Leading practices for modernizing data governance for growth: What your organization needs to know

With shifting customer needs and demographics and the rapidly changing environment within the financial services industry, digital transformation is becoming more and more important. Now more than ever, banking institutions are focusing on enhancing customer experience, improving real-time decision making and implementing new technologies to gain a competitive advantage. In order for these changes to have a positive impact on your organization, it is important to analyze your current processes and systems, and take control of your organization’s data. Here are three key indicators that show the need for a new data strategy:

• There is a lack of understanding where all customer/institution data resides within the organization
• There is a lack of centralized data and/or a heavy reliance on manual processes to move and/or combine data from various systems
• Data is siloed within various departments across the organization

Proper data governance will give you oversight over the availability, usability, integrity and security of your data. Any organization that wants to go through digital transformation or evolution needs to ensure good data governance i

The role of data governance in digital transformation is essential and should not be underestimated. A sound data governance system is critical to manage data assets, ensure regulatory compliance and drive business growth and innovation. However, traditional data governance frameworks make it difficult to utilize data due to outdated policies and/or systems. The solution lies in developing and implementing an adaptive data governance system, which ultimately opens your organization up to a flexible framework that can respond to ever-changing business needs, the regulatory environment and new innovations.

Evaluating your current data governance structure can be broken down into four key phases:

• Phase 1 – Assess: An effective process must occur in the context of your organization. Begin with an understanding of the current organizational and decision-making structure
• Phase 2 – Envision: All programs need a solid charter and set of objectives to be successful. In this phase, set the vision and document it into the project charter and key objectives
• Phase 3 – Plan: All execution should start with a solid plan. Anchoring back to the project charter and objectives, in this phase, set key roles and responsibilities as well as identify the organizational model best suited for the data governance effort
• Phase 4 – Build: In this phase, work to create the steering committee, inventory, risk framework and policies and procedures that will be the foundation of the data governance program

Once established, to be successful your organization’s adaptive data governance program should be collaborative across all facets of your business, able to grow as you grow, proactive and agile.

Once you’ve established an adaptive data governance program, you can then analyze the tools your organization is using and focus on transforming them to promote a culture for effective data usage. Organizations cannot go from standard, operational reporting to automated decision-making overnight once their data governance program is in place. It takes time to gradually mature your data and analytics capabilities. To promote a culture of effective data usage across your organization, you need to:

• Choose the right data: Don’t make all of your organization’s data available to everybody in every department. Choose the right data for the role or audience that you are trying to communicate with
• Build a data-driven culture: From executive level down, hold people accountable to prove that they are taking initiative and whether their performance is driven by data or other factors
• Modernize your data architecture: Once your data governance framework is established, you are then able to implement the latest tools within your organization
• Embrace technology and data literacy: Teach your stakeholders how to use the newly implemented tools and technologies in order to reshape how your organization accesses, manages and acts with data

There are many opportunities for transforming your organization’s use of data, but there are also changing regulatory requirements and cybersecurity considerations to keep in mind. In addition, considerations for AI continue to evolve rapidly and are increasing the focus on data quality and overall governance.  There will always be a continued focus on protecting sensitive data, especially in the financial services industry. Cybersecurity requirements and regulations are becoming more complex as organizations embrace new technologies like artificial intelligence and machine learning. It is vital that you consider how your organization is protecting sensitive data, what incident/breach response practices you have in place as well as your association with external vendors and third parties. 

For a more in-depth breakdown of the evolving cybersecurity and compliance landscape within the financial services industry in 2024, refer to our article on the subject.