Question everything in the age of information

Whether you describe it as currency or an asset, there’s no escaping the value of data to the financial services sector. Its an industry driven more by data than perhaps any other, making the impact of big data on these institutions hard to overestimate.

Banks hold vast amounts of customer data, from purchases and cash withdrawals, to KYC data and the sources are ever increasing when we include things like mobile payments, app data and the IoT (Internet of Things).

With all of these streams of data continuously flowing into the business, an opportunity presents itself to gain insights and act on them. Whether that action is to create an edge over the competition, improve products and services, or improve customer loyalty, each is using data to fuel business growth.

Where we’ve come from and where we’re going

Traditionally banks have held this information in siloed systems, separated by product or purpose, meaning the data could be unstructured and difficult to harvest valuable insight from.

Over the past few years we have seen improvements and investment in data collection and processing, in particular within data warehousing and business intelligence. Institutions have realised that by bringing all of this information into one place they can use it in a more effective way.

With this change, as well as changes to customer behaviours, industry standards and regulatory requirements, a new challenge presents itself: Data Governance.

“Digital Transformation” – once simply the buzzword of the week, has proven to be anything but that. It’s now a priority on the agenda for almost all financial services institutions so they are able to meet customer expectations and compete alongside the small but successful fintech companies.

In order to be successful in Digital Transformation and start to exploit data assets, good data governance is non-negotiable. Businesses want to take advantage of new technologies such as machine learning and AI, which each depend on clean, quality data.

Getting data-governance right has an impact across the whole organisation, from being able to leverage market opportunities at a management level, to finance reports being consistent and accurate, to understand the customer and market to them more effectively, and of course meeting the regulation requirements for compliance and legal teams.

Plain and simple – good data governance makes everything better.

What does successful data governance look like?

In building a data governance strategy, there are four pillars to consider that will go a long way towards a successful program, allowing for better use and management of technologies such as cloud, machine learning and AI.

The four pillars are:

• Collaboration
• Speed
• Data Privacy and Protection
• Scale

Now we know what they are, let’s look at these pillars in slightly more detail.

Collaboration

When it comes to data governance, communication is key, without which no one knows what best practice looks like, what workflows, infrastructure and architecture are in place and no one would understand the goals of the project.

Keeping everything in one place, that single shared resource (if there’s a benefit to your data in one place, take the same approach to your documentation), helps facilitate collaboration across all stakeholders involved in a data governance project.

This will support aspects of your project such as audit trails, processes, guidance and project ownership.

Speed

Any IT professional or project manager will tell you, one critical aspect on any project is momentum. As soon as things start to slow down, you can hear the sighs coming from the projects team as they try to keep everyone moving.

In order to implement a successful data governance program, organisations need to be agile and adaptable, otherwise the project risks losing the efficiency benefit that data governance is there to facilitate.

Making use of AI and automating processes can take a lot of the manual tasks away from your teams’ workload and allow them to focus on more high-value, insight driven efforts.

Data protection and privacy

Cybersecurity is level 1 priority, security breaches are at an all time high and customer demand for control of their data (as well as trust in the organisation that hold it) are all pressing concerns for financial institutions.

Part of successful data governance is being able to protect data wherever it is and easily identify what protection sensitive data should have, so that your safeguards and processes meet the expectations of both customers and regulators.

Scale

We mentioned agile in relation to keeping momentum on projects, and it is applicable here too.

Often organisations will start a small data governance project and scale up as required in order to meet digital transformation goals and roll out the program across the whole enterprise.

Being able to take advantage of modular systems means that when you’re trying to get investment buy from management for data governance projects, you can also start small with the technology you use and grow with demand.

What next?

As data continues to pour into every financial services institution daily, being able to deliver on successful data governance is moving from a desirable “we’ll do it next financial year” to a key priority for businesses.

Customers are increasingly looking for the “best of breed” across all purchases, and banking and finance are no exception. Companies must implement a data governance program that can support them in this changing landscape, or risk getting left in the dust of competitors.

CACI work with institutions across financial services to help build and implement data governance and other data technology solutions. Click here to find out how we could help your business.