Analytics for Insurance : The Real Business of Big Data.

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 Channels -- 2.9.1 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 Tool -- 4.4 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 Claims -- 5.5.1 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 -- 6.4 Segmentation -- 6.5 Promotion Strategy -- 6.6 Branding and Pricing -- 6.7 Pricing Optimization -- 6.8 The Impact of Service Delivery on Marketing Success -- 6.9 Agile Development of New Products -- 6.10 The Challenge of 'Agility' -- 6.11 Agile vs Greater Risk? -- 6.12 The Digital Customer, Multi- and Omni-Channel -- 6.13 The Importance of the Claims Service in Marketing -- Notes -- Chapter 7: Property Insurance -- 7.1 Flood -- 7.1.1 Predicting the Cost and Likelihood of Flood Damage -- 7.1.2 Analytics and the Drying Process -- 7.2 Fire -- 7.2.1 Predicting Fraud in Fire Claims.

7.3 Subsidence -- 7.3.1 Prediction of Subsidence -- 7.4 Hail -- 7.4.1 Prediction of Hail Storms -- 7.5 Hurricane -- 7.5.1 Prediction of Hurricane Damage -- 7.6 Terrorism -- 7.6.1 Predicting Terrorism Damage -- 7.7 Claims Process and the 'Digital Customer' -- Notes -- Chapter 8: Liability Insurance and Analytics -- 8.1 Employers' Liability and Workers' Compensation -- 8.1.1 Fraud in Workers' Compensation Claims -- 8.1.2 Employers' Liability Cover -- 8.1.3 Effective Triaging of EL Claims -- 8.2 Public Liability -- 8.3 Product Liability -- 8.4 Directors and Officers Liability -- Notes -- Chapter 9: Life and Pensions -- 9.1 How Life Insurance Differs from General Insurance -- 9.2 Basis of Life Insurance -- 9.3 Issues of Mortality -- 9.4 The Role of Big Data in Mortality Rates -- 9.5 Purchasing Life Insurance in a Volatile Economy -- 9.6 How Life Insurers can Engage with the Young -- 9.7 Life and Pensions for the Older Demographic -- 9.8 Life and Pension Benefits in the Digital ERA -- 9.9 Life Insurance and Bancassurers -- Notes -- Chapter 10: The Importance of Location -- 10.1 Location Analytics -- 10.1.1 The New Role of the Geo-Location Expert -- 10.1.2 Sharing Location Information -- 10.1.3 Geocoding -- 10.1.4 Location Analytics in Fraud Investigation -- 10.1.5 Location Analytics in Terrorism Risk -- 10.1.6 Location Analytics and Flooding -- 10.1.7 Location Analytics, Cargo and Theft -- 10.2 Telematics and User-Based Insurance ('UBI') -- 10.2.1 History of Telematics -- 10.2.2 Telematics in Fraud Detection -- 10.2.3 What is the Impact on Motor Insurers? -- 10.2.4 Telematics and Vehicle Dashboard Design -- 10.2.5 Telematics and Regulation -- 10.2.6 Telematics - More Than Technology -- 10.2.7 User-Based Insurance in Other Areas -- 10.2.8 Telematics in Commercial Insurances -- Notes -- Chapter 11: Analytics and Insurance People -- 11.1 Talent Management.

11.1.1 The Need for New Competences -- 11.1.2 Essential Qualities and Capabilities -- 11.1.2.1 Foundational Insurance Knowledge -- 11.1.2.2 Technology Insight -- 11.1.2.3 Quickness to Learn and Adapt -- 11.1.2.4 Problem Solving -- 11.1.2.5 Collaborative and Communication Skills -- 11.2 Talent, Employment and the Future of Insurance -- 11.2.1 Talent Analytics and the Challenge for Human Resources -- 11.3 Learning and Knowledge Transfer -- 11.3.1 Reading Materials -- 11.3.2 Formal Qualifications and Structured Learning -- 11.3.3 Face-to-Face Training -- 11.3.4 Social Media and Technology -- 11.4 Leadership and Insurance Analytics -- 11.4.1 Knowledge and Power -- 11.4.2 Leadership and Influence -- 11.4.3 Analytics and the Impact on Employees -- 11.4.4 Understanding Employee Resistance -- Notes -- Chapter 12: Implementation -- 12.1 Culture and Organization -- 12.1.1 Communication and Evangelism -- 12.1.2 Stakeholders' Vision of the Future -- 12.2 Creating a Strategy -- 12.2.1 Program Sponsorship -- 12.2.2 Building a Project Program -- 12.2.3 Stakeholder Management -- 12.2.4 Recognizing Analytics as a Tool of Empowerment -- 12.2.5 Creation of Open and Trusting Relationships -- 12.2.6 Developing a Roadmap -- 12.2.7 Implementation Flowcharts -- 12.3 Managing the Data -- 12.3.1 Master Data Management -- 12.3.2 Data Governance -- 12.3.3 Data Quality -- 12.3.4 Data Standardization -- 12.3.5 Storing and Managing Data -- 12.3.5.1 Industry Data Models -- 12.3.5.2 Data Platform -- 12.3.5.3 Cloud Computing -- 12.3.5.4 Computer 'Appliances' -- 12.3.5.5 The Lexicon of Technology -- 12.3.6 Security -- 12.4 Tooling and Skillsets -- 12.4.1 Certification and Qualifications -- 12.4.2 Competences -- Notes -- Chapter 13: Visions of the Future? -- 13.1 Auto 2025 -- 13.2 The Digital Home in 2025 - 'Property Telematics' -- 13.3 Commercial Insurance - Analytically Transformed.

13.4 Specialist Risks and Deeper Insight -- 13.5 2025: Transformation of the Life and Pensions Industry -- 13.6 Outsourcing and the Move Away from Non-Core Activities -- 13.7 The Rise of the Super Supplier -- Notes -- Chapter 14: Conclusions and Reflections -- 14.1 The Breadth of the Challenge -- 14.2 Final Thoughts -- Notes -- Appendix A: Recommended Reading -- Appendix B: Data Summary of Expectancy of Reaching 100 -- Appendix C: Implementation Flowcharts -- Appendix D: Suggested Insurance Websites -- Appendix E: Professional Insurance Organizations -- Index -- End User License Agreement.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.