To my colleagues here in Bangko Sentral and to our resource persons today, good morning.
Welcome to our data governance seminar. As we prepare ourselves with the data governance seminar this morning, let me start with some food for thought:
It used to be that the problem of society is not having enough data and computing power. Today, what we are facing is clearly an abundance of data and almost unlimited computing power.
In a Forbes magazine article, internationally best-selling author and strategic business and technology advisor Bernard Marr notes that there are 2.5 quintillion bytes of data created each day. Further, 90% of available data across the globe was created only in the last two years.1
On the other hand, according to the World Economic Forum, the entire digital universe is expected to reach 44 zettabytes by 2020, roughly 40 times more bytes than there are stars in the observable universe.
Going by this, data is the new currency. Understanding of data as a strategic asset is now quite fundamental to every business and organization—the BSP included. In fact, in my recent policy pronouncements, I always say that the Monetary Board’s decisions are always data driven and evidence-based on market conditions.
Despite the significance of data, even highly technical and professional organizations still experience issues in data consistency, quality, and timeliness. This affects an organization’s ability to generate the data needed for high quality decisions and policies.
These seem to indicate that many organizations have yet to reach that point of being able to effectively harness the power of their data assets.
This is where data governance, our topic for today, becomes most relevant. DAMA, an international organization of professionals and standard setters in data management, defines data governance “as the exercise of authority and control over the management of data assets.”
Its purpose is to ensure that data is collected, processed, organized, protected, and consumed properly, according to agreed-upon policies and best practices.2 It is about determining data strategy and policy, defining standards for data quality and delivery, as well as establishing oversight and issue management processes. This is to ensure that the reliable and actionable data are received by the ones who need it, when they need it, and in the way they need it.
Thus, a well-functioning data governance structure should guide decisions made about data and how people and processes are expected to behave in relation to it. Too many times, however, this is left to chance or to operate within silos with different, if not competing objectives, sometimes to the detriment of the organization in general.
To establish a data governance program is to be able to exercise authority and deliberate control over data and, as a result, increase the value that can be derived from our data assets. Data governance need not be intrusive or invasive, and neither should it be restrictive. Instead, it should be designed around the best way data processes can support the delivery of our mandates.
Following the global financial crisis of 2007, the Basel Committee on Bank Supervision (BCBS) issued BCBS 239 covering the principles for effective risk data aggregation and risk reporting.3 These principles, issued in January 2013, aim to strengthen banks' risk data aggregation and risk reporting with a view to improving their risk management, decision-making processes, and resolvability.
One of the key takeaways from BCBS 239 is Principle 1. It is entirely devoted to governance, recognizing the importance of having a strong governance framework, risk data architecture and IT infrastructure as preconditions to ensure compliance with the other principles in the guidelines. The rest of the principles outline building data aggregation capabilities, reporting practices, and tools to monitor compliance.
While the guidelines are principally intended for systemically important banks, many of the principles may be ported over and applied to how an institution like our own should be governing our data for our purposes, even while we explore the applications of other generally accepted principles and best practices in data governance.
Our goal in today’s session is to jumpstart the definition of our data governance strategy. We have invited experts from the industry as well as the most senior data stakeholders in the organization to this workshop in order to accelerate our journey— because it will be a journey towards a more efficient and effective data governance in the BSP.
We believe that with active support of the Monetary Board and the Office of the Governor and the strong partnerships among the business users and the IT teams, we will be well on our way towards defining our data governance strategy and practices to address not only our present needs but also to position us well for our future data and information requirements.
2 DAMA-DMBOK to the Data Management Body of Knowledge, 2nd ed. DAMA International, 2017
3 Principles for effective risk data aggregation and risk reporting. Bank of International Settlements. January 2013. https://www.bis.org/publ/bcbs239.pdf