Whether to tax data use or just data misuse

Ever since tech giants such as Facebook and Google began reporting profits with enough zeros to look like an accounting error, regulators have been keen to rein in any company’s ability to profit exponentially using a service which is purely digital. Their nervousness derives from the observation that platform companies – also referred to as ‘Software as a Service’ or SAAS businesses - don’t create as many jobs as companies with greater physical operations and often don’t have the same national tax bills or ties with specific regions or communities.

There is another cause of unease too: the idea that these profits are derived directly from personal data, often with no compensation or reward channelled back to the person whose data is being monetised. The argument has been building momentum and now it’s the subject of an escalating geopolitical tensions.

In 2019, France introduced a controversial ‘tech tax’, which it plans to implement from around the end of 2020.

The new tax will affect companies with a global turnover from digital activities of more than 750 million euros (about 1.15bn Singapore dollars) and a turnover in France of more than 25 million (around 38 million Singapore dollars).

When it agreed the tax, the French government told media that: "Today digital giants pay 14 percentage points less tax than European SMEs. The fact that these companies pay less tax than [small business] is a real problem”.

Although U.S. President Trump is fiercely opposed to the tax others in the U.S. have muted the idea of some kind of data tax there too.

Saadia Madsbjerg, Managing Director of the Rockefeller Foundation, published in the New York Times calling for a tax on personal data to be collected and reinvested in improving privacy of information on the Internet.

And earlier this year, in the U.S., Minnesota senator, Amy Klobuchar floated the principle of taxing large companies such as Facebook to curb their ability to profit off personal information without the owner’s permission.

Maybank suggests that there are three routes that lawmakers are talking about - or already pursuing - around the world.

First, there’s the idea of taxing companies as a way to somehow get money back to consumers when organisations monetise their personal details but as Maybank explains, this hasn’t progressed beyond an idea because of the difficulty of putting it into practise in a consistent way globally.

Then, there’s the concept of a tax to address the mismatch between how much tax small companies pay versus large tech giants who have set up operations in ways that minimise their tax bills – the French tech tax being the first example of this around the world.

The third and more immediate and actionable approach involves charging companies who misuse data - fining companies that breach privacy or show negligence collecting, storing or monetising personal information. This is the area Maybank is focusing on, because it’s the only known and quantifiable risk at this point. Maybank is encouraging clients to be knowledgeable on the regulations to avoid making costly mistakes.

Any Asia Pacific company doing business in Europe is already required to meet strict new privacy regulations for business conducted there. The policy is called General Data Protection Regulation or GDPR, and the penalties for breaking its rules are incredibly steep.

With 60 years of banking expertise, Maybank advises clients to manage, audit and protect their data as meticulously as they manage their financial records.

Effective data management usually requires an investment in systems and in qualified and experienced talent to manage them. When companies fail to digitise quickly, it’s usually because of the cost. 

Maybank helps clients to work through the level of investment required, to plan the timescale for returns on this investment and to assess the best routes for funding the digitisation roll-out or upgrade, which can vary depending on what they need. This includes helping them quantify the cost of not modernising their approach to data which is sometimes the most compelling driver to change.

As the FANGS* have shown in stark terms, getting a data strategy right can be enormously profitable.
(*FANGS is the umbrella term used these days to describe the major tech giants: Facebook, Amazon, Netflix and Google)

It has been estimated that personal data could be worth around $1000 per person per year to publishers but it’s impossible to be specific with this number as it depends on a pricing model which changes in relation to demand. It works like this: A news website that takes information from subscribers will hold a database on those subscribers’ demographics, for example, how much they earn, how many children they have, how often they travel for business etc.  Some of their subscribers will be more valuable than others. When they are selling ‘eyeballs’ through advertising to an airline, for example, they can charge more to guarantee 1000 impressions by high-earning business travellers than they could for audiences who barely travel at all. In this way, everybody’s personal data has a different value in different settings and to different advertisers.

The ongoing discussions around data tax are a signal from the future around the growing value of data and, allied to this, the growing importance to every business of sophisticated data management.

Some businesses lend themselves to greater data usage than others. However, Maybank advises all of our global clients to explore constantly how they could be collecting, managing and using their data more effectively to extract value from it, for themselves and for their clients.

Maybank concludes that there are three main ways that companies are finding value from data and they encourage clients to ensure they’re optimising all three:

• Making their own operations more intelligent and efficient by using data to guide decision making
• Improving sales through a more in-depth view of their customer
• Allowing their customers to enjoy a better experience; the process of buying something online is smoother when the online portal can for example, predict what a customer is likely to want and when it can automatically complete any form that needs filling in through the process

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