The most prominent trends in the financial services industry today all rely on data. Whether we are talking about operational resilience, digital transformation, or about Environmental, Social and Corporate Governance (ESG) transformation, data reusability is critical.
The concept of data reusability has been around for decades and is the essence of establishing a “single source of truth”. It is based on the premise that the extraction of data from the source system is supported by aspects such as metadata collection, data quality, data lineage, master and reference data management. It also requires that the data be stored centrally, allowing access to both human and non-human actors, so that the same data can be used repeatedly for various purposes.
This article talks about how data reusability impacts each of the 3 trends mentioned above. For operational resilience, this would take the form of using resilient technology, such as cloud computing, having a robust data quality framework in place to continuously test the data, incorporating situational awareness by means of database governors or AI-based analysis, and having the right metadata in place to ensure that the resulting information is both timely and relevant.
The objective of digital transformation, without doubt, is to generate additional value for the financial institution’s customers, stakeholders and shareholders. This article gives examples of how each of these types of value are influenced by data reusability. For instance, to democratize data and empower employees with self-service BI and analytical capabilities for better, faster decision-making, the organization needs to ensure consistency in results, which requires an enterprise metadata layer and enterprise data layer (data warehouse, customer MDM) to provide employees with consistent, clean data. Similarly, to ensure greater customer value, organizations need a ‘single view’ of the customer (Customer MDM), their portfolios (data warehouse), and advanced analytics to understand the customer needs and relationship lifecycle (good data quality).
When it comes to ESG transformation, financial institutions are still in the early stages and most customer data is still organized in a product-centric manner, which does not intuitively offer an understanding of the banks’ financial exposure to climate-related risks. Banks will need to create a single view of the counterparty across all holdings and associated Scope 3 emissions to understand and mitigate their exposures. Considering that most of this data is new, it will require associated metadata to be created, the quality understood, and this data will need to be integrated in some form of data warehouse and customer MDM to be reused across organization.
The article also delves into the steps for implementing a data reusability framework and touches upon some of the common roadblocks that organizations face in successfully implementing data reusability. Adastra’s experts have helped organizations of all scales and sizes implement end-to-end data management programs, including but not limited to data governance, master data management, metadata and reference data management, and cloud implementations. We offer complete stack delivery of all cloud-based solutions, including data warehouses and data lakes, and no matter which platform you choose, we can help you realize the benefits of data reusability.