An organisation's competitive advantage rests on many characteristics but big data has rarely counted among them – until now.

Google Technical Director, Financial Services, Ulku Rowe, says organisations that take advantage of the cloud and its new-found capabilities to analyse huge data sets are likely to be the winners in this new data-driven world.

"About 2.5 million terabytes are generated every day and I think financial services institutions are using only 0.5 per cent of that available data," Rowe said at a SIBOS 2018 session on disruption in the payments landscape.

"The winners will be the ones that actually understand that data, are able to turn that data into insights and knowledge because data in itself is not valuable, it's what you do with that data."

The potential benefits are enormous: insights from public information and shared data from private sources alone could unlock more than $US3 trillion a year in economic value, according to a McKinsey report

Westpac's corporate venture capital arm, Reinventure, has invested in several data-based FinTech firms including data exchange firm Data Republic, AI-powered data analyst HyperAnna and financial data aggregation platform Basiq.

"We have formed a deeply held belief that data is the single biggest lever for microeconomic and social reform in the next two decades and needs to be a material part of policy and trade consideration at all levels of thinking in the public and private sector," Danny Gilligan, co-founder and managing partner of Reinventure Group, wrote in a recent report about the global data opportunity. 

But it also raises a key question lurking behind big data for market participants, governments, regulators, and the public: how to strike the right balance between privacy and innovation?

Different approaches between countries as tussle between privacy and innovation continues

Big data and technology are quickly reshaping the world leaving many local regulations in their wake. 

Countries such as China lean strongly towards innovation, using a huge range of big data with little regard for privacy; while many European Union countries lean strongly towards privacy, with new regulations such as the General Data Protection Regulations (GDPR) and 'right to be forgotten' proving burdensome to tech companies. 

Australia has a more balanced approach between the two forces, having already enshrined a consumer data right and data sovereignty guidelines alongside plans for more open government data, a digital ID and open banking.
However, Australia’s regulatory framework for data remains archaic and lacks co-ordination across several regulators and government departments, according to Reinventure.

"Both this policy development and regulatory fragmentation should be contrasted with a model like Singapore which has evolved rapidly to a single executive branch for the data economy which has a paired model of accelerator (innovation, industry development) and brake (privacy, sovereignty etc)," Reinventure says.

By way of contrast, Singapore's IMDA (and its two sub-branches, the privacy-focused Personal Data Protection Commission and innovation-focused Data Innovation Programme Office) is leading a unified approach towards the country's goal of building the world’s first global data exchange.

Reinventure says the most likely outcome is that cross-border trade in data happens at the algorithmic level on common infrastructure, not at the raw data level, given data sovereignty and regulatory concerns. 

"The best parallel for this is SWIFT in banking, being a common infrastructure/approach to enabling cross-border flows in money/payments."

Big data innovations impress but still in their infancy 

This future data economy has many benefits, some of which are already starting to produce positive results for organisations and society. 

Companies are using data to make better decisions. For example, anonymised bank transaction data is revealing important information about the behaviour of Australians. Large shopping retailers are using this data to help select the best location for their retail sites or to optimise their mix of stores. 

In the public sector, Westpac has taken part in four government insight projects using bank transaction data for modelling and policy. Geografia’s Spendmapp, developed via Data Republic’s technology and ecosystem, for example, combined Westpac bank transaction data with population data, allowing local governments to measure the benefit of future projects.

However, many sectors of the economy are just beginning their big data journey.

For example, recent Productivity Commission research suggests that most superannuation funds collect just one of 10 key member traits, which is rarely used to design or price products. Meanwhile, more than 240,000 member records (8% of all records) still had core data errors, such as date of birth, at December 2016, according to industry estimates.

Most funds can learn more about their members
The situation is changing as funds begin to collect more personal data, setting the foundation for big data sets to be overlaid and deepen the industry's understanding of the behaviour of members in retirement. With more than $2.8 trillion in super managed on behalf of millions of Australians, the potential to boost retirement incomes is enormous.

But that may be just the tip of the iceberg given unanalysed terabytes of data are being generated every day across the financial services sector.
This article represents the views and opinions of the author and do not necessarily reflect the opinions of BPAY.
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