What is data governance and why is it increasingly important for financial services?

Jay Reilly, SVP, EMEA at Precisely

Like many industries, the financial services sector has undergone significant development in recent years and continues to grow. In fact, according to research from Zippia1, the global industry is expected to be worth more than 28 trillion dollars by 2025. Financial institutions have also undergone significant digital transformations often promising to improve efficiency while enhancing the customer experience. An example of this can be seen with the shift to online banking, which, according to Finder2, around 93 percent of UK adults use in 2022.

Data governance in a nutshell

To keep up with the rapid change, it is becoming an imperative for financial services organisations to fuel business intelligence reporting with data that is accurate, consistent and contextual – data with integrity. However, while many organisations recognise both the benefits of effective data management, and the risks that come with hosting a vast amount of data, they do not always have an effective strategy in place. Data governance is a key factor in how organisations achieve data integrity.

The overall goal of data governance is to transform data into an enterprise asset, by aligning the people, processes, and technology needed to better understand it. It delivers visibility and understanding of data, and strengthens accountability for data assets, while enabling organisations to unlock analytical insights. Essentially, implementing a data governance programme can improve all policies and standards with regards to managing data, which ensures information is discoverable, trusted, and understood, while still being safe and accessible.

With privacy laws such as general data protection regulation (GDPR) in place, maintaining regulatory compliance remains a top priority for many organisations. Data governance can address this by helping companies track consent receipts, appropriate usage, and data subject rights requests. In addition, it ensures personal data location complies with data privacy laws throughout different countries.

Jay Reilly

Identifying business goals

One way to ensure a data governance programme is successful, is by establishing meaningful business goals ahead of time. A data governance initiative can support objectives by identifying key stakeholders and expected outcomes, while also measuring success with clear metrics. This enables companies to map data to the success factors, which align with the desired outcomes.

Some financial institutions, such as banks, often aim to improve the personalisation of products and services, to better fit the unique needs of each customer. Undoubtedly, there is an abundance of personal data within these establishments, such as card transactions, online bill payment records, and purchasing data which can provide information about internet browsing habits.

Once a business goal has been established, it is important for organisations to link data elements. For example, to improve personalisation, data governance goals need to be driven by a comprehensive and trustworthy view of each customer, which is available to everyone across the organisation. This requires giving employees access to a data catalogue, as well as clear data quality rules with approval workflows, and a view of data lineage for customer data.

A business-wide initiative

As well as establishing business goals, organisations should ensure the data governance initiative bridges the gap between business and IT metrics, across all levels of the organisation. Generally, this can be broken down into three tiers of personnel; the first is strategic personnel, who are responsible for visionary transformation at an executive level. Then, there is operational personnel, who oversee organisational execution and growth, and lastly, tactical personnel, who deal with data engineering, data migrations, and analytics.

Each level will approach the success of the organisation from unique perspectives. For example, C-suite executives will assess metrics which map overall return on investment (ROI) and business impact. This will include factors such as strategic goals around process enablement, customer sentiment, and financial results. Operational personnel will typically look for performance improvements related to response times and data quality, and those at the tactical level will focus more on granular metrics around data movement, performance, and effectiveness in cataloguing data for informed discovery.

Deploy data governance to solve problems and drive value

To achieve positive business outcomes on a strategic level, a data governance programme should solve immediate problems, while also addressing potential opportunities which add value to the business. For example, regarding the personalisation goal, data governance can immediately solve the centralised collection of customer data for sales and marketing teams. The ongoing opportunity it can address could be data profiling which adds depth and context to said customer data.

Another example is with financial organisations being responsible for managing investments and income, it is essential that businesses can make confident decisions based on data they can trust. Data governance is an important factor of a data integrity strategy, providing a comprehensive view of administrative, operational, legal and compliance expertise, as well as institutional, customer, banking, accounting, and portfolio information.

According to research from ReportLinker3, the global data governance market is expected to be worth more than three billion dollars in 2022 and grow to more than seven billion by 2026. Showing that business leaders around the world are recognising the significant impact data has on organisational growth. Going forwards, enterprises will need to lay down a solid foundation for data integrity, with data governance a key factor in driving meaningful business value.



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