2026-10-30 –, Main Hall
In today’s threat landscape, the most dangerous scenarios are not the ones you detect—but the ones that look perfectly normal.
Cyber Security assumes systems can be compromised. Financial crime frameworks assume systems can be trusted. But what happens when those assumptions collide?
This session explores the hidden intersection where identity compromise, data manipulation, and legitimate system access transform secure environments into enablers of financial crime. Across AML, fraud, sanctions, and corruption risk, attackers are no longer just bypassing controls—they are operating within them.
It challenges the belief that “secure systems produce safe outcomes,” and introduces a new perspective: financial crime risk as a direct consequence of broken trust in identity, data, and behaviour.
In Cyber Security, we design controls assuming attackers are already inside, identities can be compromised, and systems—even trusted ones—can be manipulated.
Financial crime frameworks have evolved differently. Across AML, fraud, sanctions, and anti-bribery & corruption (ABC), controls are built on a more implicit assumption: that identities are real, data is accurate, and systems provide a reliable view of reality. Risk is detected through patterns, rules, and known typologies—often after events have already taken place.
This session explores what happens when these two worlds meet.
Using real-world examples and cross-domain insights, we will examine how modern attack techniques—such as identity compromise, synthetic identities, data manipulation, and abuse of legitimate access—can quietly undermine financial crime controls. In these scenarios, systems continue to operate as designed, transactions appear legitimate, and decisions remain “compliant”—while financial crime risk unfolds undetected beneath the surface.
The talk will:
- Compare the core assumptions of cybersecurity and financial crime frameworks
- Explore how “trusted systems” can become enablers of AML breaches, fraud, sanctions evasion, and corruption risk
- Highlight what cybersecurity can learn from financial crime disciplines, including decision accountability and risk assessment under uncertainty
- Translate these insights into practical actions for CISOs and security teams—focusing on identity trust, data integrity, and cross-domain detection
- Challenge the audience to rethink how signals, systems, and trust models should be connected
This is not a compliance session. It is a conversation about trust. And how both cybersecurity and financial crime functions must evolve together to respond.
This session is an invitation for cybersecurity professionals to extend their thinking beyond infrastructure and to play a critical role in preventing financial crime risks that traditional controls were never designed to detect.
Caroline van Gorp, FICA, MBA, is Head of Global FEC Sanctions Change & Portfolio at Rabobank, where she leads large-scale transformation initiatives at the intersection of financial crime prevention, risk, technology, and regulatory change.
With a career spanning financial services, compliance, risk management, and business transformation, Caroline is known for her ability to connect disciplines that are often treated separately. She brings a holistic perspective to risk, exploring how innovation, technology, human behaviour, and governance collectively shape organizational resilience. Pioneer, entrepreneur, and Non-Executive Director for NGOs.
Passionate about the potential of technology to drive meaningful change, Caroline focuses on navigate complex challenges in an increasingly interconnected and digital world. Her work combines strategic thinking with practical execution, enabling sustainable transformation while strengthening trust, security, and customer outcomes.
A speaker and thought leader, Caroline is particularly interested in the paradoxes, wicked problems, and different perspectives. Her insights challenge conventional thinking and encourage audiences to look beyond silos to better understand the evolving risk landscape.