For financial institutions, the conversation around data has moved decisively beyond governance, reporting and regulatory compliance. Artificial intelligence, process intelligence and increasingly sophisticated client expectations are changing both the potential value of data, and the capabilities banks need to extract it.
At Standard Bank, Sibusiso (Sibu) Ngubeni is at the centre of that evolution. Having joined the bank in 2015, he now serves as Executive Head of Data & Analytics within its Corporate and Investment Banking (CIB) environment. During that period, he has seen data develop from a discipline primarily concerned with governance, quality and control into an increasingly strategic organisational capability.
“When I joined, much of the conversation around data was obviously focused on governance, and regulatory requirements,” he explains. Those foundations remain critical, but the focus has expanded towards a fundamental question: “How do we then turn this trusted data into organisational intelligence?” he asks. The focus is on building a common capability with local relevance, and the clarity, empowerment and accountability to resonate.
Turning data into digital organisational intelligence
The opportunity to derive greater commercial value from data is particularly significant because every organisation possesses a unique information asset. Even competing banks offering similar products do not necessarily possess equivalent data because individual clients interact with each institution according to different needs and relationships, notes Sibu.
Understanding that context can help Standard Bank’s relationship managers develop a richer understanding of their clients. At the same time also supporting the automation and redesign of complex processes.
However, Sibu cautions against interpreting legacy purely as a technology issue. There are legacy processes and, more importantly, legacy ways of thinking. Building an organisation capable of using AI at scale therefore requires more than introducing new platforms.
This becomes especially important when organisations consider whether AI itself can resolve their underlying data problems. As Sibu puts it: “AI does not inherently possess an organisation’s context. It needs to be grounded in trusted, contextualised information and data.”
Data leadership built on clarity, empowerment and accountability
Sibu’s approach to transformation is closely connected to his leadership philosophy. It was developed over 26 years of working life, around 20 of them in leadership positions. Three principles stand out: clarity, empowerment and accountability.
His experience as a junior software engineer taught him the importance of receiving clear direction. As a leader, he now seeks to provide that clarity to his own teams. Empowerment follows, but it must extend beyond simply assigning responsibility.
“If I as a leader trust people to do stuff, I should also give them the empowerment, give them the decision rights,” he says. That empowerment must be balanced by accountability. People who have the authority to act must also accept responsibility. For the decisions they make and the outcomes they deliver, he believes.