage: The journey behind the numbers

Decoding data lineage involves understanding the journey of data as it moves across systems, undergoes transformations, and supports key business outcomes. It is not simply about tracking origins and destinations; it is about understanding context, logic, ownership, and evolution. The shift from a purely IT-focused approach to a more holistic enterprise view can be transformative.

In an era where data drives decisions, banks can no longer afford to treat data lineage as a compliance hurdle. It has evolved into a strategic capability—essential for trust, transparency, and transformation. By capturing not only where data travels but how it is interpreted, governed, and applied, lineage becomes a critical enabler of both compliance and agility.

The following section highlights the themes around data lineage that have been explored in greater detail in our report, End-to-End Data Lineage: Building trust and powering reliable reporting. 

The path forward for banks involves actionable, collaborative methods—embedding unified governance, leveraging scalable automation, and crafting intuitive documentation strategies. The central theme is accountability across the board: a unified approach that dissolves barriers between technical and business domains and encourages a shared stake in preserving data clarity and trust.