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The banking sector has undergone a rapid transformation in the last five years, making the role of Chief Information Officers (CIOs), who sit at the nexus between data and technology, more important than ever.
Several factors have influenced this tectonic shift:
The pandemic: The rapid shift to a remote workforce during the COVID-19 crisis caused individuals and companies to quickly embrace digital technology. Advances in banking technology helped drive the rapid growth of online banking, and new firms entering the online market caused the entire industry to respond to increased customer demands for easier ways to do their banking.
Data and risk: As digitalization has increased, the value of data and the associated risks in managing the large data pools that banks control, now have a much higher profile and priority for financial institutions compared to even three years ago.
Compliance: Engagement with regulators and the expectations around data privacy and data localization rules have also become much more heightened, particularly in countries where data sharing is highly restricted.
To meet these challenges, today’s CIOs must deliver the technological vision to:
Grow the bank’s core lines of business
Protect against financial crime and fraud
Connect and unlock the value of data
Ultimately, it’s about delivering data at scale and leveraging it safely to grow the business—a strategy that sits at the core of HSBC’s Technology Vision 2027 strategic plan. Implementing the ‘data at scale’ program is led by HSBC’s Global Data CIO Kai Yang, a groundbreaker in banking innovation.
Recently, we had a chance to sit down with Kai to discuss:
How technology has changed the banking sector
The value of data in growing a bank’s core business
The pivotal role CIOs play as transformational leaders
As CIO, Kai manages HSBC’s large data refineries, the data toolsets across the organization, and the large set of resources globally that service HSBC’s many lines of business and markets around the world. Like technology teams everywhere, Kai’s team of 3,000 people spread across HSBC’s technology centers, faces several key challenges:
Privacy versus growth: With the demand for data from the business increasing, and the expectation to manage the risk, the nagging question for Kai becomes: “How do you balance protecting the data yet enable the data to be leveraged to grow the business safely?”
Governance: With countries employing different rules and approaches to data sharing, HSBC needs to ensure it abides by data-sharing regulations across a wide range of nation-states, from a free flow of information in countries like Australia to much more closed environments.
Supply chain: HSBC has many large wholesale clients with footprints in over 20 markets. As their banker, HSBC needs to make sure it's providing the right data and insights to support these clients end-to-end across their supply chains.
Kai used shirt manufacturing as an example of the complexities banks face in assessing risk. Cotton to make the fabric might come from China, but it gets processed in Vietnam. The shirts might be made in Vietnam, but the head office is in the U.S. Their distribution network might be across retail shops around the world, which adds further complications.
"Until now, decision-makers didn’t always have a direct line of sight into their risk exposure to see all of the connections between their counterparties…and their counterparty’s customers, vendors, and suppliers.”
Global Data CIO, HSBC
This has left companies unable to truly understand:
Who are they doing business with?
Who are the extended counterparties of the counterparty they are doing business with?
Can they do business with this counterparty? (Do sanctions or other complications stand in the way?)
Do they want to continue doing business with this counterparty?
Where do the opportunities to develop new revenue streams, products, and services lie?
Having the ability to create a single, enterprise-wide view of people, organizations, and places, and deliver that at the scale and speed at which an organization the size of HSBC needs to be successful, has been the Holy Grail and is the foundation upon which HSBC and Quantexa have built their partnership over the years.
Quantexa’s Decision Intelligence (DI) Platform is a new generation of software designed to automate or augment processes – empowering operational teams like Kai’s to make faster and more accurate strategic, tactical, and operational decisions.
By harnessing the power of artificial intelligence, the platform can connect billions of data points across internal and external data sources to provide a trusted and reusable data hub that is enriched with vital intelligence about the interrelationships between real-world entities such as people, organizations, events, and places.
The open and modular platform provides outcome-driven solutions to:
Unify data by integrating any source at scale to build a trusted data foundation
Create context by revealing relationships and insights to create stronger analytics
Decide and act using augmented and automated decision-making for actionable insights
"Sharing the derived outputs from Quantexa between lines of business and front-line coverage teams… will help identify opportunities to follow up with our customers or approach potential customers.”
Global Data CIO, HSBC
Being able to see data “in context,” with the DI platform is one of the key ways HSBC has been able to fight financial crime, but it has also opened new doors to grow the bank’s core business by allowing managers to make better, faster decisions at scale regarding who they want to do business with and who they are doing business with.
Creating a single customer view is helping HSBC from both a bank and customer perspective by:
Being able to manage customer relationships across multiple touchpoints in multiple countries more easily.
Bringing data together, but also enriching it with external sources and registries, to add another dynamic dimension to the holistic, Customer-360 view.
“HSBC is uniquely placed where we have a presence across all those locations…and we should be able to help, using the entity resolution capability [and] single customer view, to better support our multinational clients and customers.”
Global Data CIO, HSBC
Entity Resolution allows HSBC to stitch datasets together in a trusted and highly visual way. Having a single solution also allows HSBC to build a deeper, richer set of data and provide much more breadth in terms of opportunities and the diversity of use cases. Analyses are also much richer, providing HSBC with the confidence within its business units to drive and accelerate its customer-data asset build-out.
Marrying this with the modern core capability that the bank is moving towards will ultimately enable HSBC to move from a batch-based process or product-and-service offering to a near-real-time product-and-service offering across HSBC’s omnichannel service offering, whether that’s in its call center, directly through branches, or through its digital channels.
While using the DI platform more broadly across HSBC is still in what Kai described as “the early stages,” the bank is already reaping the benefits.
“We are looking at a very broad range of use cases that it [the DI platform] can be applied to,” Kai explained. “Now, if I pare it back into the foundational capabilities—such as matching rule consistency, having a single set of governed approvals that we can trust and use to solve our datasets—it’s highly valuable across all our important business services and our customer journeys. So, foundationally, the value proposition is there.
“And even for us at this early stage, what we’ve just done is the conversion of our four different tools in this space into one. Picking the best of breeds and having our organization use the best-of-breed capability at scale, having a common tooling—is already reaping value by having our people connect. It’s not just data, but also people using the same toolset that naturally connects our teams in a faster way.
“Again, I think it’s still early days because we’re doing the transformation of our modern core and our Customer 360, and Entity Resolution is one of our underpinning capabilities,” Kai said. “But I’m very confident that there is a huge positive impact.
“The ability to underpin the digital journeys, both internal and external, with the consistency of our customer base is central to our banking strategy to better serve our customers. … And increasingly, this is the expectation, even at the more complex end of our relationship scale, for example, in our global banking and large corporate book. So it’s not just the retail book, it’s also our corporate and institutional accounts.”
As technology, data, and the need to meet new expectations from customers and regulators come together, having a sound data management strategy and a strong CIO to drive it is critical for banks that want to stay competitive. CIOs must also be empowered to scale their infrastructure to support their ongoing business needs.
"Every industry [and] every company is starting to realize that data is the actual asset of the organization.”
Global Data CIO, HSBC
“Whether you’re a financial institution or not,” Kai explained, “every industry [and] every company is starting to realize that data is the actual asset of the organization; not necessarily just the application, the CX/UX that you build from a tech perspective. It’s the actual [customer] data that you collect and act as a custodian of that is of value.”
“Having a data strategy that sits alongside technology is critical, because … up until now, if I looked at IT, it tended to be the little ‘i’ and the big ‘T.’ What organizations realize now actually, is that it needs to be a big ‘I’ and a big ‘T,’ because you need to take data [and] refine it into information and actionable insights. And the only way to do that is by having a very comprehensive data strategy. Just like you have a technology strategy, the two go hand in hand. But I feel like in the past five years the elevation of data, definitely in the banking world, has significantly accelerated, and it’s critical.
“Are Chief Information Officers now empowered to scale their infrastructure up to support ongoing business needs? Yes, absolutely.
“My team is accountable to deliver technology capabilities that enables the bank to better meet business objectives, address customer needs and also increasing regulatory expectations such as data privacy, and data sharing requirements in a more scalable and automated manner.”
Despite all that’s on his plate, Kai attacks each day with vision and a deep appreciation for those he works with.
“I’m a very vision- and purpose-driven leader,” he explained, “and the drive I have at a group level is to help the organization simplify and transform HSBC to be a digital-first bank, to deliver value for our shareholders, improve our customer experience, and create a better colleague experience by having better-quality data available.
“Now, from a data technology [standpoint], so wearing-my-CIO-hat perspective, my drive, if you double click into that, is about simplifying the bank’s data architecture, making our datasets to be reusable, and again, having actionable insights to better service our customers.
“And last but not least, if I look at it through a people lens, I’m passionate about leading my team. I love working with them, and I want to create an environment where innovation and engineering brilliance are rewarded and can prosper. So I think it’s those multiple dimensions that get me up every day to work probably too-long hours.”
The ability to bring multiple datasets together (converge data) offers three key benefits to HSBC as Kai explained.
First and perhaps most important, reducing duplicative technology capabilities in data saves money, which allows every dollar invested into technology to go further. In HSBC’s case, four tools are now combined into one with Quantexa, which provides cost savings and improved efficiency.
Convergence of data provides HSBC with a much richer dataset across all its lines of business and it is available in a much more timely and relevant manner. This results in a much richer understanding of customers.
As Kai explained, “If we can approach a director of a large wholesale client of ours, they might be very suitable to become a private client or private-wealth client of ours as well. Leveraging that convergence of data to recognize both sides of the wholesale and our retail businesses and service offerings, that’s one of the other key benefits.”
One of the things that has come out of the convergence work that Kai and his team have done so far is that it has highlighted a lot of the data-quality issues and deficiencies upstream from the data refineries that need to be fixed.
This was a great surprise for his team. “That visibility,” he explained, “that visual visibility of the [Quantexa] tool, allows us to have a much stronger mandate to the front-line product system owners to say, ‘Do we believe it’s in our customers’ best interest that we fix those data-quality issues?’”
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