2026 Risk | REIMAGINED

From capital buffers to enterprise resilience

For decades, risk management was defined by capital, liquidity, and regulatory compliance. Those disciplines still matter, but they are no longer enough. Today’s institutions are judged by whether they can keep operating, adapting, and making decisions when markets, technology, supply chains, geopolitics, and customer expectations shift at speed.

This keynote reframes risk as an enterprise resilience capability: one that protects critical services, strengthens decision-making under pressure, and helps organizations absorb shocks without losing strategic direction.

From third-party risk to third-party resilience

Financial institutions no longer operate within a neat enterprise perimeter. Cloud providers, SaaS platforms, data partners, payment rails, and critical vendors now shape the resilience of the business itself.

This panel examines how leading firms are moving beyond vendor checklists toward active dependency management. Speakers will discuss how to identify critical relationships, test operational resilience, strengthen contracts, improve visibility, and prepare for disruption when the weak point sits outside the organization.

GRC, audit, and assurance in the age of agents

AI and automation are beginning to reshape the control environment. Evidence can be generated continuously, processes can adapt in real time, and digital agents may soon execute tasks once owned by people.

This panel explores what governance, risk, compliance, audit, and SOX controls look like when work becomes increasingly autonomous. Speakers will address accountability, transparency, assurance, control ownership, and the practical steps firms are taking to modernize GRC without creating a black box.

Cyber, privacy & identity, oh no.

Cybersecurity, privacy, identity, and technology governance are no longer separate risk domains. Together, they define whether customers, regulators, and counterparties trust the institution.

This session looks at how firms are turning cyber and privacy programs into measurable trust outcomes. Panelists will discuss identity risk, data protection, deepfakes, synthetic identity, breach response, customer experience, and the governance needed to protect trust while still enabling digital innovation at scale.

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A practical playbook for AI-driven cyber escalation

The time between vulnerability discovery and exploitation has collapsed. Traditional triage models struggle when medium-risk issues can be chained into critical attack paths, third-party dependencies are opaque, and patching cannot move as fast as the threat.

This workshop focuses on what readiness looks like in the Glasswing era. Participants will explore decision governance, attack-path prioritization, break-glass change processes, layered defense, executive reporting, third-party exposure, and the operating model needed to respond at speed without creating organizational chaos.

Digital assets, tokenization, and the new financial perimeter

Digital assets, tokenization, and on-chain finance are moving from experimentation to infrastructure. As they do, risk no longer fits neatly into traditional categories such as market, operational, compliance, or technology risk.

This workshop examines how institutions are redefining the enterprise risk perimeter for digital assets. The discussion will cover on-chain data, controls, AML, sanctions, valuation uncertainty, smart-contract exposure, third-party infrastructure, governance, and regulatory expectations. The focus is on building risk capabilities that can scale with innovation.

How to govern models, agents, and decisions at scale

Many institutions are moving quickly to deploy copilots, decision engines, and autonomous agents. The limiting factor is no longer the technology. It is trust.

This workshop focuses on how firms are building Trusted AI as a practical operating capability. Topics include AI governance, three-lines-of-defense models, explainability, model testing, technical controls, monitoring, drift detection, accountability, and audit readiness. The goal is to help institutions scale AI adoption while maintaining control, credibility, and regulatory confidence.

From algorithms to accountable systems

AI is now shaping credit decisions, financial crime detection, customer interactions, internal operations, and risk management itself. But as adoption accelerates, institutions face a harder question: how do you govern AI as a system, not just as a model?

This keynote explores what it takes to scale AI responsibly across the enterprise. It will examine accountability, explainability, bias, human oversight, third-party dependency, controls, assurance, and the evolving role of risk leaders as AI becomes embedded in core business processes.

Financial crime in the age of modern data

Financial crime is increasingly coordinated, digital, and adaptive. It moves through networks, not isolated events.

This panel examines the shift from rules-based monitoring to intelligence-led detection. Speakers will discuss behavioural signals, graph analytics, cross-channel insights, false-positive reduction, explainability, case management, and investigative workflows. The focus is on how institutions can fight financial crime more effectively by seeing networks, patterns, and intent earlier.

Turning capital, liquidity, and scenarios into decision support

Stress testing, capital planning, and liquidity risk management are often treated as periodic regulatory exercises. Their real value is much larger: helping leaders make faster and better decisions under uncertainty.

This session explores how institutions are building more agile scenario capabilities with better data, faster analysis, clearer governance, and stronger links to management action. Panelists will discuss how to balance rigor with speed, improve executive relevance, and turn stress testing into a steering tool rather than a backward-looking report.

Redefining talent in an AI-augmented financial sector

As AI moves from experimentation into daily operations, financial institutions are rethinking what work should be done by people, what should be automated, and where human judgment matters most. Across risk, finance, compliance, operations, and customer-facing functions, the workforce is being redesigned around new capabilities, new controls, and new expectations.

This panel will examine how AI is changing the shape of teams inside financial institutions. The discussion will focus on which roles are evolving, which skills are becoming more valuable, and how leaders are preparing employees to work effectively alongside automated systems, copilots, decision engines, and agentic tools.

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Modernizing the model ecosystem before AI overwhelms it

For many institutions, the model environment has become fragmented, slow, and difficult to explain. Models sit across teams and platforms, changes take too long, and leaders struggle to understand how models connect or why results differ.

This workshop explores how firms are modernizing their model ecosystems to support faster decisions, stronger transparency, and better governance. Topics include model access, scenario analysis, what-if testing, model interdependencies, explainability, platform modernization, and the controls needed to scale AI safely.

Agentic AI, automation, and human judgment

Credit risk is being reshaped across origination, underwriting, monitoring, collections, and portfolio management. The opportunity is speed and consistency. The risk is losing judgment, explainability, or supervisory confidence.

This workshop examines where automation and AI can improve credit decisions, and where human judgment remains essential. Speakers will discuss credit architecture, model modernization, workflow design, data quality, explainability, model risk, operational risk, and the controls needed to move faster without compromising accountability.

Building the data backbone for AI-enabled risk management

Risk leaders want real-time insight, predictive analytics, and AI-enabled decision support. But those ambitions fail when the underlying data is fragmented, poorly owned, or not trusted.

This workshop focuses on the foundations of modern risk data: quality, lineage, governance, ownership, control, and usability. Using practical examples, including AI and productivity tools such as Microsoft Copilot, the session will examine why the same risk question can produce different answers, and how better data discipline turns AI from a liability into a trusted management tool.