Let Artificial Intelligence work for you

Get a glimpse into what AI can do for you, with UseCases from RBS Services, ETHjuniors and Accenture. What are the conceptual tools we need to become effective? How to create successful applications to ease your workload? What do we need to understand before we go any further?

As always there will be presentations and workshops, as well as plenty of time to network with people across different companies and industries.


  • Opening by Host 10′
  • Keynotes by Experts 4 x 20′
  • Start ups 2 x 20′
  • Workshops  1 x 60′
  • Cognitive NetworkingDinner



Date & Time

28th May 2018 – 1:30PM

Host & Location

RBS Services (Switzerland), Zurich


Presentations in German and English
All slides in English


 more will be added soon

Dr. Jürgen Pulm
RBS Services (Switzerland)

Host Welcome

Pinar Wennerberg

Sherlock Scheduling Tool – Using AI to Optimize Internal Project Staffing

Arman Bukvic
RBS Services (Switzerland)

“Supercharge the Private Banking Platform with AI” – How RBS plans to leverage the AI technology


Jörgen Stehr & Tania Rebuzzi
Credit Suisse

Cognitive Banking Support – How to move from vision to delivery

Marcus Johansson

Discover the meaning of textual content with topic modelling – Experiences from the media industry

Tim Grunow & Lukas Wawrla

Jens Pflueger

Addressing patient’s needs in diabetes care using machine learning


Ryan Salton & Boris Rankov 
RBS Services, InCube

Recommender Systems

Recommender systems have been widely adopted in areas such as online shopping and movie streaming. They automatically suggest new items to users based on their characteristics and previous behaviour. We will explore some use cases on how the models of recommender systems could bring benefits to the world of finance.

Philipp Bärfuss

“Yes, I talk AI” – the AI-Alphabet for Non-Technical Human-Beings

For non-technical people the field of AI can be overwhelming and confusing. Let’s get a grip on key terms and understand the most relevant algorithms like random forest, deep learning or generative adversarial networks.

Mark Cieliebak

Text Analytics in Real-Life Projects

Automatic text analytics is an important ingredient in many applications: chatbots, internet search, Twitter monitoring, automatic customer support, opinion mining, etc. There are literally thousands of successful applications. We will explore how to implement text analytics projects in real life: Which problems can be solved? How good are existing technologies? And how can you run a successful text analytics project?

Marc Lecoultre

Applied Machine Learning to solve your back office problems

The case I would like to discuss with you is the optimization of a back office we did for a client. Suppose you have customer requests with different complexity that you receive each day, such as insurance claims, loan applications, tax returns, customs declarations, subscription to a service offered by your company.

In your team you have people with different skills and capacities. How do you divide the workload among your team members so that the processing time is small but of high quality?

Impressions from past Events

Testimonials from Participants