Data, AI & Security Summit UK schedule

Data and AI are no longer separate conversations. As financial institutions look to get more value from analytics, automation, and AI, success increasingly depends on how well data and AI leaders work together.

This panel brings together Chief Data & Analytics Officers and Chief AI Officers to discuss what effective partnership looks like in practice. How do organizations align data strategy with AI ambitions? Who owns governance, accountability, and business outcomes? And how can leaders ensure they're building the right foundation for innovation without creating additional risk?

•  Scaling AI is not just about deploying more models. It's about creating the right foundations, from governance and oversight to culture and leadership. Attendees will hear how organizations are navigating these challenges while continuing to innovate and deliver business value.

• Is your biggest AI risk really the model, or the data feeding it?
• Can AI ever be trusted if the underlying data can't be trusted?
• Are organizations investing more in AI innovation than in data integrity?
• Will poor data become the hidden reason most AI initiatives fail to scale?
• How much business risk is created when AI decisions are built on incomplete, inconsistent, or outdated data?

• Expanding the CDAO role from data steward to strategic AI leader, driving business transformation across the enterprise
• Connecting data strategy with AI ambition, turning investments into measurable business outcomes
• Building the trusted data foundations needed for successful AI adoption, improving speed, accuracy, and confidence in decision-making
• Leading the shift from governance-focused programs to value-driven innovation, creating competitive advantage
• Aligning data, analytics, and AI priorities, ensuring efforts deliver meaningful business impact

Panelists:

Jennifer L. Mezzio, Former Global HR Data Officer, FIRST CITIZENS BANK

• Moving from detecting threats to stopping them in real time
• Using AI to identify suspicious activity before it becomes a business problem
• Responding to cyber threats at machine speed while keeping humans in control
• Reducing the time between detection, decision, and action
• Strengthening fraud prevention through continuous monitoring and intelligent intervention

• Turning insights into action: how leading institutions are creating measurable value from data and AI
• Empowering better decisions across the customer journey, risk function, and business operations
• Understanding the human side of AI adoption and what drives trust in AI-powered recommendations
• Embedding intelligence into everyday workflows to make smarter decisions at scale

• How can organizations move quickly with AI without creating new vulnerabilities or governance challenges?
• What are the hallmarks of effective AI governance in organizations that are scaling successfully today?
• How can leaders ensure AI investments remain connected to business outcomes, ethical principles, and customer expectations?
• As AI becomes more autonomous, how do we maintain accountability for its decisions and actions?
• Where does innovation end and institutional risk begin in the age of agentic AI?

• Turning data, analytics, and AI into decisions that create real business value
• Building confidence in AI so teams can act faster and make better decisions
• Understanding when to rely on AI and when human judgment matters most
• Making AI part of everyday decision-making, not just a standalone technology initiative
• Creating a culture where insights lead to action and innovation leads to results

• Are we measuring what is easy to track or what actually drives business success?
• How many AI initiatives can demonstrate clear business value today?
• Is ROI enough, or should success also be measured by resilience, trust, and customer impact?
• What happens when the metrics that drive innovation conflict with the metrics that drive risk management?
• Are leaders rewarding activity and adoption, or actual business outcomes?
• How can organizations avoid chasing AI hype and focus on measurable value creation?

Dan Galeon, Director, Head of Platforms Governance, ROBINHOOD

• Can organizations move fast with AI if they don't trust how their models are making decisions?
• When an AI model gets it wrong, who is ultimately accountable?
• Are we spending more time building models than governing them?
• How much visibility do leaders really have into the AI decisions being made across their organizations?
• Is model governance becoming a business issue rather than a technology issue?

• Expanding financial access through technology-enabled solutions, reaching new customers and underserved markets
• Transforming payments, lending, and wealth management, creating more seamless and efficient experiences
• Partnering across fintech and traditional financial services ecosystems, unlocking innovation and business value
• Responding to evolving customer expectations, driving greater convenience and digital adoption

Keynote Speaker: Yousuf Khatib, Chief AI Strategy Officer, VANTAGE FINANCIAL ALLIANCE

 This interactive workshop explores what effective leadership looks like in an AI-driven world. As AI capabilities continue to evolve, leaders face new challenges: balancing innovation with governance, driving business outcomes while managing risk, and ensuring their organizations have the data foundations, culture, and skills needed to adapt.

• Is regulation the biggest threat to AI innovation, or is poor governance the bigger risk?
• Can financial institutions afford to wait for regulatory clarity before scaling AI?
• Will the winners be those with the best AI, or those with the strongest governance?
• Are organizations building governance frameworks for today's regulations or tomorrow's realities?
• How much innovation is being delayed in the name of risk management, and at what cost?

Panelists:

Randall (Randy) Gordon, Head of Data Governance, CROSS RIVER

• Ensuring transparency and explainability in increasingly complex AI systems
• Managing model risk throughout the AI lifecycle from development and deployment to monitoring and retirement
• Strengthening data quality and governance to support reliable and responsible AI outcomes
• Addressing bias, fairness, and ethical concerns while maintaining model performance and business objectives
• Aligning governance frameworks across multiple jurisdictions with differing regulatory expectations

• Making AI part of the business, not just the technology strategy
• Lessons from organizations that have successfully operationalized AI
• How leading financial institutions are closing the gap between AI ambition and execution
• What it takes to move from experimentation to measurable business impact
• Building the culture, talent, and governance needed for sustained AI success

• Leveraging AI to enhance underwriting accuracy and risk assessment
• Transforming customer experiences through hyper-personalized insurance services
• Harnessing real-time data for proactive risk prevention and mitigation
• Balancing innovation, privacy, and regulatory compliance in data-driven ecosystems
• Predicting emerging risks with advanced analytics and machine learning models

Panelists:

Jerry Xu PhD, FRM, Investment VP, PRUDENTIAL FINANCIAL

• What governance frameworks are most effective for managing AI risk across the insurance value chain?
• How can organizations balance innovation and speed-to-market with responsible AI practices?
• What role do data quality, diversity, and governance play in building trustworthy AI systems?
• How can insurers maintain customer trust while increasing the use of AI and automation?
• What regulatory and compliance challenges should organizations anticipate as AI adoption grows? 

• Leveraging advanced analytics to improve underwriting precision, resulting in faster and more accurate decisions
• Enhancing risk intelligence through predictive analytics, reducing losses and improving portfolio performance
• Optimizing underwriting outcomes with data-driven insights, increasing profitability and operational efficiency
• Identifying key risk drivers with greater precision, enabling better risk selection and management
• Redefining underwriting excellence through precision risk assessment, driving measurable business impact

As insurers face new risk patterns, rising customer expectations, and growing regulatory scrutiny, data and technology are becoming essential drivers of business value. This panel will explore how insurers are using AI and advanced analytics to improve underwriting decisions, streamline claims processing, and create more personalized customer experiences. Speakers will share practical examples of how technologies such as generative AI, automation, IoT, and predictive modeling are delivering measurable outcomes while helping organizations navigate implementation challenges and regulatory considerations.

Panelists:

Kamal Distell, VP Enterprise Data, TRAVELERS

• Transforming business processes with scalable AI and analytics capabilities
• Driving sustainable competitive advantage through continuous innovation and intelligence-led operations
• Measuring business impact with actionable KPIs and performance analytics
• Aligning operational strategies with evolving customer and market demands

Panelists:

Bill Carey, Managing Director, Client Analytics, Commercial Insurance Risk Control Services, LIBERTY MUTUAL INSURANCE

Anuj Gupta, VP - Group Enterprise Data, ARGO GROUP

Beyond compliance, insurers need data they can trust. This presentation will discuss the foundations required to achieve that goal, from understanding where data comes from and how it is used, to improving quality, ownership, and oversight across the enterprise. Real-world examples will illustrate how organizations are overcoming legacy systems and data silos to create a more reliable and scalable data environment.

• How can AI-powered automation improve policy servicing, claims management, and customer communications?
• What emerging technologies are most likely to redefine the insurance customer journey over the next five years?
• How can insurers use predictive analytics to reduce churn and strengthen long-term customer relationships?
• What metrics should organizations track to measure the success of customer-centric AI initiatives?

• Automating underwriting processes, reducing turnaround times and operating costs
• Enhancing decision-making with predictive insights, improving portfolio performance
• Empowering underwriters with intelligent recommendations, increasing productivity and consistency
• Transforming risk assessment through AI innovation, achieving greater accuracy, efficiency, and speed

• Navigating the intersection of AI, cybersecurity, and regulation, enabling innovation without compromising trust
• Strengthening cyber resilience, protecting critical assets and customer data
• Building responsible AI governance frameworks, ensuring transparency and compliance
• Preparing for emerging regulatory requirements, increasing organizational agility and readiness
• Aligning risk, compliance, and technology strategies, creating a competitive advantage in a rapidly evolving landscape

Panelists:

David T. Vanalek, Esq., SVP, Chief Legal and Compliance Officer, RICHMOND NATIONAL INSURANCE

• Building AI-ready data foundations, unlocking more accurate and reliable insights
• Strengthening data quality across the enterprise, improving business performance and risk management
• Establishing governance frameworks for trusted AI, ensuring transparency and compliance
• Eliminating data silos and inconsistencies, enabling enterprise-wide intelligence
• Unlocking the full potential of AI through trusted data, accelerating innovation and competitive advantage 

• How to create a shared vision for data as a strategic business asset?
• How to establish shared accountability for data across the enterprise?
• How to build trust in data to support AI adoption?
• How to break down organizational silos that limit data value?
• How to embed data stewardship into everyday decision-making?
• How to balance governance with innovation?

This interactive workshop explores how insurers can leverage data and analytics to gain a deeper, more holistic view of customer risk. Participants will examine how internal data, third-party sources, behavioral signals, and advanced analytics can be combined to uncover hidden risk patterns, enhance segmentation, and support more informed decision-making across the insurance value chain.

• Making faster decisions with greater confidence, improving responsiveness across the organization
• Gaining a clearer view of risk and opportunity, supporting more informed strategic choices
• Turning data into a competitive advantage, driving growth, efficiency, and customer value
• Aligning people, processes, and insights, creating more consistent business outcomes
• Using data as a strategic asset, enabling precision, agility, and long-term success in a changing insurance landscape

Panelists:

Kevin Nickerson, AVP, Analytics and Sales Enablement, CHUBB

The conversation around AI has shifted from "What is possible?" to "How do we use it responsibly?" Insurers are under pressure to innovate, but they also need to address concerns around data quality, compliance, security, and oversight. This keynote will share how organizations are finding the right balance, embracing AI's potential while putting the safeguards in place to manage risk and build confidence across the business.

• Building trust in AI across the organization, increasing adoption and business value
• Establishing guardrails for responsible AI use, reducing risk without slowing innovation
• Aligning business, technology, legal, and compliance teams, creating shared accountability
• Ensuring AI decisions can be understood and explained, strengthening customer and regulator confidence
• Scaling AI responsibly across underwriting, claims, and operations, delivering measurable outcomes with confidence

•    Exploring how AI-driven impersonation, account takeover and identity attacks are blurring organizational boundaries.
•    Discussing where cyber, fraud, digital identity and financial-crime teams can collaborate more effectively.
•    Understanding how combining data and intelligence can create a more complete view of threats.

•    Exploring how cloud, SaaS and AI adoption are changing where sensitive financial data resides.
•    Discussing how leaders can establish consistent data-security governance across fragmented environments.
•    Understanding how organizations can enable AI access to enterprise data without creating unacceptable exposure.

•    Exploring how the boundaries between cybersecurity, infrastructure and operational resilience are changing.
•    Discussing how CISOs and CIOs can establish shared accountability for critical technology services.
•    Understanding where investment decisions become difficult when security and transformation priorities compete.

•    Exploring the leadership decisions required during the first hours of a major cyber or technology outage.
•    Discussing how cyber, technology, legal, risk and communications leaders coordinate under pressure.
•    Understanding what tabletop exercises reveal about gaps in authority and accountability.

•    Exploring why financial institutions are reassessing increasingly complex cybersecurity technology estates.
•    Discussing the trade-offs between best-of-breed security and integrated platforms.
•    Understanding how CISOs can evaluate consolidation through cost, capability, resilience and concentration-risk lenses.

•    Exploring how evolving regulatory expectations are changing senior security leadership.
•    Discussing what increased scrutiny means for governance, evidence and executive decision-making.
•    Understanding how CISOs can demonstrate that cybersecurity controls operate effectively rather than simply exist.

•    Exploring how regulatory expectations are shaping cybersecurity priorities across New York financial services.
•    Discussing how organizations can turn regulatory requirements into sustainable security capabilities.
•    Understanding how leaders can prepare for continuing changes in oversight and accountability.

•    Exploring how AI is changing the economics, scale and speed of cyberattacks.
•    Discussing where defensive AI can materially improve detection, investigation and response.
•    Understanding how CISOs should balance automation with human oversight and accountability.

•    Exploring the growth of machine, workload, service and AI-agent identities.
•    Discussing how organizations can establish ownership and governance for identities that aren't employees.
•    Understanding how identity leaders can reduce excessive privileges without restricting transformation.

•    Exploring how generative AI is changing impersonation, onboarding and authentication risk.
•    Discussing how financial institutions can strengthen digital trust without creating customer friction.
•    Understanding where responsibility sits across security, fraud, identity and digital leadership.

•    Exploring how financial institutions are moving from isolated AI pilots toward enterprise-wide deployment.
•    Discussing how leaders can establish consistent governance without creating barriers to adoption.
•    Understanding how security, privacy, data, technology and model risk can operate within a common framework

•    Exploring how financial institutions are shifting from cyber prevention toward enterprise resilience.
•    Discussing how CISO, CIO, risk and business leadership should divide responsibility during major incidents.
•    Understanding what meaningful resilience investment looks like beyond compliance and recovery plans.

•    Exploring the potential impact of quantum computing on cryptography, data and financial infrastructure.
•    Discussing how leaders can distinguish immediate migration requirements from longer-term risk.
•    Understanding how cryptographic discovery and crypto-agility fit into today's technology roadmap.

•    Exploring which security capabilities financial institutions still consider strategically important to own.
•    Discussing how managed services, automation and platforms are changing sourcing decisions.
•    Understanding how CISOs evaluate capability, cost, control and resilience when selecting strategic partners.

•    Exploring what boards and executive committees increasingly expect from security leadership.
•    Discussing how CISOs can move conversations beyond vulnerabilities, alerts and maturity scores.
•    Understanding how cyber exposure can be communicated through financial, operational and strategic impact.