Advanced Analytics in action
Advanced Analytics and AI for BFSI: June 25-26, London
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The AI & Intelligent Automation Network surveyed corporate enterprise practitioners at the turn of the year. Far and away, the largest focus for investement was Advanced Analytics.
Add that to the fact that Banking, Financial Services and Insurance are the leading industries in adoption of automation technologies and you've got a recipe for a possible can't miss event.
Change Management, Exploiting Data & Improving Outcomes, Advanced Analytics to Improve Loyalty and Engagement, Advanced Analytics in the Cloud and mapping your entire journey are just some of the concepts covered.
Key topics include:
Change Management: Creating, Leading and Developing a Data and Technology Led Culture
Huma Lodhi - Principal Data Scientist, Direct Line Group
Alpesh Doshi - Partner, Redcliffe Capital
Yehuda Dayan - Co-Head of the Research Innovation Lab/Manager Big Data Analytics, Citi
- What are the unique characteristics new technology will bring?
- How can risk and resistance to change be managed effectively?
- Who, how many and in which way will people be affected?
- Key tips for developing a change management strategy: Team structure, sponsor model, special tactics and risk assessment
- How can you strike the balance between changing mind-sets, technological change and standardisation
- What is the best way to establish strategic partnerships between departments, employees and stakeholders
- Key tips for executing a change management methodology and leading organisational change
Advanced Analytics & AI in the Cloud
Angela Johnson - Programme Director, Deutsche Bank
- Business transformation and innovation through the cloud:
- Supporting key technologies such as advanced analytics and AI to drive competitiveness
- Buy-in, change management and leadership: Creating and building a cloud centre of excellence
- Managing the data migration process and ensuring quality
Leveraging Advanced Analytics & AI to Exploit Data and Improve Organisational Outcomes
Peter Thomas - Senior Manager, Regulatory Technology, Bank of England
- Market snapshot: What is happening in the market right now and how is it anticipated to change in the future
- Department overview and objectives: Collecting, exploring, analysing and managing quality data to improve organisational outcomes
- Challenges of operating in a public organisation: Demonstrating ROI, culture and change management
- Find and fix: Exploring regtech and suptech that can solve the bank’s unique problems
- Turning fun proofs of concept into organisation wide solutions
Strategies to Move from Proof of Concepts into Deployment
Martin Thorn - Senior Manager – Decisioning Analytics & AI, CYBG
Gaye Soykok - Head of Emerging Technologies, Legal & General
Huma Lodhi - Principal Data Scientist, Direct Line Group
Stephen Magora - Director, Data Analytics, Credit Suisse
Yehuda Dayan - Co-Head of the Research Innovation Lab/Manager Big Data Analytics, Citi
An Intelligent Automation Journey: Business Case, ROI, Roadmap, Testing and Next Steps
Rashmi SHROFF - FSO Transformation Plan Deputy Program Director, Societe Generale
- How is the banking industry currently automating processes, how is RPA being utilised and how will it continue to mature in the future?
- Demonstrating the true value of automation and what are the expectations from the investment
- Outlining the key technologies and the main players in the market
- How SGSS started their thought process for adopting RPA for securities business:
- What were the pain points that led to RPA;
- How did we organize to develop the BOTS within the firm;
- What were the major challenges, what was the gap between the expectations and the results
- Results, lessons learned and next steps
Advanced Analytics to Improve Loyalty and Engagement
Umran Rafi - Head of Digital Data, Santander
- The importance of agility: Maintaining pace in a fast moving technology market and keeping abreast of customer’s changing needs and priorities
- Viewing all interaction points along the customer journey to achieve a single view of the customer
- Unlocking the value from customer data to identify trends, history and customer profile to understand your customers’ needs and grow lifetime value
- Developing the right architecture and selecting the right vendors to collect and analyse important behavioural insights
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