Archives: Agenda
AI in MedTech: redefining clinical trials and device development
- ISR Market Research results and insights into the State of AI in Clinical Trials
- Opportunities for companies that embrace AI across the Clinical Trial Lifecycle
- Adoption of AI in MedTech for Clinical Product Development
Adapting trial designs to global market realities
- Align protocol design with MDR, FDA and global regulatory expectations
- Manage endpoint variability across geographies without undermining quality
- Avoid costly rework by building flexibility into trial strategy
Registration and refreshments
From PMCF obligation to strategic advantage: standardising PMCF under EU MDR with 1Survey+
- The reality of PMCF under EU MDR: mandatory, continuous and increasingly scrutinised
- Common pitfalls in current PMCF strategies and why many approaches no longer satisfy Notified Body expectations
- Introducing 1Survey+, a clinical-grade, regulator-ready PMCF platform designed in accordance with ISO 14155
- From fragmented PMCF activities to portfolio-level standardisation and scalability
Chairperson’s opening remarks
Can your controls keep up with your AI?
Financial institutions across the Nordics are deploying AI into regulated functions at pace. Most are doing so on fragmented controls infrastructure — detection in one system, policy in another, archive somewhere else, investigations requiring manual reconstruction across all of them. The AI is advancing. The controls around it are not always keeping pace.
This session sets out what defensibility-grade integrated controls look like in practice: what it takes to maintain an end-to-end, auditable evidence trail from regulatory obligation to case outcome, where most institutions have integration gaps today, and what a practical modernisation path looks like. Drawing on patterns from more than 100 financial institution deployments, it gives compliance, AI, and risk leaders a concrete framework for assessing where their controls programme stands — and what to prioritise next.
The Path to Agentic AI Transformation
Step into the Future of AI from pioneering intelligent automation to unleashing the power of Agentic AI across the SS&C estate. Join us on our journey, where we are moving beyond automation to build AI agents that are driving change at scale with a digital-first mindset and governance-first approach. Walk away inspired, informed, and ready to lead your own transformation.
What you’ll take away:
• The story of our evolution—from automation to AI-led operations.
• How we’ve deployed agentic AI agents at scale, with governance at the core.
• Why experience, innovation, and trust matter when choosing your AI partner.
The Sovereignty issue: Full control of all your AI-touching data
As Nordic financial institutions move from AI pilots to enterprise-scale production, the “Sovereignty Trap” remains the biggest hurdle. High-value initiatives often stall when sensitive proprietary data meets the boundaries of public cloud APIs. In this session, we explore Private AI—a transformative architectural approach where the organization, not a third-party provider, hosts and controls the AI models within its own secure environment. By “bringing the model to the data” rather than sending sensitive enterprise data to an external cloud, firms can ensure that LLMs run entirely within their own firewall. Join us to discuss how this inverted architecture satisfies the strictest global mandates—including GDPR and the EU AI Act—while providing the immutable audit logs required for modern fund governance and risk management.
Beyond Copilot: Moving from basic AI to “Agents with Agency” in Governed Financial Workflows
Generative AI is no longer novel. Financial institutions are now at a crossroads: either continue managing a fleet of helpful “assistants” or transition to Autonomous Agents. While basic LLMs can summarise data, true “Agents with Agency” can execute complex workflows – from AML investigations to KYB verification – autonomously. However, in the high-stakes world of FSI, there remains a significant risk. We will deconstruct a manual Anti-Money Laundering (AML) workflow to show how agentic systems mimic human reasoning, and more importantly, how adopting a governance layer ensures these agents operate within safe, auditable parameters, to move beyond the “AI as a toy” narrative and explore the architectural shift required to give AI the power to act.