Based on the syllabus of the actuarial profession courses on general insurance pricing – with additional material inspired by the author’s own experience as a practitioner and lecturer – Pricing in General Insurance, Second Edition presents pricing as a formalised process that starts with collecting information about a particular policyholder or risk and ends with a commercially informed rate. The first edition of the book proved very popular among students and practitioners with its pragmatic approach, informal style, and wide-ranging selection of topics, including:Background and context for pricingProcess of experience rating, ranging from traditional approaches (burning cost analysis) to more modern approaches (stochastic modelling)Exposure rating for both property and casualty productsSpecialised techniques for personal lines (e.g., GLMs), reinsurance, and specific products such as credit risk and weather derivativesGeneral-purpose techniques such as credibility, multi-line pricing, and insurance optimisationThe second edition is a substantial update on the first edition, including:New chapter on pricing models: their structure, development, calibration, and maintenanceNew chapter on rate change calculations and the pricing cycleSubstantially enhanced treatment of exposure rating, increased limit factors, burning cost analysisExpanded treatment of triangle-free techniques for claim count developmentImproved treatment of premium building and capital allocationExpanded treatment of machine learningEnriched treatment of rating factor selection, and the inclusion of generalised additive modelsThe book delivers a practical introduction to all aspects of general insurance pricing and is aimed at students of general insurance and actuarial science as well as practitioners in the field. It is complemented by online material, such as spreadsheets which implement the techniques described in the book, solutions to problems, a glossary, and other appendices – increasing the practical value of the book.

Constructing Insurable Risk Portfolios offers a data-driven approach to devising risk retention programs that safeguard firms from a multitude of risks. Because firms face many risks, including fire damage to their buildings, liability from management misconduct, and external threats like cyberattacks, this book treats these potential liabilities as a "portfolio." Drawing inspiration from Markowitz portfolio theory, the text leverages techniques from probability, statistics, and optimization to build algorithms that construct optimal risk insurable portfolios under budget constraints.FeaturesThrough engaging case studies and supporting statistical (R) code, readers will learn how to build optimal insurable risk portfolios.This book illustrates a frontier that depicts the trade-off between the uncertainty of a portfolio and the cost of risk transfer. This visual representation, mirroring familiar Markowitz investment tools, enables informed decision-making and easy adoption by risk advisors.This book lays the mathematical groundwork for constructing optimal insurable risk portfolios in an effective and aesthetically pleasing manner.For those interested in the detailed mathematical aspects of insurable risk portfolio optimization, comprehensive proofs and derivations are available in an online supplement.This book equips students, academics, and practitioners with quantitative tools to analyze real-world risk portfolios. Additionally, it empowers financial analysts to provide data-driven insights that enhance their advisory roles for risk managers.

Actuarial loss models are statistical models used by insurance companies to estimate the frequency and severity of future losses, set premiums, and reserve funds to cover potential claims. Actuarial loss models are a subject in actuarial mathematics that focus on the pricing and reserving for short-term coverages.This is a concise textbook written for undergraduate students majoring in actuarial science who wish to learn the basics of actuarial loss models. This book can be used as a textbook for a one-semester course on actuarial loss models. The prerequisite for this book is a first course on calculus. The reader is supposed to be familiar with differentiation and integration.This book covers part of the learning outcomes of the Fundamentals of Actuarial Mathematics (FAM) exam and the Advanced Short-Term Actuarial Mathematics (ASTAM) exam administered by the Society of Actuaries. It can be used by actuarial students and practitioners who prepare for the aforementioned actuarial exams.Key Features:Review core concepts in probability theory.Cover important topics in actuarial loss models.Include worked examples.Provide both theoretical and numerical exercises.Include solutions of selected exercises.

Based on the syllabus of the actuarial profession courses on general insurance pricing – with additional material inspired by the author’s own experience as a practitioner and lecturer – Pricing in General Insurance, Second Edition presents pricing as a formalised process that starts with collecting information about a particular policyholder or risk and ends with a commercially informed rate. The first edition of the book proved very popular among students and practitioners with its pragmatic approach, informal style, and wide-ranging selection of topics, including:Background and context for pricingProcess of experience rating, ranging from traditional approaches (burning cost analysis) to more modern approaches (stochastic modelling)Exposure rating for both property and casualty productsSpecialised techniques for personal lines (e.g., GLMs), reinsurance, and specific products such as credit risk and weather derivativesGeneral-purpose techniques such as credibility, multi-line pricing, and insurance optimisationThe second edition is a substantial update on the first edition, including:New chapter on pricing models: their structure, development, calibration, and maintenanceNew chapter on rate change calculations and the pricing cycleSubstantially enhanced treatment of exposure rating, increased limit factors, burning cost analysisExpanded treatment of triangle-free techniques for claim count developmentImproved treatment of premium building and capital allocationExpanded treatment of machine learningEnriched treatment of rating factor selection, and the inclusion of generalised additive modelsThe book delivers a practical introduction to all aspects of general insurance pricing and is aimed at students of general insurance and actuarial science as well as practitioners in the field. It is complemented by online material, such as spreadsheets which implement the techniques described in the book, solutions to problems, a glossary, and other appendices – increasing the practical value of the book.

Constructing Insurable Risk Portfolios offers a data-driven approach to devising risk retention programs that safeguard firms from a multitude of risks. Because firms face many risks, including fire damage to their buildings, liability from management misconduct, and external threats like cyberattacks, this book treats these potential liabilities as a "portfolio." Drawing inspiration from Markowitz portfolio theory, the text leverages techniques from probability, statistics, and optimization to build algorithms that construct optimal risk insurable portfolios under budget constraints.FeaturesThrough engaging case studies and supporting statistical (R) code, readers will learn how to build optimal insurable risk portfolios.This book illustrates a frontier that depicts the trade-off between the uncertainty of a portfolio and the cost of risk transfer. This visual representation, mirroring familiar Markowitz investment tools, enables informed decision-making and easy adoption by risk advisors.This book lays the mathematical groundwork for constructing optimal insurable risk portfolios in an effective and aesthetically pleasing manner.For those interested in the detailed mathematical aspects of insurable risk portfolio optimization, comprehensive proofs and derivations are available in an online supplement.This book equips students, academics, and practitioners with quantitative tools to analyze real-world risk portfolios. Additionally, it empowers financial analysts to provide data-driven insights that enhance their advisory roles for risk managers.

Actuarial loss models are statistical models used by insurance companies to estimate the frequency and severity of future losses, set premiums, and reserve funds to cover potential claims. Actuarial loss models are a subject in actuarial mathematics that focus on the pricing and reserving for short-term coverages.This is a concise textbook written for undergraduate students majoring in actuarial science who wish to learn the basics of actuarial loss models. This book can be used as a textbook for a one-semester course on actuarial loss models. The prerequisite for this book is a first course on calculus. The reader is supposed to be familiar with differentiation and integration.This book covers part of the learning outcomes of the Fundamentals of Actuarial Mathematics (FAM) exam and the Advanced Short-Term Actuarial Mathematics (ASTAM) exam administered by the Society of Actuaries. It can be used by actuarial students and practitioners who prepare for the aforementioned actuarial exams.Key Features:Review core concepts in probability theory.Cover important topics in actuarial loss models.Include worked examples.Provide both theoretical and numerical exercises.Include solutions of selected exercises.