Reinsurance underwriters, treaty & facultative teams, brokers, actuaries, claims professionals, risk managers, and senior insurance professionals seeking a strategic and practical understanding of AI in reinsurance.

By the end of the course, participants will be able to:

• Understand how AI is transforming the reinsurance value chain.
• Identify practical AI use cases across underwriting, pricing, claims, and portfolio management.
• Appreciate the risks, limitations, and governance challenges of AI in reinsurance.
• Evaluate how reinsurers and cedants can responsibly adopt AI to enhance decision-making and resilience.

Module 1

AI Fundamentals & Why It Matters to Reinsurance

Key Topics

• What is AI, Machine Learning, and Generative AI (non-technical overview).
• How AI differs from traditional actuarial and rule-based models.
• Why reinsurance is uniquely suited (and challenged) by AI adoption.
• Data as the foundation: internal, external, and alternative data sources.
• The evolving role of human judgment vs algorithmic decision-making.

Reinsurance Lens

• Long-tail risks, sparse data, and tail dependency.
• Model uncertainty and explainability concerns.
• Impact on underwriting discipline and risk appetite.

Learning Outcome

• Explain key AI concepts and their relevance to reinsurance decision-making.

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Module 2

AI Applications Across the Reinsurance Value Chain

Underwriting & Pricing

• AI-enhanced risk selection and portfolio optimisation.
• Treaty pricing, exposure analysis, and accumulation management.
• Use of AI in catastrophe modelling and climate-adjusted risk assessment.

Claims & Loss Analytics

• AI in claims triage, reserving support, and fraud detection.
• Pattern recognition in complex and catastrophic loss events.
• Improving speed and consistency in claims handling.

Portfolio, Capital & Strategy

• AI for stress testing, scenario analysis, and capital optimisation.
• Early warning signals and emerging risk detection.
• AI-driven insights for retrocession and risk transfer strategies.

Learning Outcome

• Identify practical AI use cases across underwriting, claims, and portfolio management in reinsurance.

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Module 3

Risks, Limitations & Governance of AI in Reinsurance

Key Risks

• Model bias, data quality, and over-reliance on AI outputs.
• Explainability and transparency challenges.
• Regulatory expectations and supervisory scrutiny.
• Cyber, data privacy, and intellectual property risks.

Governance & Controls

• Human-in-the-loop decision frameworks.
• Model validation, monitoring, and auditability.
• Ethical AI and accountability in reinsurance decision-making.

Learning Outcome

• Assess the risks and governance requirements associated with AI adoption in reinsurance.

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Module 4

The Future of Reinsurance in an AI-Driven World

Looking Ahead

• How AI may reshape reinsurer–cedant relationships.
• Impact on reinsurance broking and market intermediation.
• Talent, skills, and organisational implications.
• Balancing innovation, prudence, and trust.

Interactive Discussion

• Case discussion: “Would you trust AI with this reinsurance decision?”
• Group reflection on opportunities vs risks for participants’ organisations.

Learning Outcome

• Evaluate how AI could reshape reinsurance business models and professional roles.

Raymond Cheung is a CEO, Independent Director, and Chartered Actuary with over 20 years of leadership experience across financial services, insurance, fintech, and capital markets in Asia. He most recently served as Group CEO of Basel Medical Group (Nasdaq: BMGL), leading its successful Nasdaq IPO in 2025 and subsequent strategic acquisition to strengthen operational scale and governance.

Raymond currently serves as an Independent Director of SGX- and Nasdaq-listed companies, chairing Risk Management Committees and providing oversight on governance, IPO readiness, restructuring, and M&A. His career includes senior roles as Chief Risk Officer at AIG Asia Pacific and Asia Capital Reinsurance Group, and Regional Insurance Lead at Grab, where he built insurance frameworks across eight Southeast Asian markets.

A former Chair of Singapore’s Risk-Based Capital Working Party, he has worked closely with MAS and regional regulators. Raymond is also an ESG advisor and sustainability trainer, and a UK-qualified Chartered Actuary.

Local Participant: S$141.70 (inclusive of 9% GST)

Overseas Participant: USD100.00

Participants who register at least two months prior to the course commencement date will be entitled to a 10% Early Bird Discount.

A 10% Group Discount is also applicable for organisations registering a minimum of three participants.

Please note that the Early Bird and Group Discounts are not cumulative.