Unravelling the Gordian knot of accurate reference data

Article highlights
  • Managing Reference Data Amidst Lack of Standards: The absence of a single, global identification and transaction messaging standards presents significant challenges in managing reference data.
  • Unique Challenges of Post-Pandemic Home Working Model: The post-pandemic home working model has created new challenges in managing reference data, particularly with respect to the timeliness, security, and compliance obligations of data destinations and consumers.
  • Challenges in Unravelling Reference Data Gordian Knot: Key challenges in unravelling the reference data Gordian knot include the lack of consistency in data collection, storage, and usage across different organisations and industries.
  • The Importance of Data Management Strategy: Despite the complexities and challenges of managing reference data, it is crucial for financial firms to invest in resources, processes, and technologies that support greater transparency, operational efficiency, and regulatory compliance

This blog highlights a discussion point from FOW’s comprehensive eBook: “Reference Data: The Essential Guide”.

In the continuing absence of single, global identification and transaction messaging standards, the challenges of managing reference data are many and varied, since every data point may be subject to multiple interpretations – and indeed uses – in different contexts.

Effective data management is further challenged by a new, post-pandemic home working model that has created a whole new set of data destinations and consumers, with attendant timeliness, security and compliance obligations.

So what are the key challenges to unravelling the reference data Gordian knot?

1. Lack of consistency

Specifically, the absence of consistency in how data is collected, stored, and used across different organisations and industries, and the lack of clear definitions and processes for recording data or variations in regulations and requirements for different markets and jurisdictions. Even within an organisation, multiple data sources may lead to inconsistencies.

2. Complexity and volume of data

Managing the large and complex volumes of data. In addition to managing the volume and complexity of data capture, reference data also includes multiple layers of detail with respect to the type of asset, location, currency and counterparty, all of which must be correctly identified, categorised and maintained for use in their respective messaging field.

3. Cost and resources:

Another crucial challenge, particularly in the current global economy, is the cost and resources necessary to capture and manage reference data effectively and efficiently, and to implement appropriate data quality control, and validation checks and balances throughout the data lifecycle.

4. Technical hurdles

Technology challenges may also hamper efficient consolidation of data sets from multiple sources, systems and formats. Internal data management systems must constantly adapt and flex to accommodate growing data volumes, efficient distribution to multiple end points and real-time approvals, with associated system security and robustness checks and protocols.

Implementing a data management strategy

Regardless of the costs, complexities and challenges, financial firms have no option but to grasp the data management mettle with respect to ongoing investment in resources, processes and technologies that support greater transparency, operational efficiency and regulatory compliance.

In today’s regulatory-heavy financial markets ecosystem, it is more important than ever for financial firms to implement an efficient and effective data management strategy that optimises data sourcing and delivery efficiency, while mitigating any points of failure on its journey from sources to end destinations.

To find out more about reference data trends and challenges, download FOW’s comprehensive eBook “Reference Data: The Essential Guide”.

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