Data is currency. It undergirds everything in our economy. In the banking days of old, money used to be stored securely in a vault. Today, our money is no more than numbers on a screen; bits and bytes, protected by firewalls and multi-factor authentication (MFA). The financial services industry, like all other industries, has been forced to adapt and change with technological innovations. But change isn’t easy, and adapting has also meant dealing with legacy infrastructure and a culture of “that’s how we’ve always done it.”
As data gradually replaced tangible assets and manual processing, most financial institutions never really treated it as its own pillar or division, worthy of executive guidance and strategic planning. Instead, it was handled piecemeal by various existing groups without a strategy for the organization or for most of the financial services industry.
The industry needs to build a healthy data culture.
What is a data culture? As many financial services organizations haven’t had to intentionally define their data culture, it has grown and developed more organically. This means that data has been used in an ad-hoc way. For example, when reporting is needed for a specific business unit, an environment to support that gets spun up. Without guidance from the enterprise, it is reliant on that business group to set expectations for security, privacy, master data, and metadata usage (among others). When that happens across an organization, there are different expectations in different silos and no emphasis on data sharing or using data in a strategic and efficient manner.
This contributes to a culture of data fiefdoms, where people protect what they have built. This siloed approach creates an organizational culture that becomes a roadblock to efficiently leveraging data for daily tasks, let alone for realizing the business value it can provide. Building a more formalized data governance function can help move from a fiefdom to collaboration culture and promote an efficient and controlled approach to harnessing data throughout an organization.
Data governance program
There are several data management frameworks that are useful in understanding how to approach the identification, use, and sustainability of data in a financial services organization. As you can see from the DAMA Data Management Framework pictured below, there are many functional areas that must be considered when trying to control data. The Data Governance program is responsible for promoting data culture and creating data strategy, policies, standards, and procedures around all data functions.
A strong Data Governance program needs a dedicated executive to advocate for having a culture that enables access to data based on defined rules. This will help break down data silos and provide management support needed to enforce the rules. Without management support, the siloed culture will continue. One of the difficulties of a siloed environment is the amount of pushback that occurs when someone wants to access a data source. The best way to combat this attitude is to have a centralized function that sets access rules based on data classification and the specific business needs of the requestor.
A data strategy engages stakeholders from around the organization and uses their diversity in background and knowledge to develop a strategy based on their business goals and a roadmap of how to get there. The strategy should include people, process, and technology components and be thoughtful in its implementation approach. Key business drivers (Regulatory Compliance components, for example) might need to be implemented prior to other areas that might not be as urgent.
The Data Governance Program is responsible for leading the development of the data strategy, but it also relies on other functions around the organization for implementation. This makes it crucial to build good working relationships with those functions to gain buy in. A good data strategy should also be revisited regularly to ensure it stays aligned with business goals and technological advancements.
Roles and responsibilities
Developing the Data Governance organization also necessitates defining roles and responsibilities. Each organization must tailor its roles to what makes sense, given the size and complexity of the company. But generally, having defined roles like data stewards, data councils and committees will benefit the organization by formalizing responsibilities for managing and governing data to ensure the strategy is implemented across disciplines.
As financial services organizations, and the economy in general, become increasingly dependent on data, it is critical to ensure that data is properly identified, organized, secured, and governed across the board. Creating a solid data governance foundation will reduce risk while also increasing the ability to harness the value of data to drive business results.