Today's world is becoming binary. On one hand, there are a few giants such as Google, Facebook, Uber, and Amazon that have discovered "the magic formula" and have become the only reference in their field in just a few months or years. On the other hand, some large traditional well-established companies can disappear overnight as recent history has proved. In this new world, the companies that will be successful have to integrate Artificial Intelligence (AI) in their strategy and way of thinking which will often imply that a paradigm shift is required.
In order to be a player of this revolution, BNP
Paribas has recently created a Data Science and Artificial Intelligence Lab
both at the service of its Corporate and Institutional Banking division and of
its clients. Interview of Edouard d' Archimbaud the Data Scientist in charge of
the Lab.
To start, could you come back to the basics and explain what artificial intelligence is about?
Artificial Intelligence is an attempt to imitate the
way a human brain works. Actually there are two major ways to think about
approach to Artificial Intelligence: weak and strong intelligence. Weak
Artificial Intelligence is about creating intelligent programs that replicate
certain behaviours of the brain. For example automatic translation system or
Voice to Text programs are weak Artificial Intelligence applications. Strong
Artificial Intelligence attempts to understand what a human brain is and how it
works to duplicate human brain power. The latter remains a dream for now, as we
are still far from being able to do this.
Why is artificial intelligence so important for all businesses?
Just
to put things into perspective since the development of digitalisation all the
information in the world is stored in a digital format, i.e. a format that can
be readable and computed by a machine. Companies that will manage to exploit
this layer of analytics and create added value for their clients are the ones
that will succeed. Uber, for instance, could be seen as a payment platform
connecting passengers and drivers. If it was the case, the customer would pay a
few basis points for this service as a standard payment via a bank transaction.
Uber's margin is tenths of percent because the added value created is not in
the payment service but in the capacity to help drivers to find passengers and
passengers to find drivers thanks to data analytics processed by a clever
Artificial Intelligence program.
Artificial intelligence seems to be at the heart of the successful stories of some of the tech giants, can you explain why?
I
strongly believe that the leading tech giant companies like Facebook, Google,
Amazon, YouTube, Netflix, Twitter, Airbnb and BlaBlaCar are the ones that have
understood something fundamental: DATA is the key asset. To use Artificial
Intelligence you need 3 types of components: data, computing power and brain understanding.
Computing power has become a commodity in today's world. In a similar way,
algorithms are now easily accessible in a collaborative economy. For instance,
one of the best facial recognition algorithms is now accessible in open source.
The treasure of a company nowadays really lies in its data, and some companies
have totally understood this.
If we look specifically at the banking industry, which banking players are best positioned to use artificial intelligence?
For well-established banks like BNP Paribas, we have
everything needed to do Artificial Intelligence. We have computing power, brain
power and most of all: a big volume of data. Remember this is one of the core
assets for Artificial Intelligence and this is what start-ups, "new challenger
banks", do not have. It is very encouraging and we are working a lot to
build customer centricity through data centricity. Companies have not
historically been built with data as the central point. This is the paradigm
shift that is necessary for us to make and that we have engaged in to deliver
value to our customers through Artificial Intelligence.
"DATA is the key asset."
Can you give some examples of what the lab is working on?
Yes,
we have already engaged in many projects. We are working on a compliance
screening system for instance. The idea is to automate the screening of
contracts to check if they contain names that are on sanction lists. For this,
we are building several bricks: one program that transforms documents into
plain text format, one name recognition program that is able to identify and
extract the names of people, ships, organisations, places that are included in
the text, and finally there is a fuzzy matching program that checks if the
extracted names are or not on the sanction lists. We are also working on ways
to improve our clients' experience when interacting with the Bank. For the
moment we are aware that we have quite a "siloed" relationship with our
clients (for instance with multiple web pages). With AI we can build a natural
language user interface and intelligent navigator that will help a client go
straight to the information needed.
"(...) we want to create a club to give our clients access to part of the technology that we develop so that they can use it on their own data."
Are you working on anything that will be of particular interest to corporate treasurers?
Yes, we have just worked on the second edition of the
Corporate Treasury Insights Survey that BNP Paribas and the Boston
Consulting Group (BCG) co-published mid-2016 to create a
web tool that enables a
treasurer to navigate interactively through the data. More generally we want to
create a club to give our clients access to part of the technology that we
develop so that they can use it on their own data. Our clients and we are part
of the same ecosystem where our data and knowledge are interlinked. Using AI
programs will benefit to clients before anything else.
You obviously need to know a lot about how the human brain works to be able to imitate some of its functions. How does the lab conduct research and improve its knowledge of the human brain?
First of all, there are many publications available on
the topic and we spend time reading and studying these of course. We have also
developed partnerships with some research labs and PhD students specialised on
these topics. For instance, we have a partnership with a person working on text
mining. Banks know how to process and analyse figures, but they are not as good
when it comes to process efficiently text format data. We are also working with
specialists in recommendation engines to bring more intelligence to our
clients.
In your view should we be scared of the introduction of so much intelligent technology in our everyday life? In other words, what is your vision of the relationship between human and technology?
We are still very far from being able to really and
totally replicate the way a human brain works. Technology is not going to
replace mankind. Introducing weak AI in our everyday life and work enables
human beings to be more efficient and so frees up time for people to
concentrate on tasks with a higher added value. For the moment we spend 25% of
our time just searching for data, this time is not spent on doing something
more useful!
When is this paradigm shift going to happen?
It is happening as we speak. Artificial Intelligence
is inevitably spreading across all businesses just as IT spread a few decades ago!
leading the Data Science and Artificial Intelligence Lab at BNP Paribas CIB