This course is designed for a broad range of professionals across the general insurance ecosystem who engage with or are impacted by pricing decisions — whether from a technical, commercial, or risk management perspective.

It is suitable for both technical and non-technical roles and is especially valuable for those navigating market cycles or seeking to deepen their understanding of how pricing is determined, challenged, and optimised.

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Recommended for:

• Underwriters (General Insurance, Specialty, and Reinsurance)
• Actuaries and Pricing Analysts involved in rate setting and model development
• Product Managers and Portfolio Owners overseeing performance and strategy
• Insurance Buyers and Risk Managers looking to better understand pricing drivers
• Brokers and Client Managers advising clients on market conditions and pricing trends
• Claims and Reserving Professionals contributing to pricing insights
• Regulatory, Compliance, and Filing Experts
• New joiners or cross-functional teams working with pricing stakeholders

At the end of the programme, participants should be able to:

• Understand the insurance pricing landscape, including market dynamics, cover structures, and the underwriting cycle.
• Apply core pricing methodologies such as burning cost, frequency/severity modelling, and experience vs exposure-based rating.
• Break down the components of a technical premium, including cost loadings, capital considerations, and profit margins.
• Evaluate pricing applications across multiple lines of business, including property, casualty, and reinsurance.
• Incorporate external influences such as reinsurance, catastrophe risk, inflation, and litigation trends into pricing decisions.
• Quantify and communicate uncertainty in pricing assumptions and outputs.
• Understand the pricing control cycle and perform rate adequacy and risk-adjusted rate change assessments.
• Adapt pricing strategies to emerging risks and evolving market conditions.
• Understand the application of Artificial Intelligence in general insurance pricing, including its use in analytics, automation, and emerging trends, as well as the associated governance and risk considerations.

Laying the Foundation: Classical Pricing Techniques

• Welcome & Introduction
• The Insurance Market Landscape
• Insurance and Reinsurance Products
• Cover Structures
• Pricing in Context
• Experience Rating: A Generic Process
• Modelling Fundamentals
• Components of the Technical Premium
• Experience vs Exposure-Based Rating

Advanced Pricing & Applications in a Changing Market

• Pricing Cycles & Controls
• Pricing Applications by Line of Business
• Pricing Across Multiple Lines
• Case Discussions & Emerging Themes
• Wrap-Up Discussion: Building a Best-in-Class Pricing Function

Use Cases of AI within Insurance

• Possibilities and Implications of AI use within Insurance
• AI in Analytics and Data Science
• Workflow Automation

Group Exercise 3: Hands-on Exercises with AI

Wrap-Up Discussion: Future of AI and Insurance

• AI Governance and Risk Management
• AI Trends
• Q&A and audience reflection

Ishita Bhatia FIA is a Fellow of the Institute of Actuaries (UK) and holds a Certificate in London Market Insurance from the Chartered Insurance Institute. She is the Group Head of Specialty Pricing at QBE, where she leads global pricing strategy and portfolio governance across major Specialty classes including Marine, Natural Resources, Aviation, Construction & Engineering, and Renewables. In this role, she works closely with underwriting, claims, and data science teams internationally to embed consistent pricing methodologies, enhance model sophistication, and support disciplined, evidence based decision making across regions.

Prior to her current role, Ishita led Pricing and Data Science for QBE’s Natural Resources, Construction, and International Markets portfolios, delivering pricing solutions in complex and evolving areas such as Renewable Energy. Before joining QBE, she spent nearly a decade at Willis Towers Watson in Singapore, advising insurers and corporates on actuarial modelling, capital strategy, and risk financing across a wide range of P&C and specialty risks.

Ishita brings deep expertise in general insurance pricing, portfolio level loss dynamics, aggregation and volatility management, and coverage structures across underwriting cycles. She has co authored a paper in the British Actuarial Journal titled “Loss Modelling from First Principles,” and serves as a Subject Matter Expert and instructor with the Singapore College of Insurance and International Union of Marine Insurance, contributing actively to professional education and capability development across the marine and specialty insurance market.

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Justin Chan is a Chartered Actuary of the Institute and Faculty of Actuaries (IFoA) with 20 years of experience spanning actuarial science, data science, artificial intelligence, and insurance analytics. He has held senior roles across leading insurers and reinsurers, including Prudential, Swiss Re, AIA Singapore, and Singlife, where he led advanced analytics and machine learning initiatives for underwriting, claims, customer analytics, and policyholder behaviour.

Most recently, Justin served as Product Owner and Senior AI Engineer at Prudential, where he led the development of large language model (LLM) applications for claims processing and agent performance insights. Earlier, as Senior Actuarial Data Scientist at Swiss Re, he led machine learning projects for policy lapse prediction and contributed to global data science governance and best practices.

Justin is also an experienced educator and trainer. He has taught data science and analytics as an instructor at General Assembly and conducts training in Python, generative AI, and data analytics for organisations including NTU and industry partners. He is an active contributor to the Singapore Actuarial Society and regularly mentors actuarial students and professionals.

He holds a BEng (Hons) in Electrical Engineering from the National University of Singapore and a Graduate Diploma in Actuarial Science (Distinction) from the University of Kent.

Full Course Fee: S$827.31  (inclusive of 9% GST)

Participants who register by 29 May 2026 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.