Insurance Analytics for Beginners: A Practical Guide to Risk, Pricing, Underwriting, Claims, Customer Analytics, Fraud Detection, AI, and Data-Driven Insurance - Tapa blanda

Sinopsis

Insurance is built on risk. Analytics is transforming how that risk is understood, priced, managed, and predicted.

Insurance Analytics for Beginners is a practical, easy-to-understand introduction to how data analytics, artificial intelligence, and predictive models are changing the insurance industry.

Designed for readers who do not need a technical or actuarial background, this book explains how insurers turn policy, customer, claims, underwriting, financial, and external data into better business decisions.

From pricing risk and detecting fraudulent claims to predicting customer churn and using AI in underwriting, the book takes you through the most important applications of analytics across the insurance value chain.

Inside, you'll learn how to:

• Understand the foundations of insurance analytics and the data behind it
• Measure essential insurance KPIs such as loss ratio, combined ratio, claim frequency, claim severity, retention, and profitability
• Apply analytics to underwriting, risk selection, and insurance pricing
• Understand actuarial analytics without complex mathematics
• Analyze claims performance, settlement times, leakage, and reserves
• Detect suspicious claims using fraud analytics and anomaly detection
• Use customer analytics to improve retention, cross-selling, and lifetime value
• Measure agent, broker, and distribution-channel performance
• Analyze portfolio profitability, concentration risk, and reinsurance decisions
• Understand analytics across life, health, auto, and property insurance
• Explore predictive analytics and machine learning in insurance
• Understand how generative AI and tools such as ChatGPT can support insurance analysts
• Build effective underwriting, claims, sales, fraud, and executive dashboards
• Understand AI bias, explainability, privacy, and responsible insurance analytics

Real-world examples and practical case studies connect the concepts to the way modern insurance organizations operate.

The book also includes practical resources for aspiring and working analysts, including insurance KPIs, dashboard frameworks, analytics exercises, a comprehensive glossary, and ready-to-use AI prompts.

Who is this book for?

This book is ideal for insurance professionals, business and data analysts, underwriters, claims professionals, risk managers, insurance sales and distribution teams, MBA and finance students, aspiring data analysts, and anyone interested in understanding how data and AI are reshaping insurance.

Whether you're entering the insurance industry, moving into an analytics role, or simply want to make better data-driven decisions, Insurance Analytics for Beginners will help you understand the numbers behind one of the world's largest and most data-intensive industries.

No advanced mathematics. No coding experience required. Just a practical introduction to turning insurance data into better decisions.

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