Opinion

From fintech to techfin: data is the new oil

By Janos Barberis

At the closing session of the 17th Asian Banker Summit, Janos Barberis, founder of FinTech HK, discussed the power of data to transform financial technology and why China will lead the world in financial innovation.

When I arrived in Hong Kong slightly over a year ago to build a fintech accelerator, I knew three things.

First, inspire my generation to join or build a fintech company. So the accelerator I founded had an Apollo programme vision. Second, adapt myself to Asia, accepting that financial brands are global but financial behaviours are local. So I aimed for locally anchored sponsors such as Tsinsghua University and Baidu. Third, embrace the fact that China will lead the world in terms of innovation. And therefore started the idea of a fintech silk road, facilitating Chinese company to scale out.

However, I wasn’t prepared to fully appreciate the difference between fintech and techfin. To me it was all about establishing a fintech hub, developing a fintech regulatory framework and measuring fintech investment growth. Yet when I spoke to start-ups in China they kept telling me they didn’t consider themselves fintechs. But instead were techfins. I thought it was splitting hairs and miscommunication but it was more than that. It was misunderstanding.

We often quote Jack Ma for saying, “There are two big opportunities in the future financial industry. One is online banking, where all the financial institutions go online; the other is internet finance, which is purely led by outsiders.”

We have read reports on China’s leadership in fintech. Ant Financial valued at over $30 billion after a series B round. Tencent facilitating over eight billion red envelopes to be shared in a day, up seven billion compared to the previous year. We know these facts but do we understand them?

Let’s forget the “fin” and focus on the “tech”. What does best available technology do? Breaking down what the “BAT” does we essentially have: 

  • Baidu connects people with information
  • Alibaba connects people with products
  • Tencent connects people with people 

 Each of these companies has hundreds of millions of users, and for them, fintech is just a commoditised layer that is used to enhance their core product.

Baidu can better sell information by letting you not only search for your favourite restaurant but also handle the reservation of the table, the payment of the menu, and the taxi ride back home.

Alibaba can better sell products by facilitating express checkout via Alipay and can facilitate the number of products available by financing the SMEs that it knows will sell.

Tencent can better connect people by splitting bills in a restaurant via WeChat Wallet or reconnecting families millions of kilometres apart during Chinese new year simply by digitising red envelopes.

I can give you many more examples with other companies that I have met—from an electric car manufacturer to China’s largest online dating platform.

Each of this fintech layers within their products is incredibly valuable and valuated. Yet their growth is finite. There are only so many friends you will have, restaurants you will search, and products you will buy. However, what is exponential is the information around your decision. What is valuable is not just the content—the data—but the context, the metadata. It is then that I learned the source of my misunderstanding.

Money has been digitised and now data is monetised—this was my Eureka moment. Whilst the first part is about fintech today, the second is about techfin tomorrow. So let’s look at the consequences this has for our industry.

Let’s break down the opportunity of techfin across two sectors that have been said to replace banks: Internet service providers (ISP) and e-commerce platforms.

We often draw parallels between telcos and banks. Both laid the infrastructure and risked to become dumb pipes to the internet 2.0 companies like Facebook. Let’s stop and think what flows in these pipes. Data. Data that if properly understood can generate money. AOL increased its revenue by $300 million (50% increase in one quarter) "just" by adding data analytics from Verizon to its ISP business.

What about e-commerce platforms? Sesame Credit in China is now used not just to originate loans but instead sell you nonfinancial products and services. Your credit score is an asset that can be traded for a better service. And the BATs are brokering that. They make money by taking a fee on selling a better hotel room as opposed to posting more regulatory capital for originating a loan. In both cases they used the same credit score.

Fintech to techfin represent a shifting trend that China has already leapfrogged. We are going towards a new industrial epoch coined by Professor Klaus Schwab, who designated it the “Fourth Industrial Revolution.” According to his book, the previous three eras had the following as juncture points: first, 1784 with the creation of the steam engine; second, 1870 marked by the introduction of electricity; and third, 1969 signified by the rise of communications and IT systems.

Today, we are entering an area of data analytics and artificial intelligence. These in turn transform data from being simply a byproduct of human interaction into a core commodity for economic growth. Data has been designated “the new oil” because it pushes companies to find, extract, refine and monetise it.

We are indeed at the beginning of a new cycle simply because less than 1% of the world's data is analysed, and over 80% is unprotected.
Let’s start with data protection. From a regulatory perspective, this creates a direct challenge. Data privacy laws were designed with humans in mind.

However, today, this is irrelevant.

As for data analysis, deep learning is the new enabler. We all heard about Alpha Go beating world champion Lee Sedol. This is fascinating; however, not fully disruptive.

The exponential growth in data analytic capabilities and the reduction in costs to produce them:

  • Deep Blue was the IBM program started in 1985 that beat Garry Kasparov in 1997 at a cost of 5% of IBM revenues 
  • Watson beat the world’s best Jeopardy players in 2011 at a cost of $1.8 billion
  • Deep Mind is the start-up behind AlphaGo, acquired for GBP242 million in 2014.

If you want to run Watson software, irrespective of licence cost you will need a $1 million supercomputer. In other words—great headline but still very much boys with expensive toys.

What is really disruptive is something else. A university researcher in 2015 taught in 72 hours an algorithm to go from 0 to winning an international chess tournament as part of its research project.

In that example we have university resources matching a multi-million if not billion dollar programme. If we conceptualise it, we are talking about commoditising “deep learning” and “artificial intelligence.” Start-ups are already doing it.

The timeline of the future of fintech: 

  • Fintech 1.0: Was about infrastructure
  • Fintech 2.0: Was about banks
  • Fintech 3.0: What about start-ups
  • Fintech 4.0: Will be about techfin

The next time you look at your mobile phone don’t use it just for selfies. Realise that this item changed from a communication tool (third industrial revolution) to one of data collection and analysis (fourth industrial revolution). In other words you all hold the shift in your hands.

Categories: Technology & Operations
Keywords: The FoF Summit, FinTech HK, China, data analytics, fintech, techfin, Baidu, Alibaba, Tencent, money, digitisation, monetisation, BAT, best available technology, artificial intelligence, fourth industrial revolution, e-commerce
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