How can Australian companies gain a competitive edge using big data?

When used well, big data and analytics can deliver great insights to organisations, enabling them to identify opportunities, make informed decisions and improve customer outcomes.

In the third event of HSBC’s virtual Think Bigger Innovation Series, technology leaders from Xero, Mastercard and HSBC talked about some of the amazing ways they’re leveraging big data – and why it’s important to give customers a say in how their data is used.

As many of its customers struggled to stay afloat during the COVID-19 crisis, cloud technology firm Xero empowered them to use their data and take advantage of the JobKeeper program. The government wage subsidy scheme offered small businesses a much-needed lifeline, but many of Xero's customers didn't know how to use it or whether they were qualified.

“We built an eligibility test right into our actual accounting platform, so a small business owner could tell straight away if they were eligible for JobKeeper or not,” said Trent Innes, Xero’s former Managing Director for Australia and Asia.

“And then, more importantly, we made it really easy for them to access that stimulus program,” added Innes.

Like Xero, HSBC has taken advantage of big data analytics to create more value for its customers. Using the Liquidity Management Dashboard on HSBCnet, businesses get an aggregated view of their available cash globally in any currency of choice, giving them greater visibility of their finances. Now, they can gain even more insights with HSBC’s new Cash Flow Forecasting tool. The tool provides businesses with a forward-looking view of their cash flows based on a combination of historical trends and expected payment flows, enabling them to better manage their finances.

Mastercard has also added value to customers and improved its results using big data analytics. By embedding artificial intelligence (AI) in its credit risk scoring and decisioning platforms, the company generated $20 billion in savings that it would have otherwise lost to fraud.

“So we’ve prevented fraud through the use of AI-enabled systems that we’re able to make available to our customers,” said Mallika Sathi, Mastercard’s Vice President, Cyber & Intelligence Solutions and Digital Identity.

While big data analytics can greatly help improve customer outcomes, businesses have to make sure their customers understand how their data is being used.

"We have high levels of knowledge around data and how it might be used. Unfortunately, that’s not the case for the average customer,” said Innes. “So, there is a large amount of education that still needs to go on.”

And as concern over data privacy grows, it’s critical to establish customer trust, according to Innes. “How do we best utilise data to actually really impact customer outcomes? I think a lot of that is built on foundations of trust,” he said.

“If you take a very customer-centric view of data privacy and the way you use data, that should lead you in the right direction,” added Innes.

Sathi agreed, noting that customers have the right to communicate their preference about holding or deleting their data.

“And that’s where the regulations are heading around the world,” she said. “So in the AI models that we build, we want to make sure we limit bias wherever possible.”

Mastercard has access to an enormous depth of payments-related data as it handles 75 billion transactions a year. To gain new learnings, Mastercard processes its data in a way that protects customer privacy.

“It’s about cleaning up that data, picking the components that are meaningful, augmenting that data – and aggregating and anonymising it. This is really, really important to make sure privacy considerations are taken into account,” said Sathi.

“So only when we have that aggregate level of data do we extract some insights.”

Just like Mastercard, HSBC handles massive amounts of data worldwide across more than 7,000 software applications. To get this data into a usable format, the bank has built a reference architecture and ensures any data it uses aligns with that architecture.

“It means any data source is only moved to a cloud once and used many times, and that brings consistency of usage,” said John Doman, HSBC Australia’s Chief Information Officer.

To use data more effectively, HSBC has run proofs of concepts and implemented machine learning. Recently, it has been working with a cloud service provider to focus on a single machine learning workbench.

“That means all the IP [intellectual property] you put into creating machine learning can be reused. Once you start doing machine learning, a lot of it is specific to the subject, but once you get more consistent data sources, reuse levels become much higher,” said Doman.

“These strategies help make sure our data is secure, is consistent and is available.”

HSBC has partnered with Mastercard and PayTech to provide Mastercard B2B Analytics (MBA) to valued clients. MBA is a Mastercard commercial card optimisation tool and support service that enables clients to identify opportunities for consolidation and efficiency in their accounts payable data.

One remarkable data-driven innovation that’s helping businesses make smart decisions is bank feeds. These feeds are automatically generated lists of bank account transactions that are typically integrated into accounting platforms.

Millions of these transactions automatically find their way to businesses’ accounting records.

“Why that’s so important is, it gives a small business owner real-time insights into what’s happening in their business,” said Innes.

“HSBC is a great example of a bank that provides automated and timely feeds,” he added. “Businesses don’t have to wait for the end of the month or quarter, or even worse, to find out their actual financial position.”

Keen to learn more how leading Australian businesses are innovating? Read our other Think Bigger Innovation Series articles and visit our Think Bigger website to see how HSBC can help your business achieve its ambitions in Australia, in Asia or globally.