Archives: Agenda

• Identifying and prioritizing high-value AI use cases
• Measuring ROI across efficiency, risk reduction, and revenue growth
• Overcoming challenges in scaling AI investments for long-term impact

• Comparing capabilities and trade-offs between Large and Small Language Models
• Use cases in financial services: scale vs efficiency
• Future outlook: hybrid approaches and evolving model architectures

Invitation only

This closed-door roundtable brings together senior financial-services decision makers to hear from GlobalData’s research and analysis team , who will present key industry trends and predictions as surfaced through their proprietary data and intelligence, and how they will impact the use of AI across the Nordic banking, insurance and fintech sector. This Chatham House Rule environment will also facilitate the creation of senior peer-to-peer networks around the topic of AI adoption to support industry benchmarking and collaboration.

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