Archives: Agenda

1. What are the strategic implications of AI to the financial industry and what do we expect to see in the future?

A forward-looking discussion on how AI is reshaping financial services strategy, from data governance and organisational design to customer propositions and regulatory expectations.

Nivedh Iyer, Head of Group Data Management, Group Data & Analytics, Danske Bank  

2. Integrating AI Solutions into Contact Centre systems: Preparing people processes, and data for automated customer interactions

A practical exploration of how AI is embedded into existing contact centre platforms, aligning data, workflows and operating models so automation delivers real efficiency and experience gains without undermining quality, governance or control.

Farhad Fatemi, Sales Engineer. Puzzel 

3. Strategic adoption of Agentic AI: Automating customer-facing communications across voice, chat and email

An honest discussion on moving agentic AI from pilots to production across channels, examining where automation genuinely adds value and what is required to scale it safely while maintaining oversight, consistency and trust.

Jesper Jønsson, Director of AI Products, Puzzel 

4. Can Nordic financial institutions escape the pilot graveyard? 

The average Nordic bank is running 15-30 AI pilots simultaneously. Most will never reach production – not because of bad technology but because of a broken strategy. The pattern is always the same: a proof of concept wins a budget, a pilot runs for six months, stakeholders celebrate the demo. But nothing scales, the P&L doesn’t move, the board asks where the ROI is and, inevitably, another cycle begins. We’ve been through this ourselves, and we built our way out of it. Let’s discuss what really works for aligning people, technology, and value engineering to capture the full potential of AI.         

Genady Chybranov, Head, BFSI Centre of Excellence Sigma Software

5. From blueprint to production: Modern banking at speed with AI, automation and compliance intelligence

This roundtable explores how financial institutions can move from strategy to execution, putting AI solutions quickly and safely into the hands of customers and employees. As firms face growing pressure to scale AI in highly regulated environments, delivery speed, governance and compliance intelligence are becoming critical to success. Join this discussion to examine how financial institutions can remove barriers to deployment and accelerate the delivery of real business value.

Christer, Hedström, Regional Sales Director Nordics, OutSystems

6. How to set the right level of ambition for AI

How ambitious should organisations really be with AI, and how do leaders set the right targets to turn ambition into real impact? How should organisations prioritize and follow up to ensure progress in the areas that matter most?

Karianne Sundahl, Head of data and analytics, Storebrand

Financial institutions are generating more data than ever, yet over 68% of it goes unused, and most AI projects fail not because of the models, but because of the data foundation beneath them. Drawing on real-world case studies across fraud detection, AML investigations, and ATM operations, this session explores how organisations can deliver quantifiable business value by unifying and acting on structured and unstructured data in real time.

NOBA Bank Group’s AI journey at was never just about technology. With a small, dedicated team and strong executive support, they developed internal and customer-facing AI solutions by focusing on adoption, change management, and practical impact. Rolling out licenses or generic “off-the-shelf” tooling quickly proved insufficient; instead, they prioritised self-service creation, and focused on understanding, categorising, and embedding internal knowledge in a structured manner. By leveraging Azure OpenAI and internal APIs, they achieved fast and secure results. Key learnings from their internal rollout directly shaped their customer chatbot, proving that true success comes from understanding user needs and organisational context. Importantly, this approach allowed them to connect AI development to clear business goals and deliver tangible customer value. Join us for a deep dive into their approach, adoption metrics, and why rolling out AI in a financial institution is “not a tech project”- it’s about people, process, and purpose.

This session explores the real-world challenges teams face when implementing AI; the late nights, unexpected setbacks, and the hard-earned lessons that shape success. Through candid stories and reflective insights, participants will unpack what went wrong, why it happened, and how resilience and learning turned breakdowns into breakthroughs.

AI ambition is high across financial services, but measurable impact remains uneven. This session centres on a detailed real world case study, illustrating how an outcome-led framework helped a firm move beyond pilots to deliver tangible operational and commercial value through embedded, workflow-driven AI.

• The hard truth about stalled AI initiatives
• Defining business outcomes before selecting technology
• How the framework was applied in practice
• Measurable results and lessons learned

For financial institutions, the “gold rush” of AI experimentation is meeting the “brick wall” of the EU AI Act. As organisations move from internal pilots to customer-facing production, the critical question is no longer just about model accuracy – it’s about governance. How do you track every prompt, redact PII in real-time, and manage skyrocketing token costs without slowing down your developers? In this session, SEB and Kong share a blueprint for leveraging a dedicated AI Gateway – a centralized “control plane” that decouples AI innovation from regulatory complexity.

Moderator: Steve Roberts, Global Strategic Advisory Services Lead, Kong Inc

To realise enterprise AI ROI, integration, analytics, and business leaders must rewire their approach. But with so many organisations invested, yet so few seeing a return, what needs to change? Centralise for control, or decentralise for innovation? How about both – and neither? It’s the classic “governance vs self-service” debate, revisited.

As financial crime grows more sophisticated, so must our defences. This panel explores how AI is transforming fraud detection and where its blind spots still lie. From real-time detection to post-payment forensics, we will examine how institutions can build resilient, end-to-end fraud strategies that balance automation with accountability.

Moderator: Bartosz Golba, Director of research and analysis, GlobalData

Agentic AI promises systems that can act, adapt, and make decisions at scale. As that capability increases, a more fundamental question emerges: where does control and accountability actually sit? In this session, Jonathan Sunderland sets the context for Agentic AI beyond capability alone, exploring how organisations must think systemically about decision-making, trust, and boundaries, and examining what must change, what must stop, and what must remain under explicit control. As enterprises push toward more autonomous systems, the real constraint is not capability, but whether the system they are built on can support them reliably, transparently, and at scale. The session examines how one enterprise, working with Ab Initio, has taken a strategically different approach to shifting the fulcrum and building the foundations required for Agentic AI.