CDAO Financial Services Europe 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! 

• Establishing robust data governance as the cornerstone of transformation. 

• From siloed data to a unified architecture: Laying the groundwork. 

• Educating teams and aligning leadership around data literacy. 

• The role of compliance and regulation in shaping data infrastructure. 

• Why strong fundamentals are critical before scaling AI initiatives. 

• From analysts to data citizens: Scaling data use across teams. 

• Building high-performing data teams: Skills, roles, and structures. 

• Fostering a culture of experimentation and agility. 

• Upskilling in AI and analytics: What financial leaders need to know. 

• Retaining talent in a competitive tech-driven market. 

• Align compliance strategies with complex EU regulations (e.g. GDPR, DORA, CSRD) while enabling innovation. 

• Implement data governance practices that support auditability, transparency, and operational efficiency. 

• Balance secure data usage with flexibility to drive digital transformation across borders. 

• Prepare for future regulatory shifts with scalable, technology-driven compliance models. 

• Rethinking the role of core data infrastructure in a fast-evolving financial landscape 

• Why getting the basics right (quality, lineage, governance) is still the hardest—and most strategic—challenge 

• Breaking free from legacy constraints: How to modernize without disrupting trust 

• From transactional records to predictive intelligence: Building the bridge 

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. 

• Building AI governance frameworks to ensure compliance and manage risk. 

• Establishing the right people, roles, and tech accelerators for scalable AI. 

• Showcasing real-world GenAI use cases driving value in financial services. 

• Evaluating the readiness of AI agents for real-world financial applications. 
• Creating a sustainable feedback loop between AI adoption and business outcomes. 

• The latest trends and technologies shaping data-driven decision-making. 

• How financial services are utilizing data analytics to gain a competitive edge. 

• Transformative techniques in data analysis to drive strategic insights. 

• Key factors driving the evolution of decision-making processes in 2025. 

• The future of financial services through data-led strategies and innovation 

• How to build data architectures that are adaptable to regulatory change (MiCA, DORA, etc.) 

• Managing fragmented compliance demands across European jurisdictions 

• Stress-testing your data infrastructure for macroeconomic shocks 

• Leveraging data to support strategic agility in times of instability 

• From Brexit to inflation: Aligning data strategies with market unpredictability 

• Real-world use cases: KYC, reporting automation, client advisory 

• Human-in-the-loop: balancing automation with expert oversight 

• Deployment challenges: data quality, hallucinations, security 

• Measuring ROI: productivity, customer impact, cost savings 

• Preventing financial data breaches in an age of advanced persistent threats 
• Data lineage and traceability: Knowing where your risk lives 
• Cyber risk modelling with AI and real-time signals 
• Cloud resilience strategies for critical financial workloads 
• Cross-border coordination: How to align on data security in pan-European institutions 

• Open Finance in practice: Building real value from data sharing 

• Embedded finance as a data challenge: Partnerships, APIs, and control 

• How to ensure customer trust in distributed financial ecosystems 

• Navigating consent, security, and ownership in open data flows 

• Real-time intelligence in third-party channels: Managing quality and risk 

• Building ethical AI frameworks tailored for financial institutions. 

• Navigating GDPR, DORA, and other evolving compliance landscapes. 

• Creating explainable and auditable models: AI transparency in action. 

• Bias, fairness, and accountability: New standards in AI risk management. 

• Internal governance vs external regulation: Finding the right balance. 

• Unlocking real-time decision-making across the enterprise. 

• Predictive analytics for credit, investment, and customer behavior. 

• Leveraging alternative data sources: What’s valuable, what’s noise? 

• Cloud infrastructure and data streaming: Making it work in finance. 

• From dashboards to next-best-actions: Operationalizing real-time insight. 

• Moving beyond experimentation: Deploying AI at scale across functions. 

• How AI is transforming risk assessment, fraud detection, and underwriting. 

• Intelligent automation in back-office operations: What works and what doesn’t. 

• Embedding machine learning into core banking processes. 

• Pitfalls to avoid when integrating AI into legacy systems. 

• Scaling GenAI use cases from prototype to production 

• Human-in-the-loop: Ensuring oversight and risk control 

• Regulatory reporting and compliance automation 

• Hyper-personalized client engagement 

• Data quality, security, and hallucination management 

• Measuring ROI: productivity, cost savings, and client outcomes