04 - 05 July, 2018 | Hilton London Kensington, London, United Kingdom

Agenda Day 2

8:15 am - 9:00 am Registration and Coffee

8:50 am - 9:00 am Chairperson's Welcome

9:00 am - 9:40 am Data in the Cloud and Fraud Prevention Using Machine Learning

David Laramy, Director, Head of Fraud Strategy & Analysis,Capital One Kyle Roberts, Fraud Data Analysis Manager,
  • Uncovering previously undetected anomalous activity by creating a central point for data access
  • Cross-channel fraud prevention by amalgamating data
  • Exploring the use case for machine learning across fraud types
  • Case studies for internally built and externally sources machine learning
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David Laramy

Director, Head of Fraud Strategy & Analysis
Capital One

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Kyle Roberts

Fraud Data Analysis Manager

8:00 am - 12:00 am Data Monetisation: Data as a Means for Direct & Indirect Revenue Growth

Neil Taylor, Head of Data and Systems,Liv-Ex
  • Treating your data as an asset: Quick overview of how both direct and indirect revenue streams have been achieved
  • Leveraging insights that will improve customer experience, loyalty, retention whilst increasing spend per customer and drive overall business revenue
  • Open Data: Understanding how releasing data created

Neil Taylor

Head of Data and Systems
Liv-Ex

  • Industry overview: How has the industry changed, what has been the impact and how can the industry evolve to protect themselves?
  • What are the existing and emerging threats and the impacts currently affecting the industry?
  • What is the best way to structure an organisation, departments and individuals to combat financial and cyber crime?
  • How can we use analytics to gain great insights into customers, employees and partners to reduce fraud and threats?
  • What key advice would you have for anyone just starting out with developing a fraud and cyber program?
  • What advice would you give to organisations that are modifying data to monitor and capture suspicious activity?
  • What are the current and future impacts on data and privacy and how can that be managed to protect business?
  • AI, Machine Learning and other technology: How do you envisage the use of existing and emerging technology combat financial crime?

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Steve Jackson

Head of Financial Crime & MLRO
Covea Insurance

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David Laramy

Director, Head of Fraud Strategy & Analysis
Capital One

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Juan Amador

Global Head Financial Crime Risk Technology Strategy
HSBC

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Bob Spencer

Head of Claims Counter Fraud
Direct Line Group

11:20 am - 11:50 am Morning Coffee and Networking Break

8:00 am - 8:35 am Machine Learning, Big Data & Analytics to Combat Fraud and Financial Crime

Steve Jackson, Head of Financial Crime & MLRO,Covea Insurance
  • Describing how advanced machine learning analytics can greatly reduce fraud, improve customer experience and drive a competitive edge
  • Creating and utilising insights to improve predictions on new types of fraud  as well as measure and manage risk
  • Using AI and machine learning to improve speed and accuracy of data-driven decisions: Automating tasks to free up valuable resources
  • Choosing the right solutions: Understanding your unique business problems and only selecting solutions that achieve those business objectives
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Steve Jackson

Head of Financial Crime & MLRO
Covea Insurance

11:50 am - 12:30 pm Revolutionising the Financial Services Sector through Real Time and Predictive Analytics: Use Case, Challenges and Implementation

Mark Whitehorn, Professor of Analytics,University of Dundee
  • What are business benefits of real time and predictive analytics?
  • Describing how real time analytics can leverage customer insights to improve experience and grow revenue
  • Understanding how real time analytics can improve fraud detection, manage risk and improve credit scoring
  • What are the challenges with implementation and what the tools and technologies required?
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Mark Whitehorn

Professor of Analytics
University of Dundee

12:30 pm - 1:10 pm Delivering and Maximising Business Impact through Autonomous Decision Engines

  • Incorporating machine learning technology into the data strategy to help improve agility and flexibility throughout the organisation
  • Delivering business value through more accurate predictions and automating decisions
  • Understanding how to interpret and apply the results from advanced analytics and machine learning to improve business outcomes
  • Establishing a data structure that will enable innovation and capitalise on new business and market opportunities

1:10 pm - 2:10 pm Lunch and Networking Break

2:10 pm - 2:50 pm Cyber Security and Threat Intelligence through Big Data

  • Overview of the advancements of data analytics and cyber security: Enabling analysts to visualise cyber attacks by simplifying data patterns
  • Strategy: Developing risk management and actionable intelligence capability
  • Talent management: Sourcing the right people, with the right experience to build an efficient team that understand what data trends to spot
  • Automating tasks through machine learning that that enable faster availability and accessibility of data
  • Incident response: Ensuring data analysis and any anomalies are directed to the right place at the right time
  • Creating business value from investments in data by adapting and borrowing principles from Agile, Lean and Dev Ops
  • Agile data science: Aligning data science with organizational goals
  • Practical solutions to increasing the velocity of value creation
  • DataOps – The new approach to data science: Analytics professionals in the centre of the company’s strategy, advancing its most important objectives
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Harvinder Atwal

Head of Data Strategy and Advanced Analytics
Moneysupermarket.com

3:30 pm - 4:10 pm The Link Between Data Privacy, Security and Customer Centricity

Nsemeke Ukpong, IT Chapterlead,ING
  • Overview of ING data privacy project: Drivers and opportunities
  • Understanding how data privacy and security can be the catalyst for customer centricity
  • Focusing on data governance and ensuring the right blend of business process, automation and technology will drive the best results

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Nsemeke Ukpong

IT Chapterlead
ING

4:10 pm - 4:20 pm Closing Remarks from the Conference Chair and Close of the Conference

4:20 pm - 4:25 pm Farewell Afternoon Tea and Networking Break