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 can financial institutions align their data strategies with the Financial Conduct Authority's (FCA) new five-year plan to foster trust and growth in the UK's financial services sector? 
• What are the potential trade-offs associated with the FCA's growth objectives, and how can data leaders mitigate risks such as increased mortgage defaults and financial misconduct? 
• In what ways can the integration of fund tokenisation technologies be leveraged to enhance operational efficiency and competitiveness in asset management? 
• How can financial institutions encourage retail investors to engage with higher-return financial products while ensuring adequate consumer protection? 

• • What does PSD3 mean for data-sharing infrastructure and consumer protection? 
  • How can firms comply with the Data Act while maintaining innovation speed? 
  • What security, consent, and trust mechanisms are essential in open ecosystems? 
  • How can tech and data teams collaborate to support open finance strategies?

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. 

• 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?

• How can financial institutions leverage cloud-native analytics platforms to process data in real time and make faster, more informed decisions? 

• What advantages do cloud-native solutions offer over traditional analytics platforms in terms of scalability and flexibility? 

• How can adopting cloud-native analytics enhance operational efficiency and improve responsiveness to customer needs? 

• What are the key challenges financial institutions face when integrating cloud-native analytics, and how can they overcome them?

• 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? 

• How can AI reasoning capabilities enhance underwriting processes by improving the accuracy of risk assessment and pricing? 

• What are the key benefits of using advanced AI models that go beyond basic understanding to enable more sophisticated decision-making in underwriting? 

• How can financial institutions integrate AI reasoning into their existing underwriting workflows to drive better outcomes and reduce errors? 

• What challenges might arise when implementing AI reasoning in underwriting, and how can these be overcome to ensure successful adoption? 

• How are insurers aligning ESG reporting with CSRD’s data disclosure mandates? 

• What tools and frameworks are enabling accurate, auditable ESG metrics? 

• How can data teams support sustainable underwriting and investment decisions? 

• What’s next in climate and ESG data innovation? 

• What are the key challenges insurance firms face when modernising legacy systems, and how can they address these hurdles? 

• How can integrating new technologies with existing infrastructure enhance operational efficiency and improve the customer experience in the insurance sector? 

• What strategies can insurers adopt to ensure a seamless transition from legacy systems to modern digital platforms without disrupting services? 

• What opportunities does digital transformation present for the insurance industry, and how can organisations make the most of them for long-term success? 

• How can we make GenAI traceable, transparent, and regulator-ready? 

• How can internal audit and AI work together to build trust without stalling innovation? 

• What do financial leaders need from governance to scale AI effectively? 

• How can risk controls be transformed into commercial enablers? 

• How are top firms aligning with FCA, DORA, the EU AI Act, and other regulations? 

• How can compliance be streamlined to support global growth? 

• How can duplication be avoided across risk, compliance, and data teams?  

• What lessons can we learn from international data leaders? 

• 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) 

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. 

• 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? 

• How can CDOs build a truly data-driven culture — not just a tech stack? 

• What are the biggest people and mindset barriers to data adoption? 

• How do you win senior buy-in and drive cross-functional accountability? 

• Where are most firms going wrong with data literacy — and how do you fix it? 

• What does an effective, modern data team structure actually look like? 

• How do you sustain momentum through organisational change and fatigue? 

• How can CDOs build a truly data-driven culture — not just a tech stack? 

• What are the biggest people and mindset barriers to data adoption? 

• How do you win senior buy-in and drive cross-functional accountability? 

• Where are most firms going wrong with data literacy — and how do you fix it? 

• What does an effective, modern data team structure actually look like? 

• How do you sustain momentum through organisational change and fatigue?