Europe at Night from Space


Building a smarter
organisation with AI

Tuesday 26th March 2019
8 Fenchurch Place, Fenchurch Street,
London, EC3M 4PB

Checkout the Roadshow coming to a city near you!

Artificial Intelligence has become mainstream and is fuelling more and more aspects of businesses and day-to-day life.  Beyond the hype, the question is how data-driven innovation can be brought to life and put in action to resolve real business problems. What steps are needed to move AI out of the lab and into business operations to realise the desired outcomes?

During the morning of our half-day event we will take a practical approach around some different techniques, with true life examples. We will help you understand how to join those organisations breaking new ground with AI and analytics. And crucially, how you can deliver transformative value within your organisation.

Learn why AI is evolving the way data is used to leverage actionable insight in organisations today. We will talk through the value that machine learning, natural language processing and computer vision can drive and why data management is key to successful AI implementations. Register here.



Georgios Kapetanvasileiou

Georgios Kapetanvasileiou
Data Scientist

Kayne Putman

Kayne Putman
Data Scientist

Matthew Stainer

Matthew Stainer
Principal Data Scientist

Iain Brown

Dr Iain Brown
Lead Data Scientist, SAS UKI

David Smith

David Smith

Graeme Reed

Graeme Reed
Senior Manager, The Analytics Hub, Nationwide

Tuba Islam

Tuba Islam
Global Technology Practice, SAS


Tuesday, 26 March
8:30 – 9:00
Registration Coffee Pastries
9:00 – 9:10
9:10 – 09:40
Five lessons learnt from AI deployment
We will cover real-world applications of AI deployments detailing both the results and more importantly the actionable lessons learnt.
  • understand the critical factors that will make your AI strategies successful
  • have a feel for what AI could do within your organisation.
Dr Iain Brown, Head of Data Science
09:40 – 10:10Data management is key to successful AI
AI is seen by many as the best way to secure the future of their organisations, but there is significant public concern about its possible detrimental impact. Some are concerned about the concentration of power in the hands of huge tech companies, while some see automation as a threat to their employment. In this session we will cover how transparency will go some way to alleviating these concerns;
  • transparency can be brought to AI through data management and data governance good
  • data management is essential for successful AI, including matters of security, regulatory compliance and deployment
Dave Smith, Head of Data Management
10:10 – 10:40Using Natural Language Processing to further improve customer satisfaction at Nationwide
Nationwide has started to use Natural Language Processing (NLP) techniques, to further improve its already industry-leading customer satisfaction. Nationwide set out to investigate why their members get in touch and find better ways to resolve their enquiries. Successful projects to improve understanding of member contact has led to an increased demand for NLP based analytics across the societies broader text footprint.

Graeme Reed, Senior Manager, Nationwide

Matthew Stainer Analytics consultant

10:40 – 11:00Break and Networking
11:00 – 11:30
Real world example of Machine Learning in Insurance
Cutting through the hype of Machine Learning and AI, we will take you through a practical application of how Machine Learning was effectively used in the insurance industry. Learn how organisations are deriving actionable insight from AI applications and the business value they deliver today. This will further clarify the role of human ML expertise in the development process, both now and in future
  • machine learning and analytics
  • process modernisation
Georgios Kapetanvasileiou, Lead Data Scientist
11:30 – 12:00How are computers becoming more image-conscious?
How do you apply maths to photos, you may wonder? Computer vision is one the key AI applications for SAS; whether that be classifying images, detecting objects in images or simply assessing changes in images. Increasingly so, organisations are seeking how to apply these techniques to previously unused data sources to either:
  • enhance existing BAU processes and models,
  • drive net-new innovation.
Kayne Putman, Analytics Consultant
Tuba Islam
Global Technology Practice
12:00 – 12:45Panel Discussion and Questions from the Audience & Wrap UpALL
12:45 – 14:00Lunch and Networking
14:00 – 16:00Open Sessions and Demo

We look forward to seeing you there and supporting your AI and analytical ambitions on Tuesday, 26 March at etc Venues, 8 Fenchurch Place, Fenchurch Street, London, EC3M 4PB

etc Venues
8 Fenchurch Place
Fenchurch Street, London, EC3M 4PB


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  Data management
  Machine learning
  Computer vision
  Natural language processing
  Artificial intelligence

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Successful execution of an analytics, and thereby AI strategy, needs the right balance of choice and control.


Creativity and innovation flourish in open spaces. You need flexibility and freedom to attract the best analytical talent, use a wide variety of techniques and develop processes that work best. You need the flexibility to use multiple programming languages and analyze any data in any environment and to keep up with accelerating demands.


Analytics chaos can creep up. Once you lose control of your data, you lose trust in the system and its outputs. Transparency, governance and security become essential for maintaining trust in models and analytical results. Becoming even more critical as you scale development, monitoring and refinement of analytics applications and their associated processes.

At the intersection of data, software, and ingenuity, the future is being redefined. After all, when curiosity meets capability, progress is inevitable.

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