Treasury and Risk - REAL November 2019 Special Report

The world around us has transformed radically and a digitalrevolutionisunderway in treasury. We are in a period of rapid change, constantly wondering what our computers can do for us today. How does this impact a day in the life of corporate treasurers? Will human treasury be replaced by robots in the near future? Artificial Intelligence (AI) and Machine Learning (ML) are set to transform and optimize treasury operations.

Back to the future

AI is not new - it has been around for nearly 70 years and began with Alan Turing’s Test and the establishment of the field of AI.

In 1990 the prominent futurist and AI expert Ray Kurzweil extrapolated the performance of chess software to predict that computers would beat the best human players “by the year

2000”. The power of AI and ML has been demonstrated by the trajectory of chess computers since Deep Blue beat Garry Kasparov in 1997.

The journey of chess computers in the last 20 years illustrates how far artificial intelligence has come, and how even an apparently unbeatable chess program can be outclassed with the use of a deep learning algorithm. This is just one example of how machine learning is uncovering new strategies.

We humans have realized that
computers were able to outperform
us in many ways: processing power
for performing calculations, memory
storage, and searching vast amounts
of data and possible outcomes. With
more powerful computers and the
ability to process huge amounts
of data, new application areas will
arise, as we see now in treasury. This
journey demonstrates how embracing
deep learning can bring benefits
beyond what can be achieved by either
humans or computers individually,
ultimately transforming how a
particular problem is approached.
By adopting AI, companies can go on
their own transformational journey
and discover how they can collaborate
with technology to improve their
performance and add more value than
ever before.

How can artificial
intelligence help treasury
teams?

With the power of ML and AI, treasury teams can become more effective and add more value to the businesses they serve. AI has many use cases in Treasury. Organizations can derive monetary gains, better prepare and plan, and validate data using AI. Also, with these tools,

The artificial intelligence and machine learning revolution

A BRIEF HISTORY OF ARTIFICIAL INTELLIGENCE
Artificial Intelligence (AI) is not new - it has been around for nearly 70 years! It all started out with the Alan Turing Test and the
establishment of the field of AI. With more powerful computers and the ability to process huge amounts of data new application
areas will arise, as we see now in treasury.

1950: Alan Turing introduces the Turing Test, a test that challenges whether a machine can “think”

1956: At the Dartmouth Conference, the field of AI is launched and the term “artificial intelligence” is coined

1960: Psychologist Frank Rosenblatt’s work on perceptrons lead to the development of the

Mark I Perceptron, the ‘first
computer’ that learned skills by trial
and error
The late 1970s and 1980s were known
as “The Winter of AI” a time of reduced
funding and interest in the field

1988: British scientist Rollo Carpenter creates Jabberwacky, a chatbot designed to carry out conversations with users and intimate human interaction

1997: IBM’s Deep Blue Computer beats Garry Kasparov, reigning world chess champion, in a game of chess.

Late 1990s: Dr. Cynthia Breazeal of M. I. T designs KISMET, a robot head that can recognize and replicate human emotions.

1978/79: SCARA, a robotic arm used in assembly lines, is created in Japan, and thereby allows for high-speed automated assembly

Late 2000s: IBM introduces Watson, a question ans wering computer system that is able to answer questions posed in a natural language. Like IBM’s Deep Blue, Watson went on to beat the top two Jeopardy! contestants.