May 17, 2020

How does governance minimise data complexity in the financial industry?

Data
Data governance
Financial industry
GDPR
Gary Allemann
4 min
Financial data
Data complexity

Most financial giants have been around for decades. Over the years, they have built up a complex array of systems, platforms and variou...

Data complexity

Most financial giants have been around for decades. Over the years, they have built up a complex array of systems, platforms and various other data sources which interconnect across multiple levels. These labyrinthine environments make it extremely difficult to understand what data they have, where it resides, and whether the data can be trusted.

With data being so dispersed and circuitous, using it effectively can be an onerous undertaking. Data is used for many reasons, from gaining better insights into customers and market trends, to improving customer experience, creating new or improved products/services and, of course, complying with regulations.

Making changes also becomes challenging if the impact of any change is not clearly evident or understood. A single change on one system could cause a chain reaction across other systems, affecting functionality and operations.

Adding to this complexity is the impact of regulation. Knowing where data resides, and its relevance and purpose to the organisation, are some of the requirements of the many regulations that financial institutions are obligated to comply with. These include the Financial Intelligence Centre Act (FICA), Know Your Customer (KYC), Basel Committee on Banking Supervision's standard number 239 (BCBS 239), Protection of Personal Information (PoPI) Act, and General Data Protection Regulation (GDPR) - the latter being requirements even for South African banks who are likely to count any number of European citizens among their clients.

See also:

Understanding governance

Although there is no single, one-size-fits-all approach, bank management teams can employ some underlying data governance principles and practices to more successfully collect, manage, protect, and deliver data throughout their organisations.

Data governance is vital for a business to sort through and understand what data it has, where it resides, create a strategy around it and carry it out successfully. One of the biggest challenges with data governance, though, is a lack of understanding around what it comprises. Many organisations confuse governance with the tactical tools and tasks it prescribes to manage data.

With automation becoming so prevalent in banks, it’s important to understand the business processes that their systems are trying to automate, and what data is required to support this. This is especially true of financial institutions where open source programs such as Hadoop introduce a new level of chaos into the fray. Governance introduces the rules and policies needed to create order from that chaos, giving the ability to focus, step by step, on using the right data to solve problems.

Proper data governance has more to do with managing people and their behavior than with managing data. Governance is about assigning accountability for the proper management and use of data. If the people within an organisation understand what data is for; who the right people are to access, manage and use it; and how to use it - then they begin to understand what data is actually useable, quality data.

Making it work

Banks are making significant investments in data science, with the objective of deriving better value from their data. However, without policies, processes and frameworks (data governance) in place, the complexity of their environments could derail the efforts of data scientists. To deliver value, data needs to be trusted. And to be trusted, businesses need a mechanism to identify quality data. Systems can only go so far. The rest relies on creating accountability and responsibility with the people; on creating a governance strategy which defines who is accountable, for what, and for what reason.

Governance is not a tactical solution, and it needs to be taken seriously if financial institutions want to build their enterprise view, understanding data at a global level. There is no value in adopting a top down approach which defines structures if the focus is so tactical that the solution provided is limited to single areas of business. It needs to be broad, addressing priority areas in alignment with overall business strategy. Then it can be broken down into bite size chunks, according to priority.

A framework is essential to ensure the success of master data management. Data governance provides that framework. It eliminated inefficiencies caused by too many people focusing on solving the same problem in different ways - and often a problem that can be more easily resolved if more critical areas are addressed first, in order of priority. Governance enables the business to prioritise, making data management more efficient, effective and, therefore, more cost effective, too.

Gary Allemann, Managing Director, Master Data Management

Share article

Jun 16, 2021

SAS: Improving the British Army’s decision making with data

British Army
SAS
3 min
Roderick Crawford, VP and Country GM, explains the important role that SAS is playing in the British Army’s digital transformation

SAS’ long-standing relationship with the British Army is built on mutual respect and grounded by a reciprocal understanding of each others’ capabilities, strengths, and weaknesses. Roderick Crawford, VP and Country GM for SAS UKI, states that the company’s thorough grasp of the defence sector makes it an ideal partner for the Army as it undergoes its own digital transformation. 

“Major General Jon Cole told us that he wanted to enable better, faster decision-making in order to improve operational efficiency,” he explains. Therefore, SAS’ task was to help the British Army realise the “significant potential” of data through the use of artificial intelligence (AI) to automate tasks and conduct complex analysis.

In 2020, the Army invested in the SAS ‘Viya platform’ as an overture to embarking on its new digital roadmap. The goal was to deliver a new way of working that enabled agility, flexibility, faster deployment, and reduced risk and cost: “SAS put a commercial framework in place to free the Army of limits in terms of their access to our tech capabilities.”

Doing so was important not just in terms of facilitating faster innovation but also, in Crawford’s words, to “connect the unconnected.” This means structuring data in a simultaneously secure and accessible manner for all skill levels, from analysts to data engineers and military commanders. The result is that analytics and decision-making that drives innovation and increases collaboration.

Crawford also highlights the importance of the SAS platform’s open nature, “General Cole was very clear that the Army wanted a way to work with other data and analytics tools such as Python. We allow them to do that, but with improved governance and faster delivery capabilities.”

SAS realises that collaboration is at the heart of a strong partnership and has been closely developing a long-term roadmap with the Army. “Although we're separate organisations, we come together to work effectively as one,” says Crawford. “Companies usually find it very easy to partner with SAS because we're a very open, honest, and people-based business by nature.”

With digital technology itself changing with great regularity, it’s safe to imagine that SAS’ own relationship with the Army will become even closer and more diverse. As SAS assists it in enhancing its operational readiness and providing its commanders with a secure view of key data points, Crawford is certain that the company will have a continually valuable role to play.

“As warfare moves into what we might call ‘the grey-zone’, the need to understand, decide, and act on complex information streams and diverse sources has never been more important. AI, computer vision and natural language processing are technologies that we hope to exploit over the next three to five years in conjunction with the Army.”

Fundamentally, data analytics is a tool for gaining valuable insights and expediting the delivery of outcomes. The goal of the two parties’ partnership, concludes Crawford, will be to reach the point where both access to data and decision-making can be performed qualitatively and in real-time.

“SAS is absolutely delighted to have this relationship with the British Army, and across the MOD. It’s a great privilege to be part of the armed forces covenant.”

 

Share article