Tokenization of assets: a promise of a massive change in the financial industry.

Tokenization of assets: a promise of a massive change in the financial industry.

We are at the beginning of the 4th industrial revolution. Technology is profoundly transforming our lives. The combination of innovations such as artificial intelligence, internet of things, robotics, and blockchain, will pave the way for this revolution. We are experiencing technological changes that will alter the way we live and work on an unimaginable scale in the coming years.

There is one particular technology that catches my attention, and it’s blockchain, this technology promises to give authenticity, trust, and equality of criteria, through a consensus protocol, in global and decentralized environments.

Thanks to this technology, we can tokenize, any right, asset, stock, commodity, intangible asset, a legal association, or agreement. All of these assets will be able to be represented, tested, and transferred with a digital token.

But, what is asset tokenization?

Tokenization is the process of converting assets into tokens that can be registered, exchanged, and stored in a blockchain system. That may sound quite complex, but I assure you it is not that difficult.

To keep it simple, tokenization converts the stored value of some physical object, such as a car, or an intangible object, such as a credit, into a token that can be handled throughout a blockchain system. One could tokenize, for example, a piece of art, a real estate asset, a car, gold, a barrel of petroleum, among others. In short words, any asset that you can imagine, the sky is the limit.

What advantage does this bring?

There are many advantages that the tokenization of assets can bring to the financial industry. The most often mentioned are the reduction of administrative work, the decreasing of costs by the removal of intermediaries from the process, much faster asset transfers, and the availability to trade them 24/7 from anywhere in the world.

by Yann Gourvennec

Also, this technology allows you to have fractional ownership of an asset; for example, you can own a fraction of an art painting by Claude Monet. Which will lead to higher liquidity and accessibility to very illiquid assets as well as helps to democratize investments. This kind of assets will become easily transformable in money and will allow a more significant number of people to participate in their returns due to the reduction of the investment of entry. However, this is not something new, but it certainly simplifies the whole process.

It offers some advantages to the real estate market as well. In addition to those we have named above, the use of smart contracts will enable to automate the change of ownership of a house once the payment has been made. Also, once an investor acquires a token, no one can erase (or will be extremely difficult) the ownership information because it will be added on the public blockchain making it immutable and transparent.


Many of the advantages will not be possible without major social, legal, and technological changes that could take a long time and resistance to be adopted from unprivileged sectors.

Even though the third parties are removed, it’s necessary to create a new regulatory framework for this kind of activity.

Blockchain technology is still its early stages, so I believe it’s still not prepared for a massive enter of a vast market as the real estate is. It’s necessary to keep developing this technology.


Tokenization is a promise of a massive change to how we see things nowadays. It allows us to buy and sell all kinds of assets while democratizing the process of owning it.

France is taking a step forward in Europe by beginning to create regulatory frameworks for this type of activity. The AMF seems really interested in regulating it. You can check the recent “Loi Pacte” law that has been approved.

Blockchain offers an exciting alternative to the financial market and a unique way of owning a part of an object such as a car or a painting. Little by little, this will begin to change the way we take ownership of things.

Tokenize the world!



L’Oréal is leading the worldwide beauty industry. With 37 brands, L’Oréal covers
consumer’s needs from hair to toes. Every year, L’Oréal is investing to innovate: research and
development, acquisition of new companies, incubating start-ups, to keep their leading
position. Who would imagine years ago that we could now try lipstick on without having it
physically in hand? Or have a sticker on your hand sending your phone a text to tell you to put
sunscreen on? The company is changing, from new development methods to a high-tech
production chain to new recruitment methods. With the rise of artificial intelligence in the
beauty industry, can we state that it is leveraging innovation at L’Oréal?

First, let’s define Artificial Intelligence. Some can challenge the use of the word
intelligence here or talk about Assisted Intelligence. For this essay we will take the Cambridge
dictionary definition: “Artificial intelligence is the study of how to produce machines that have
some of the qualities that the human mind has, such as the ability to understand language,
recognize pictures, solve problems and learn”. Artificial Intelligence simplifies human’s
everyday life: autonomous cars, smartphones, smartwatches, connected objects, are
omnipresent. AI helps to test and run solutions through data analysis and machine learning. It
is a way to go further in research, to open doors that humans could not even imagine 10 years
ago. If nowadays AI is largely associated with sci-fi movies showing the machine overcoming
Human, it is much more a tool than a threat to human prosperity. In the era of the 4th
industrial revolution, machine learning could be seen as the springboard of human evolution.

As their consumer’s behavior is changing, companies must adapt. This is what L’Oréal
is doing by implementing new technologies and changing their consumer’s but also
employee’s habits.

L’Oréal is giving a lot of importance to innovation. It is one of the main values. Many
teams are even dedicated to it, from the R&D center to HR, through Sales department. AI,
augmented reality, machine learning, are influencing the beauty value chain.


Can a machine really learn? Machine learning is defined by Collins dictionary as “a
branch of artificial intelligence in which a computer generates rules underlying or based on
raw data that has been fed into it”. In L’Oréal’s laboratories, for example, Artificial intelligence
is used to analyze consumer’s anonymous data, understand them, and create the perfect
formulas adapted to their needs.


Technologies such as connected mirrors or skin scanning tools transformed the
consumer’s shopping experience.

Let’s take the example of Lancôme. Lancôme unveils the promise, for all women, of
getting their customized, custom-made foundation with « le teint particulier ». Thanks to a
technology protected by 9 patents, the foundation can be declined in 72,000 different
combinations. Consumers can have an in-shop diagnosis led by a beauty consultant. After a
skin scan, the carnation-related data is processed to find the perfect match between skin and
foundation. The tailor-made formula is then prepared live in about twenty minutes in the

This technology is a process innovation, changing the way a simple foundation is
created and delivered. It offers the consumer a new shopping experience, a customed service
and product. Thanks to this example we can see how AI is changing first, the way we consume
by redesigning our consumer experience, second, how we can provide a tailor-made solution
to each consumer transforming massive production or one size fits all philosophy to ondemand production.

As we stated it before, AI is a powerful tool to enhance human diversity and
capabilities. We can imagine that once this technology is well in place, the amount of data
collected and processed through AI systems would give the opportunity to provide consumer’s
tailor-made advice?

What about trying makeup without even having to touch it or put it physically on your
face? This is the challenge L’Oréal is now facing for 5 years, by developing connected mirrors.
This technology is based on augmented reality.


Augmented reality can be defined as a live superposition of real images and graphical

As a matter of fact, artificial intelligence plays a massive role to get qualitative and
performant augmented reality. L’Oréal saw the opportunity and recently acquired ModiFace,
a company specialized in virtual fitting of beauty products. Human resources are crucial to
developing such a tool, on both L’Oréal and ModiFace side. ModiFace employs nearly 70
engineers, with access to some of the largest facial data sets in the world, but also researchers
and scientists who have submitted more than 200 scientific publications and registered over
thirty patents.

The aim is to create beauty-try in simulations on live video by tracking facial details.
ModiFace face AI SDK tracks movements and expressions through 68 parameters such as lips,
eyes edges, iris sizes, eyes location, head pose, but also skin features like spots, textures or
wrinkles. This recently acquired technology will change the consumer’s journey on the
internet and in shop. It can be implemented as an HTML e-commerce module for the web, or
mobile app, or custom AR software designed to match any in-store smart mirror.

One of the first projects is a live skin diagnosis, on which L’Oréal R&I teams is working
for more than 15 years. This tech is based on an AI algorithm created by ModiFace and
L’Oréal’s image bank. Through deep-learning methods, the algorithm has been trained
through 6000 clinical images. It then has been tested on more than 4500 selfies of Asiatic,
Caucasian and Afro-American woman, with 4 types of different lightnings. Results were
analyzed by dermatologists. In 2019, Vichy will be the first brand to launch it, under the name

Other brands like Garnier, already started taking advantage of such technology with a
less developed application/web app called “Virtual Shade”. It allows customers to try different
hair colors before buying the right product. Giorgio Armani, YSL, L’Oréal Paris, referenced all
they makeup catalog within the YouCam makeup app, for the consumers to try on and directly
buy the wanted products. Finally, Sephora shops installed virtual mirrors with direct makeup
try on.


Digital innovation can be articulated around 4 P: Properties, Platforms, People, and
Practice, that are in my opinion well managed by L’Oréal, using artificial intelligence to lever
it. Digital experiences are put in place to enrich organizational conversations. Digital
technologies such as in shop foundation creation create proximity between those that
produce and those that consume. Working in L’Oréal for a year and a half now, I can see how
digital and machines are important for our work. L’Oréal won’t be as performant without all
this new technology. Habits are changing, services and products are evolving. Machines are
interacting with humans daily, from chatbots for consumer services to recruitments. However,
non-digital teams are not enough aware and sensitized to this digital revolution. Some
employees think it is only relevant to digital teams, others think it is not necessary. In a context
where we live surrounded by technologies, artificial intelligence is still seen as a futuristic tool.
Fortunately, managerial mindsets are starting to change. Will artificial intelligence lead to a
work revolution?

Women in tech: a question of (in)equality

Women in tech: a question of (in)equality

Why not listening to good music while reading? My inspiration for this article about women in tech is Run the World – Beyoncé. Play it now!

In her book, Lean In: Women, Work, and the Will to Lead, Sheryl Sandberg writes:

The promise of equality is not the same as true equality

These words illustrate perfectly the reality of the tech industry. New technologies are omnipresent today and everybody is impacted by it in a way or another. Forecasts are positive when it comes to jobs and opportunities for all, hoping for a more equal world. Yet, there is one thing you should know: gender inequality is still clearly strong in the tech industry.



Technology, computing, digital… all that we know today was not exclusively created by men. Many women actively contributed to it and they should be thanked for their work. Let’s review some of them!

Ada Lovelace – (1815-1852)

Born in 1815, Ada Lovelace is the inventor of the first algorithm to be applied by a machine. For that, she has been given the nickname “first computer programmer”. She also brought out important questions regarding society considering technology to a collaborative tool. Impressive for the time!

Kay McNulty, Betty Jenning, Betty Snyder, Marlyn Meltzer, Fran Bilas and Ruth Lichterman – 1946

Called the ENIAC 6, these six women programmed one of the first computers in History, the ENIAC. An interesting thing to know is that some of them did not receive any recognition for their work during their lifetimes. Also, many people and especially historians were persuaded that they were only “refrigerator ladies”.  It means that, for them, their job was only to refresh the machines while they were, in fact, creating something big.

Grace Hopper – (1906-1992)

This woman created the first computing language called COBOL. For her work, she received the award of Computer Science Man of the Year by the Data Processing Management Association in 1969. Great for a woman! Later, in 1991, she was given the National Medal of Technology which constitutes a high honour in the USA for people working in the tech industry.


Radia Perlman – (1951-)

 Have you heard about the Spanning Tree Protocol? Well, Radia Perlman does! She conceived the algorithm behind it, consisting of the “basic traffic rules” of the Internet we know today. She is named “The Mother of the Internet”.



Women making History was unfortunately not enough to have gender equality in the tech industry. Many reports have been published the last 10 years to illustrate it, showing that the tendency continues to be the same. Here are four figures to help you measure it:

1. Syntec Numérique realized a study in which is highlighted the fact that in 2016, only 33% of total employees in the digital industry in France were women. Among them, only 16% had jobs such as developers. Others were working in human resources, communication or administration for example.

2. In the USA, the National Center for Women Information Technology released a report in 2016 showing that only 25% of total computing jobs are held by women. This situation is even more concerning for Asian women who represent only 5% out of the 25%, African American women (3%) and Latina women (1%). And the evolution from year to year is not positive…

Percentage of computing occupations held by women - Author: Julie Compagny

Percentage of computing occupations held by women – Author: Julie Compagny

3. The same report proved that 41% of all women employed in the high-tech industry quit in 2015. This is huge compared to men: only 17% of them did it. This report allows an understanding that the main reason why women left their job has nothing to do with family concerns. Indeed, they perceived no possibility of evolution and development in the companies they were working in, leading them to change job.

4. In 2017, 30% of all Google employees worldwide were women and, actually, it has been the case since 2014. Three female employees took the company to the court in 2017 because they were less paid than men. It seems that Google still has a lot to learn!

Distribution of Google employees worldwide from 2014 to 2018, by gender - Author: Julie Compagny

Distribution of Google employees worldwide from 2014 to 2018, by gender – Author: Julie Compagny



The benefits of gender equality


Of course, it exists many benefits for gender equality in the tech industry. Two insights are very interesting to look at though and we will focus on them.

The first one is that with gender equality in tech, we could take advantage of the competencies, ideas and solutions that 50% of the population could bring. Image what we could have had today in terms of new technologies if we included a lot more women earlier!

The second one is that over 1.4 million computing job will be open by 2020 in the USA. Nonetheless, with the current computing grads of the country, only 30% of those jobs would be taken. It is then a huge opportunity for women who are totally needed!


How to encourage gender equality?


Here again, there are many ways to encourage gender equality. The most logical solutions are very often the ones we do not think about.

Regarding companies, simplifying job descriptions and being honest about the must-haves is a good solution to have more women applying. A fact is that a woman will apply to a job if 100% of the criteria meet who she is whereas a man will apply to the same job if only 60% of the criteria meet who he is. Making job descriptions easier is then a source of opportunity for women. Companies can also promote inclusion and diversity and make it a real priority for all employees, men and women. Encourage its female employees to develop their competencies and reach higher levels is necessary and will favour gender equality.

Other solutions exist and you should try them: find a mentor to help you, integrate an association or a digital community, have a role model to project yourself and above all, believe in yourself and do not forget that yes, it is possible! If others succeeded, why won’t you?

Gender inequality in tech can be challenged and it is our responsibility, to all of us, to make things change.

In her book, Sheryl Sandberg also writes:

We cannot change what we are not aware of, and once we are aware, we cannot help but change

I really hope that these words will be meaningful to you and that after having read this article, you will actively fight for gender equality in the tech industry.

From attention to addiction: where is the digital economy heading?

From attention to addiction: where is the digital economy heading?

The term attention economy was first coined in 1971 by Economist Herbert Simon. According to him, information consumes the attention of its recipients. The more information you have, the less attention there is, and a need emerge for this attention to be allocated efficiently.

There is no denying that we live in an information-rich world; the internet alone is proof enough. It is full to the brim with unlimited knowledge. And all of it just a click away! However, with the internet come the many companies that compete for our attention in order to make a profit. We are bombarded with colourful and eye-catching content from the moment we go online. And it works! We have a very well developed peripheral vision. In the past, it would alert us of an impending attack and help us survive. What once increased our chances for survival is now a source of great distraction thanks to the flickering images in the edge of our vision.

In short, it is an evolutionary trap.

From Attention to Addiction

We are inherently curious creatures. Once something captures our attention, we want to know all there is to know about it. So, we will begin interacting with said ‘something’ in order to begin this learning process.

And here is when the playing field changes; when the attention economy has the potential to morph into something much more dangerous.

Companies fight against each other for our attention. The more time we spend on their platforms, the more revenue they generate. And this need to monopolise attention and keep users on the platform has led to the encouragement of addictive behaviours. Platforms want users to become addicted to what they provide because that guarantees them your time and attention.

And as we all know, time is money.

And how do companies achieve this? Through a simple but highly effective combination of habitual motions (scrolling, tapping and clicking) and bursts of auto-play content that invites us to click. The rewards from this scrolling, clicking, and surfing is intermittent but rewarding. It activates reward circuits in the brain and leads to behaviours that would be labelled as addictive.

To put it into perspective: smartphone addiction forms pathways in a very similar way to how oxycontin users experience opioid addiction.

Beating the Addiction Economy

A high percentage of the population is currently addicted to some form of digital device. That much is a fact. We depend on our phones and laptops to access even the most basic of services, and we appreciate the convenience they provide. Dependence on our devices -for work or for leisure – has led to increased levels of anxiety, depression and attention deficit disorders among the connected population.

Is it possible to break the cycle?

Awareness of digital addiction is rising, and with it, a new market has emerged. One for apps that encourage and reward us for time spent away from those same devices. These rely on the same addictive-based principles: habit, conditioning and reward.

And whilst being rewarded for moving or drinking water might feel patronising, we enjoy being praised for leading a healthier lifestyle… even if the one dishing out praise is an AI.

From Quantity to Quality: the next economy?

The attention economy relies on time. Our increased awareness of how much time we have at our disposal has transformed us into overly-selective consumers. We want premium, reliable services that provide everything we might need, and we are happy to pay for it. Netflix and Spotify are the perfect examples: once subscribed we ignore other offers because our needs are met.

What should we call this: an economy of efficiency, or rather an economy of convenience? We are not so much trying to break the cycle of addiction, but rather accepting that we do have this addiction and making the most of living with it by only consuming the best products out there.

I want to hear your thoughts on the matter, so do comment and get in touch! You can also find the “live” version of this article on periscope.

if you like my writing, be sure to check my two previous pieces relating to social media influencer marketing on  Trust and the Value of Disclosure, and on Digital Footprints