Analytics for insurance : the real business of big data / / Tony Boobier

• Autore: Boobier Tony
• Pubblicazione: Chichester, England : , : Wiley, , 2016; ©2016
• Descrizione fisica: 1 online resource (299 p.)
• Disciplina: 368.00285
• Soggetto topico: Insurance - Computer network resources; Assegurances; Recursos electrònics en xarxa
• Soggetto genere / forma: Llibres electrònics
• Classificazione: BUS004000
• Note generali: Includes index.
• Nota di contenuto: Analytics for Insurance: The Real Business of Big Data; Contents; Preface; Acknowledgements; About the Author; Chapter 1: Introduction - The New 'Real Business'; 1.1 On the Point of Transformation; 1.1.1 Big Data Defined by Its Characteristics; 1.1.2 The Hierarchy of Analytics, and How Value is Obtained from Data; 1.1.3 Next Generation Analytics; 1.1.4 Between the Data and the Analytics; 1.2 Big Data and Analytics for all Insurers; 1.2.1 Three Key Imperatives; 1.2.2 The Role of Intermediaries; 1.2.3 Geographical Perspectives; 1.2.4 Analytics and the Internet of Things ; 1.2.5 Scale Benefit - or Size Disadvantage?1.3 How do Analytics Actually Work?; 1.3.1 Business Intelligence; 1.3.2 Predictive Analytics; 1.3.3 Prescriptive Analytics; 1.3.4 Cognitive Computing; Notes; Chapter 2: Analytics and the Office of Finance; 2.1 The Challenges of Finance; 2.2 Performance Management and Integrated Decision-Making; 2.3 Finance and Insurance; 2.4 Reporting and Regulatory Disclosure; 2.5 GAAP and IFRS; 2.6 Mergers, Acquisitions and Divestments; 2.7 Transparency, Misrepresentation, the Securities Act and 'SOX'; 2.8 Social Media and Financial Analytics ; 2.9 Sales Management and Distribution Channels2.9.1 Agents and Producers; 2.9.2 Distribution Management; Notes; Chapter 3: Managing Financial Risk Across the Insur ance Enterprise; 3.1 Solvency II; 3.2 Solvency II, Cloud Computing and Shared Services; 3.3 'Sweating the Assets'; 3.4 Solvency II and IFRS; 3.5 The Changing Role of the CRO; 3.6 CRO as Customer Advocate; 3.7 Analytics and the Challenge of Unpredictability; 3.8 The Importance of Reinsurance; 3.9 Risk Adjusted Decision-Making; Notes; Chapter 4: Underwriting; 4.1 Underwriting and Big Data; 4.2 Underwriting for Specialist Lines ; 4.3 Telematics and User-Based Insurance as an Underwriting Tool4.4 Underwriting for Fraud Avoidance; 4.5 Analytics and Building Information Management (BIM); Notes; Chapter 5: Claims and the 'Moment of Truth'; 5.1 'Indemnity' and the Contractual Entitlement; 5.2 Claims Fraud; 5.2.1 Opportunistic Fraud; 5.2.1.1 Analytics in Opportunistic Fraud; 5.2.2 Organized Fraud; 5.2.2.1 Organized Fraud Detection through Network Analytics; 5.2.2.2 Voice Analytics in the Claims Fraud Process; 5.2.2.3 Fraud Analytics at Inception; 5.3 Property Repairs and Supply Chain Management; 5.4 Auto Repairs ; 5.5 Transforming the Handling of Complex Domestic Claims5.5.1 The Digital Investigator; 5.5.2 Potential Changes in the Claims Process; 5.5.3 Reinvention of the Supplier Ecosystem; 5.6 Levels of Inspection; 5.6.1 Reserving; 5.6.2 Business Interruption; 5.6.3 Subrogation; 5.7 Motor Assessing and Loss Adjusting; 5.7.1 Motor Assessing; 5.7.2 Loss Adjusting; 5.7.3 Property Claims Networks; 5.7.4 Adjustment of Cybersecurity Claims; 5.7.5 The Demographic Time Bomb in Adjusting; Notes; Chapter 6: Analytics and Marketing; 6.1 Customer Acquisition and Retention; 6.2 Social Media Analytics ; 6.3 Demography and How Population Matters
• Sommario/riassunto: "The business guide to Big Data in insurance, with practical application insight Big Data and Analytics for Insurers is the industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. Written from a non-IT perspective, this book focusses less on the architecture and technical details, instead providing practical guidance on translating analytics into target delivery. The discussion examines implementation, interpretation, and application to show you what Big Data can do for your business, with insights and examples targeted specifically to the insurance industry. From fraud analytics in claims management, to customer analytics, to risk analytics in Solvency 2, comprehensive coverage presented in accessible language makes this guide an invaluable resource for any insurance professional. The insurance industry is heavily dependent on data, and the advent of Big Data and analytics represents a major advance with tremendous potential - yet clear, practical advice on the business side of analytics is lacking. This book fills the void with concrete information on using Big Data in the context of day-to-day insurance operations and strategy. Understand what Big Data is and what it can do Delve into Big Data's specific impact on the insurance industry Learn how advanced analytics can revolutionise the industry Bring Big Data out of IT and into strategy, management, marketing, and more Big Data and analytics is changing business - but how? The majority of Big Data guides discuss data collection, database administration, advanced analytics, and the power of Big Data - but what do you actually do with it? Big Data and Analytics for Insurers answers your questions in real, everyday business terms, tailored specifically to the insurance industry's unique needs, challenges, and targets"--; "The book will deal with Big Data and Analytics specifically from an insurance perspective"--
• Titolo autorizzato: Analytics for insurance
• ISBN: 1-119-14109-5; 1-119-14108-7; 1-119-31624-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910134864403321
• Lo trovi qui: Univ. Federico II
• Serie: Wiley finance series.