Importance of data governance in highly regulated industries

Rising interest rates, inflation, and a global economic decline have created a challenging macroeconomic environment. Recent data from the International Monetary Fund showed that five major Southeast Asian powerhouses, including Singapore, are expected to experience a protracted economic slowdown until 2024.

This slowdown will likely cause organisations to tighten their belts in anticipation. IDC’s poll of CIOs in December 2022 revealed that 49% are expected to reduce the ‘run’ part of the IT budget to fund new ‘build’ initiatives/projects in 2023. This shift in spending highlights the need for companies to double down on improving efficiency and optimisation. Organisations can enhance these areas by leveraging data to make better business decisions, inform quicker learning, and innovate more effectively.

Building foundation for accelerating data innovation

Sectors such as healthcare, financial services, and public institutions, all of which are subject to extensive regulation, all face similar challenges when it comes to using their data. These challenges include ensuring data accuracy, reducing time to value, and integrating disparate platforms and systems.

As an organisation’s insights are only as good as the data used, inaccurate or obsolete data can make it difficult to predict what lies ahead and make well-informed business decisions. However, if organisations can integrate disparate data sources and govern data regardless of its location, this can help eliminate data silos, prevent limited data access, and avoid bottlenecks in accessing data. An organisation with an effective data strategy can promote innovation, cross-functional collaboration, and gain a competitive advantage by harnessing data-driven insights.

Better data management can aid regulatory compliance by providing more granular insights in real time, a critical aspect of highly regulated industries. By leveraging data analytics, AI, and ML, organisations can better identify compliance risks, reduce reporting errors, and automate repetitive tasks, allowing employees to focus on higher-value activities.

For instance, PT Bank Rakyat Indonesia (Persero) Tbk (BRI), one of Indonesia’s oldest leading banks, used AI and ML to power its real-time fraud detection service called BRIForce. This automated the process of highlighting anomalies found in the stream of events coming from multiple customer touchpoints, reducing detection time from two months down to a few seconds. As a result, BRI was able to enhance its fraud detection rate and reduce fraud by 40%, helping the bank better comply with financial regulations.

To effectively leverage AI and ML, organisations must have granular control over large amounts of data across environments at scale. This requires modern data architectures that can efficiently manage metadata, data workloads, and applications across on-premises and cloud environments while maintaining control over data flows regardless of where the data resides. By achieving this level of control, organisations can enable consistent, secure, and scalable access and analytics of data while reducing data silos.

Therefore, developing a robust data strategy, analysing data to ensure compliance, and managing data in hybrid and multi-cloud environments can give organisations a competitive edge. Data governance is critical to maintaining harmony in these areas in the long run.

As the use of AI continues to grow globally, organisations — especially those in highly regulated industries — must ensure that their data governance practices promote compliance with privacy regulations and minimise bias, while also prioritising security and accountability in use cases. Deploying hybrid data platforms with built-in security and governance capabilities can provide a head start for organisations in highly-regulated industries, enabling them to securely and appropriately use data.

Improving data governance to seize opportunities and maximise resources

Without proper data governance practices, organisations spend more time verifying, cleaning, and processing inaccurate, incomplete, or corrupted data. These issues waste resources and prevent the organisation from scaling up its data efforts to harness advanced, real-time analytics, leaving them uncertain if they can trust the data to make decisions.

To achieve effective data governance, organisations must dismantle data silos and instil in employees the importance of the proper use of data. Senior management needs to be kept informed and convinced of the benefits of good data governance, so that they remain committed to building it across the organisation. Business leaders must act as stewards and play their part in maintaining good data quality, which should be held to an even higher standard in highly regulated industries.

One of the most effective and cost-efficient ways to implement good data governance is deploying a platform that has security and governance protocols built in. This centralised governance approach facilitates compliance and avails self-service data access for all users, while establishing a consistent layer of security and governance across all cloud environments and the organisation’s data-driven initiatives.

Having the platform function as a single source of truth enables traceability of data lineage, providing employees a clear view of the data’s entire lifecycle as they aim for maximum accuracy and consistency of data while also fulfilling regulatory requirements.

Better data governance, better business

Implementing strong data governance practices provides organisations with timely and accurate data, which is essential for deriving valuable insights. These insights enable organisations to quickly identify growing market trends and respond by reducing costs or optimising business processes. Proper data governance is also crucial for reducing regulatory risk, particularly as regulations become more stringent in the wake of business disruptions, which is a key requirement for organisations in highly regulated industries.

In addition to reducing time and costs spent on cleaning and processing data, effective data governance allows organisations to mitigate risks and ensure reliability as employees develop new business use cases. Most importantly, data governance enables organisations to gain foresight and maintain a competitive edge, even amidst today’s turbulent market conditions.