From FinTech to TechFin: Data is the New Oil.

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[Transcript of the Closing Keynote in Hanoi on May the 12th 2016]

When I arrived in Hong Kong slightly over a year ago to build a Accelerator I knew I wanted to do three things.

  1. To inspire my generation to join or build a FinTech company
  2. To adapt myself to Asia, accepting that financial brands are global but financial behaviors are local.
  3. To embrace the fact that China will lead the world in terms of innovation.

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 a 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, with is purely led by outsiders.”

We read reports on China’s leadership in FinTech. Ant Financial valued at over US$50billion after a series B round. Tencent facilitating over 8 billion red envelopes to be shared in a day, up by 7 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. Breaking down what the BATs do. We essentially have:

  • Baidu connecting People with information
  • Alibaba connecting People with products
  • Tencent connecting People with People.

Each of these companies have hundreds of millions of users, and for them FinTech is just a commoditized layer that is used to enhance their core product:

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

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

Tencent can better connect people by splitting bills in a restaurant via WeChat Wallet or reconnecting families millions of kilometers apart during Chinese new year simply by digitizing Red-envelopes

Each of this FinTech layers within their products is incredibly valuable and valuated, yet their growth is finite. There is 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, or the , but the context. The meta data. It is then that I learned the source of my misunderstanding.

Money has been digitized and Now Data is monetized – 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 : Internet Service Providers and E-Commerce Platforms.

We often draw parallels between telco’s and bank’s. 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 this pipes? Data. Data that if properly understood can generate money. AOL increased its revenue by US$300 million, which was a 50% Increase in 1 quarter, “just” by adding data analytic from Verizon to its ISP business.

What about E-commerce platforms? Sesame Credit in China is now used not just to originate loans, but to instead sell you non-financial 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 post more regulatory capital for originating a loan (note: this was in 2015!). In both case they used the same credit score.

FinTech to TechFin represents a shifting trend that China has simply 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 the rise of communications and IT systems. 

Today, we are entering an era of data analytics and artificial intelligence. These in turn transform data from 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 monetize it.

We are indeed at the beginning of a new cycle simply because less than 1% of the world’s data is analyzed, with over 80% is unprotected.

Starting with Data Protection. From a regulatory perspective this creates a direct challenge. Data Privacy laws were designed with human in minds. However today this is irrelevant.

“Computers can’t abstractly reason nearly as well as people, but they can process enormous amounts of data ever more quickly (if you think about it, this means that computers are better at working with meta-data than they are handling conversational data). […] Computing power is still doubling every eighteen months, while our species’ brain size has remained constant. Computers are already far better than people at processing quantitative data and they will continue to improve.” (Data & Goliath) 

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

  • Deep Mind is the start-up behind AlphaGo, acquired for GBP 242 Million in 2014.
  • Deep Blue was the IBM program started in 1985 that beats Garry Kasparov in 1997 at a cost of 5% of IBM Revenues
  • Watson beat the worlds best Jeopardy players in 2011 at a cost of US$ 1.8 billion

If you want to run Watson software, irrespective of license cost you will need a US$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 has in 2015 taught in 72h its algorithm to go from 0 to win international chess tournament as part of its research project.

In that example we have university resources matching a multimillion if not billion program. If we conceptualize it we are taking about commoditizing Deep Learning and AI and start-ups are already doing it.

So here is 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 just use it for selfies. Realize that this item changed from a communication tool (3rd industrial revolution) to one of data collection and analysis (4th industrial revolution). You all hold the shift in your hands.

Note: It can be debated that FinTech is just a service layer within the company value chain, especially as Ant Financial is an independent spin-off (but for transfering back 37% of profit to Alibaba).


is Millennial in FinTech | HKU Law | Founder FinTech HK & SuperCharger | Co-Editor The FinTech Book