Archives: Agenda

• Biomarkers defining target populations by measuring pharmacological targets and pathogenic cascades
• Biomarkers as surrogate endpoints for efficacy
• Where EMA and the FDA have taken different approaches
• Emerging trends and future challenges

Co-author: Karl Broich, President of BfArM

• Working with sites before protocol finalisation
• Identifying operational bottlenecks early
• Reducing unnecessary protocol complexity
• Designing studies that fit real-world clinical practice

We explore how Retrieval-Augmented Generation (RAG) can transform quantitative research workflows by enabling accurate, context-aware answers sourced from technical documentation.

• How to build RAG pipelines to handle complex, domain-specific queries efficiently
• What are the key technical challenges, like: retrieval strategies, query handling, grounding and answer generation
• How to train and evaluate these systems
• What are the best practices and learnings for designing robust, scalable AI assistants for quant and business decision-making

Navigating Agentic AI and Emerging Threats in Financial Services

• The Current State of AI Security in Financial Services – How organisations are balancing rapid AI innovation against regulatory requirements (EU AI Act, DORA) and legacy infrastructure challenges while maintaining robust security controls
• Agentic AI: The Next Security Frontier – Understanding autonomous AI systems in financial services, their unique security challenges, and practical approaches to securing AI agents that make independent decisions and interact with critical systems
• AI-Powered Security Tools Moving to Production – Demonstrations of AI security solutions including automated threat modelling and AI-generated incident response scenarios, showing how GenAI is transforming defensive security operations
• Industry Trends Shaping the Future – The shift from AI governance theatre to measurable implementation, growing enterprise acceptance of GenAI for defensive security, and the emergence of cross-industry collaboration through open-source security tools
• Practical Implementation Focus – Key takeaways for building production-ready AI security programs that deliver measurable outcomes while enabling innovation velocity

From skeptic to believer: join Marius Beliunas on his real-world journey through the evolving world of AI in financial services. Discover how rigorous testing and hands-on experience with Moterra’s Business AI Suite led to breakthrough results. Walk away inspired, with practical insights on adopting secure and compliant AI in highly regulated industries.

• Follow Marius Beliunas’ transformation from AI skeptic to advocate for secure, responsible innovation
• Hear how “testing everything and believing nothing” led to real breakthroughs with Moterra’s Business AI Suite
• Explore live examples of AI boosting security, productivity, and compliance in financial services
• Leave equipped with actionable strategies for implementing Agentic AI and GenAI in regulated environments

• What is a Frontier Firm? – Defining the concept: AI-first, agile, and digitally mature organisations leading transformation in Financial Services
• Stages of Becoming a Frontier Firm – From experimentation to scale: exploring the journey from pilot projects to enterprise-wide AI adoption
• Microsoft’s Role in Enabling FS Transformation – How Microsoft’s platforms, Copilot, and industry-specific solutions are laying the foundation for AI-first financial institutions
• Xpedition as a customer zero – sharing how Xpedition is implementing Agents, upskilling teams, and acting as a customer zero to model transformation
• Why Now? – Discussing the urgency and opportunity for FS firms to move beyond hype and build real capability in AI

• How financial institutions can move from AI governance principles to measurable, auditable practice
• How to connect AI governance principles with deep technical controls that provide evidence for confident AI decisions
• How evidence-based governance transforms compliance from a constraint into a driver of trust, performance, and innovation across financial organizations
• A real-world GenAI success case with a leading wealth management institution, showing how AI principles were turned into rigorous controls to test model performance, risk, and compliance