تجزیه و تحلیل مه داده در بیمه

Preface xi

Acknowledgements xiii

About the Author xv

CHAPTER 1 Introduction – The New ‘Real Business’ 1

1.1 On the Point of Transformation 2

1.1.1 Big Data Defined by Its Characteristics 3

1.1.2 The Hierarchy of Analytics, and how Value is Obtained from Data 6

1.1.3 Next Generation Analytics 7

1.1.4 Between the Data and the Analytics 9

1.2 Big Data and Analytics for All Insurers 10

1.2.1 Three Key Imperatives 10

1.2.2 The Role of Intermediaries 13

1.2.3 Geographical Perspectives 14

1.2.4 Analytics and the Internet of Things 15

1.2.5 Scale Benefit – or Size Disadvantage? 15

1.3 How Do Analytics Actually Work? 17

1.3.1 Business Intelligence

1.3.2 Predictive Analytics 20

1.3.3 Prescriptive Analytics 22

1.3.4 Cognitive Computing 23

Notes 24

CHAPTER 2 Analytics and the Office of Finance 25

2.1 The Challenges of Finance 26

2.2 Performance Management and Integrated Decision-making 27

2.3 Finance and Insurance 27

2.4 Reporting and Regulatory Disclosure 29

2.5 GAAP and IFRS 29

2.6 Mergers, Acquisitions, and Divestments 30

2.7 Transparency, Misrepresentation, The Securities Act and ‘SOX’ 31

2.8 Social Media and Financial Analytics 32

2.9 Sales Management and Distribution Channels 33

2.9.1 Agents and Producers 34

2.9.2 Distribution Management 35

Notes 36

CHAPTER 3 Managing Financial Risk across the Insurance Enterprise 37

3.1 Solvency II 37

3.2 Solvency II, Cloud Computing and Shared Services 40

3.3 ‘Sweating the Assets’ 40

3.4 Solvency II and IFRS 41

3.5 The Changing Role of the CRO 42

3.6 CRO as the Customer Advocate 45

3.7 Analytics and the Challenge of Unpredictability 45

3.8 The Importance of Reinsurance 46

3.9 Risk Adjusted Decision-Making 46

Notes 49

CHAPTER 4 Underwriting 51

4.1 Underwriting and Big Data 52

4.2 Underwriting for Specialist Lines 54

4.3 Telematics and User-Based Insurance as an Underwriting Tool 55

4.4 Underwriting for Fraud Avoidance 56

4.5 Analytics and Building Information Management (BIM) 57

Notes 58

CHAPTER 5 Claims and the ‘Moment of Truth’ 61

5.1 ‘Indemnity’ and the Contractual Entitlement 61

5.2 Claims Fraud 62

5.2.1 Opportunistic Fraud 63

5.2.2 Organized Fraud 64

5.3 Property Repairs and Supply Chain Management 66

5.4 Auto Repairs 71

5.5 Transforming the Handling of Complex Domestic Claims 73

5.5.1 The Digital Investigator 73

5.5.2 Potential Changes in the Claims Process 75

5.5.3 Reinvention of the Supplier Ecosystem 76

5.6 Levels of Inspection 77

5.6.1 Reserving 78

5.6.2 Business Interruption 79

5.6.3 Subrogation 80

5.7 Motor Assessing and Loss Adjusting 81

5.7.1 Motor Assessing 82

5.7.2 Loss Adjusting 83

5.7.3 Property Claims Networks 84

5.7.4 Adjustment of Cybersecurity Claims 87

5.7.5 The Demographic Time Bomb in Adjusting 87

Notes 88

CHAPTER 6 Analytics and Marketing 91

6.1 Customer Acquisition and Retention 93

6.2 Social Media Analytics 96

6.3 Demography and How Population Matters 97

6.4 Segmentation 98

6.5 Promotion Strategy 100

6.6 Branding and Pricing 100

6.7 Pricing Optimization 101

6.8 The Impact of Service Delivery on Marketing Success 102

6.9 Agile Development of New Products 103

6.10 The Challenge of ‘Agility’ 104

6.11 Agile vs Greater Risk? 105

6.12 The Digital Customer, Multi- and Omni-Channel 105

6.13 The Importance of the Claims Service in Marketing 106

Notes 107

CHAPTER 7 Property Insurance 109

7.1 Flood 109

7.1.1 Predicting the Cost and Likelihood of Flood Damage 110

7.1.2 Analytics and the Drying Process 111

7.2 Fire 112

7.2.1 Predicting Fraud in Fire Claims 113

7.3 Subsidence 115

7.3.1 Prediction of Subsidence 116

7.4 Hail 119

7.4.1 Prediction of Hail Storms 120

7.5 Hurricane 121

7.5.1 Prediction of Hurricane Damage 121

7.6 Terrorism 122

7.6.1 Predicting Terrorism Damage 123

7.7 Claims Process and the ‘Digital Customer’ 124

Notes 125

CHAPTER 8 Liability Insurance and Analytics 127

8.1 Employers’ Liability and Workers Compensation 127

8.1.1 Fraud in Workers Compensation Claims 128

8.1.2 Employers’ Liability Cover 130

8.1.3 Effective Triaging of EL Claims 130

8.2 Public Liability 131

8.3 Product Liability 132

8.4 Directors and Officers Liability 133

Notes 134

CHAPTER 9 Life and Pensions 135

9.1 How Life Insurance Differs from General Insurance 136

9.2 Basis of Life Insurance 137

9.3 Issues of Mortality 138

9.4 The Role of Big Data in Mortality Rates 139

9.5 Purchasing Life Insurance in a Volatile Economy 140

9.6 How Life Insurers Can Engage with the Young 141

9.7 Life and Pensions for the Older Demographic 142

9.8 Life and Pension Benefits in the Digital Era 143

9.9 Life Insurance and Bancassurers 145

Notes 147

CHAPTER 10 The Importance of Location 149

10.1 Location Analytics 149

10.1.1 The New Role of the Geo-Location Expert 149

10.1.2 Sharing Location Information 150

10.1.3 Geocoding 150

10.1.4 Location Analytics in Fraud Investigation 151

10.1.5 Location Analytics in Terrorism Risk 152

10.1.6 Location Analytics and Flooding 152

10.1.7 Location Analytics, Cargo and Theft 154

10.2 Telematics and User-Based Insurance (‘UBI’) 155

10.2.1 History of Telematics 155

10.2.2 Telematics in Fraud Detection 157

10.2.3 What is the Impact on Motor Insurers? 157

10.2.4 Telematics and Vehicle Dashboard Design 158

10.2.5 Telematics and Regulation 159

10.2.6 Telematics – More than Technology 160

10.2.7 User-Based Insurance in Other Areas 161

10.2.8 Telematics in Commercial Insurances 162

Notes 164

CHAPTER 11 Analytics and Insurance People 167

11.1 Talent Management 167

11.1.1 The Need for New Competences 168

11.1.2 Essential Qualities and Capabilities 169

11.2 Talent, Employment and the Future of Insurance 173

11.2.1 Talent Analytics and the Challenge for Human Resources 173

11.3 Learning and Knowledge Transfer 174

11.3.1 Reading Materials 175

11.3.2 Formal Qualifications and Structured Learning 175

11.3.3 Face-to-Face Training 176

11.3.4 Social Media and Technology 177

11.4 Leadership and Insurance Analytics 178

11.4.1 Knowledge and Power 179

11.4.2 Leadership and Influence 179

11.4.3 Analytics and the Impact on Employees 1

11.4.4 Understanding Employee Resistance 2

Notes 4

CHAPTER 12 Implementation 5

12.1 Culture and Organization 8

12.1.1 Communication and Evangelism 192

12.1.2 Stakeholders’ Vision of the Future 193

12.2 Creating a Strategy 193

12.2.1 Program Sponsorship 194

12.2.2 Building a Project Program 195

12.2.3 Stakeholder Management 197

12.2.4 Recognizing Analytics as a Tool of Empowerment 198

12.2.5 Creation of Open and Trusting Relationships 199

12.2.6 Developing a Roadmap 200

12.2.7 Implementation Flowcharts 202

12.3 Managing the Data 202

12.3.1 Master Data Management 203

12.3.2 Data Governance 203

12.3.3 Data Quality 204

12.3.4 Data Standardization 204

12.3.5 Storing and Managing Data 205

12.3.6 Security 207

12.4 Tooling and Skillsets 207

12.4.1 Certification and Qualifications 208

12.4.2 Competences 208

Notes 209

CHAPTER 13 Visions of the Future? 211

13.1 Auto 2025 211

13.2 The Digital Home in 2025 – ‘Property Telematics’ 214

13.3 Commercial Insurance – Analytically Transformed 2

13.4 Specialist Risks and Deeper Insight 220

13.5 2025: Transformation of the Life and Pensions Industry 221

13.6 Outsourcing and the Move Away from Non-Core Activities 223

13.7 The Rise of the Super Supplier 224

Notes 225

CHAPTER 14 Conclusions and Reflections 227

14.1 The Breadth of the Challenge 229

14.2 Final Thoughts 230

Notes 231

APPENDIX A Recommended Reading 233

APPENDIX B Data Summary of Expectancy of Reaching 100 235

APPENDIX C Implementation Flowcharts 239

APPENDIX D Suggested Insurance Websites 265

APPENDIX E Professional Insurance Organizations 267

Index 269