CDAO Financial Services & Insurance UK 2025 schedule

During this 10-minute networking session, the aim of the game is to go and meet two people you don't already know.  Have fun! 

• How are companies using AI and automation to optimise operations, reduce costs, and drive innovation in challenging economic conditions? 

• How are data leaders identifying new opportunities and areas for growth despite tightening budgets? 

• How are organisations using data and predictive analytics to detect potential risks early and manage financial uncertainty? 

• How are data strategies being adapted to create more resilient and adaptable business models during periods of economic volatility? 

Moderator: Vivek Sayal, Head of Model Strategy and Non-Financial Risk Analytics – Virgin Money  

Gael Decoud, Director Data Science – CHETWOOD FINANCIAL LIMITED  

Alan Strange, Head of Underwriting & Analytics- Sophro MGA Ltd  

• AI Evolution: The presentation highlights the rapid evolution of AI, from early excitement in the 1950s to the current advancements in Generative AI and Agentic AI . 

• Workforce Impact: AI is expected to replace 85 million jobs while creating 97 million new roles by the end of the decade, with a significant impact on the global economy  

• AI Agents: AI agents are not just chatbots but digital workers that can autonomously execute tasks, bringing transformative changes to various industries  

• AI Opportunities: Identifying AI opportunities in manufacturing, prioritizing solutions based on impact, feasibility, and ROI, and leveraging AI for inventory optimization, production scheduling, and predictive maintenance 

The choices facing data leaders tasked to transform their data and analytics functions into levers of innovation and change are overwhelming.    Mountains of and technical and data debt, excessive market hype, and increasing pressure to show progress on AI are exacerbating the enormity of the task.  Overcoming these barriers is key to breaking the curse of excessively short CDO tenures.   

Data leaders who are implementing or revitalizing their data teams, and who seek an answer to the question of ‘where should I start?’ must: 

1. Revisit legacy assumptions, challenge the status quo
2. Embrace an operating model focused on agility
3. Prioritize progress over perfection; take a practical approach to GenAI
4. Recognize that ‘all data is not created equally’
5. Leverage an analytical style of master data management (MDM) to drive short-term value, and establish a strong data foundation

Come hear industry expert, author of the ‘Data Hero Playbook’, and the CDO of Profisee, Malcolm Hawker, as he shares valuable insights the practical steps data leaders must take to drive meaningful and lasting changes in their organizations.  Malcolm also shares his experience on how an analytical style of MDM is the perfect balance between short-term business value, AI-based innovation, and data foundations. 

• • The difference between monetisation hype and productised value 
  • Internal vs external data products: What works, what flops 
  • Pricing, packaging and scaling: A playbook from those doing it 
  • Metrics that prove long-term value (not just quick wins) 

• Committing to elevating customer experience 

• Harnessing Open Banking to enable financial inclusion 

• Implementing sophisticated analytics and risk models to ensure responsible lending practices. 

• Unlocking the power of partnerships 

• AI Governance vs. Data Governance – Clarifying the distinction and why both are critical.

• Compliance & Adoption – How senior leaders can accelerate AI adoption while staying aligned with DORA, NIS2, and the EU AI Act.

• Trust & Assurance – Frameworks to ensure AI models are explainable, auditable, and trusted by regulators and customers.

• Data Governance Foundations – Are formal processes essential, and what are the first steps in a regulated environment?

• Adaptability – How to keep governance frameworks flexible as regulations evolve.

• Accountability – Preventing gaps when multiple stakeholders are involved.

Sheetal Bakshi, Data Strategy and Management Lead – Capco 

Dr Madhura Shivaraju, Senior Data and AI Specialist - UBS 

1. The Data Dilemma in Real Estate

2. Sustainability: Burden or Breakthrough?

3. AI & the Future of Real Estate Investment 

4. Interactive Discussion & Q&A

The right data at the right time—especially sustainability data—can be the difference between average and exceptional returns. Let’s make sure real estate doesn’t miss the AI-driven transformation.

Sally Bashuan, Executive Director - Head of Global Data Governance- Federated Hermes 

Katerina Papavasileiou, Director, ESG and Responsibility - Federated Hermes 

• Which types of claims or lines of business are proving most viable for agentic AI, and what blockers are you facing? 

• How do you ensure human oversight and regulatory compliance when deploying autonomous agents in claims workflows? 

• What are the toughest tech, people, and culture challenges we face in scaling up the agentic AI usage company-wide, and how do we encourage innovation while keeping risks in check for everyone involved? 

Richard Cooke, UK Business Lead – KEEPLER 

Bhushan Kokate, Chief Architect: Data, Analytics and AI – MS AMLIN 

• How are leading firms moving beyond pilots to embed GenAI at scale? 

• What governance frameworks are essential to mitigate hallucinations, bias, and misuse? 

• Where is GenAI delivering real impact — from compliance to customer experience? 

• What are the organisational and cultural shifts required to integrate GenAI into workflows? 

Moderator: Francesco Di Costanzo, CEO – JAJA FINANCE 

Gael Decoud, Director Data Science – CHETWOOD FINANCIAL LIMITED 

Sharada Khanna, Global Lead for Originations and Credit Bureau Data Strategy, Retail Banking - HSBC 

Challenges  

• Fragmented data landscape due to Aon’s history of M&A 
• Lack of standards, poor data quality, availability, and auditability
• Global adoption of centralised master data

Lessons Learnt  

• Change management and adoption – articulating the story of why this is important
• Balancing decision making between technology acceleration and cross functional alignment

An informal, interactive session where attendees ask questions directly to an AI ethics and data privacy expert. The expert will answer questions on the fly, providing practical insights and advice on navigating regulations and building trustworthy AI systems. 

Focus Areas: AI ethics, data privacy, regulatory challenges. 

Sally Bashuan, Executive Director - Head of Global Data Governance- Federated Hermes 

Vladimir Bendikow, Chief Data Officer - FirstBank UK Limited 

Andi McBurnie, Chief Architect – GIBBS Consulting 

• What long-term strategies are successful businesses adopting to ensure resilience during periods of economic turbulence?  

• How are companies reshaping their approaches to data, governance, and AI to remain adaptable in the face of market volatility?  

• How can businesses leverage data and AI to future-proof their operations against ongoing economic uncertainties?  

• What role do governance frameworks play in helping companies navigate financial instability and ensure sustainable growth? 

Moderator:  Salma Bakouk, CEO & Co-Founder - SIFFLET 

Ishant Aggarwal, Document AI Lead – Lloyds 

Dr Madhura Shivaraju, Senior Data and AI Specialist - UBS 

•  How can organisations leverage data monetisation to unlock new revenue streams and create value from existing assets?  

•  What role does data governance play in ensuring the ethical and secure monetisation of valuable data?  

•  Can data monetisation strategies truly deliver long-term value, or are they just a short-term financial boost?  

• • How can companies identify untapped opportunities for data monetisation without compromising customer trust or privacy? 

Moderator: Rebecca Linehan, Head of Insight - Confused.com 

Vivek Sayal, Head of Model Strategy and Non-Financial Risk Analytics – Virgin Money 

Lucy Clayton, CCB Data Analytics Manager - Santander UK 

Ishant Aggarwal, Document AI Lead - Lloyds 

• Is the main challenge with data initiatives a data problem or a cultural/psychological one? 

• How can we break down data literacy into something practical for shifting culture? 

• What can data do and what can’t it do? How do we manage hype vs. reality, especially with AI? 

• How do we achieve buy-in from leadership and the broader organisation, given increased AI investment but underinvestment in foundational data? 

• How do we sustain momentum and avoid fatigue in long-term data transformation projects? 

Beatrice Russell, Data & Analytics Product Manager – Global - AON 

Martin Nelson, Data Platforms Adoption Lead and Product Owner- NFU MUTUAL