How Banks Can Turn Risk Into Reward Through Data Governance

Imagine, if you will, a 'junk' closet stashed to the brim with all manner of 'must-haves' that you supposedly couldn't do without. The purported essential nature of these items is a testament to the difficulty many of us face in decluttering. We agonize over trying to organize and decide what can be kept, thrown out, or even donated.

In many ways, this is analogous to data governance. Banking executives often lament that they have data all over the place but don't know where it is. This is followed by concerns that safeguarding data privacy feels like a losing battle, as the data they possess can’t be trusted. This really is a microcosm of why sound data governance matters.

Typically, data governance covers unearthing data, classifying it, setting appropriate guidelines and standards, and enforcing those standards with rules. Ultimately, this is to manage and govern data risk, but for most organizations, this feels like an endless task. All too often, individual lines of business will adopt their own data processes and standards over those created through a broader governance initiative.

This invariably results in hampered data quality. A recent HFS Research report found that 58% of respondents in Singapore and Australia felt that as much as half of their data was bad or not usable. Quite telling was the finding that while 80% of respondents from these two countries said they were confident in their data, only 60% of them could testify to its usability. What is needed, then, is a strategic approach supported by a set of processes that ensure banks are data-driven and agile enough to comply with regulations and deliver offerings that meet the expectations of diverse customers with different financial needs.

Data governance for changing times

To understand why data governance is critical for banks, we must understand the underlying challenges facing financial services organizations as they modernize. Rolling out new cloud applications or Internet of Things (IoT) devices into an environment where legacy on-premises systems are already in place means more data silos and data sets to manage. Often, this results in data volumes, variety, and velocity increasing much too quickly for banks.

This gives rise to IT complexity—driven by technical debt or the reliance on systems cobbled together and one-off connections. Not only that, it also raises the specter of 'shadow IT' as employees look for workarounds to friction in executing tasks. This can create difficulties for banks trying to identify and manage their data assets in a consistent, enterprise-wide way that is aligned with business strategy.

Ultimately, barely controlled data leads to errant financial reporting, data privacy breaches, and non-compliance with consumer data regulations. Failing to counter these risks can lead to fines, hurt brand image, and trigger lost sales. Arguably, more importantly, the financial sector is entrusted with the personally identifiable information (PII) of consumers, suppliers, and employees—failing to live up to this duty would erode confidence, which is a cornerstone of finance.

Indeed, there is an interesting trend emerging vis-a-vis trust in the financial sector. The latest annual Banking Trust Index for Singapore survey revealed that 74% of the public was confident that the industry could navigate current risks. However, as digital transformation continues, failure to coordinate data management across diverse stakeholders raises doubts about how long this confidence will last.

Boosting outcomes with a holistic approach

Overcoming these risks rests on having the right approach toward privacy protection while delivering consistent, timely, and accurate information that can be accessed at a moment's notice by business analysts. A holistic data governance framework should directly address the following:

• Regulatory compliance and risk management - Because banks are exposed to significant risks, the financial services sector is tightly regulated. By improving the quality and reliability of data, a comprehensive data governance framework aids adherence to regulatory mandates and minimizes compliance risks.
• Operational efficiency - The rise of disruptors in financial services in recent years can be attributed to the ability to harness structured and unstructured data from a wide range of internal and external sources. Upstarts like fintechs have upended the traditional landscape and can deliver diverse financial services faster than their legacy counterparts. To keep pace with these new entrants, banks need a clear strategy to boost operational efficiency by eliminating data redundancies, reducing errors, ensuring data consistency, and orchestrating efficient data processing. In other words, the hallmarks of a data governance framework.
• Customer experience and satisfaction - By ensuring high-quality, actionable data, a robust data governance policy allows banks to provide up-to-date, personalized services that enhance the customer experience. This, in turn, improves customer satisfaction and loyalty. Data governance also helps banks manage customer consent and preferences in compliance with regulations, such as the European Union General Data Protection Regulation (GDPR), by offering mechanisms to capture, store, and update customer consent preferences.
• Innovation and competitive advantage - When data can be reliably counted upon to be of high quality, there exists a solid foundation to identify new opportunities, analyze trends, develop innovative solutions, and gain a competitive edge. Armed with the ability to undertake advanced analytics, banks can drive innovation, as well as identify upsell and cross-sell opportunities.

Implementing a data governance strategy requires a systematic approach. Financial services organizations can enhance data governance strategies via AI-powered automation that enables full configuration so that data can be delivered securely when requested. These capabilities also empower financial services organizations to mask sensitive data via roles-based permissions, preventing them from being viewed by unauthorized users.

Through clear goals, a solid framework, and the power of automation driven by a low code, cloud-native, and unified platform, banks can position themselves to capitalize on the opportunities that emerge on the back of the digital economy. By being on top of data as it proliferates, banks can compete at ever-faster speeds, unlocking the flexibility and innovation to thrive.

David Irecki, the APJ director for solution consulting at Boomi, wrote this article.

The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/utah778