Data & AI

Are regulations a burden or a benefit in the financial sector?

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When you see an updated set of data privacy regulations, what is your first reaction? Despair or frustration at having to comply with yet more bureaucracy? Or curiosity about how this could benefit your organization? Which mindset do you think is the most successful in the long run in the FSS (Financial Service Sector)?

When it comes to considering the correct approach for handling data governance, AI and other technologies are frequently mentioned. However, the FSS still has work to do to be able to fully understand and document how models are created, deployed, and managed in order to be fully compliant with new regulations concerning data.

 

Putting regulations into practice

When implementing data regulations in the financial service sector, data governance is key for ensuring that the organization’s data is gathered, stored, processed, and handled correctly. This is achieved by asking a series of questions that formulate the pillars of data governance:

• Is this the data that I need?
• How relevant is this data?
• What is the quality level of this data?
• How should I manage this data?

These pillars also form the basis of any focus area in regulations that consider data, which means organizations with good data governance find compliance easier.

 

Business benefits for compliance

While the financial service organizations that are successful when it comes to handling new regulations are those who look at the regulations as an opportunity to optimize the way their organization operates, the most successful organizations go a step further. These organizations simultaneously implement the regulations and tackle a business problem that helps to reduce costs or increase revenue in some way.

To give an example, a multinational banking and financial services corporation with activities throughout the Benelux developed a platform to support their business users and simplify their work processes. The corporation focused on the needs of their business users, rather than from looking at the situation from a regulatory or IT perspective. The banking corporation discovered that their business users spent a lot of time searching for data, especially data that is correct, relevant, and of good quality. By paying attention to delivering the right data, the banking corporation simplified their internal processes and reduced the time needed to find the required data, as well as meeting their regulatory requirements.

Discover more about IBM’s solution by watching a 15-minute webinar >

 

Data governance in the FSS

Data governance is becoming increasingly essential in the FSS to help organizations remain compliant within a highly regulated sector. However, that is not its only role. As a data or AI platform, it supports the organization and their processes, adds value to the organization’s activities, and helps the organization to prepare for the future.

 

How to get started with data governance

Are you interested in learning more about the importance of a sound governance foundation? If so, read our blog > on Data governance: The importance of a modern machine learning knowledge catalog.

Or if you have an idea about how your organization should tackle data privacy and regulations, contact IBM to discuss a discovery or strategy workshop to further develop your idea or arrange a MVP (Minimum Viable Product) to prototype and test your idea.

 

Executive Analytics Architect, IBM

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