Title page
Contents
Executive Summary 4
1. Introduction 6
2. Applications of new technologies in insurance for risk assessment and supporting policyholder risk reduction 11
3. Challenges to technology adoption in insurance for risk assessment and supporting policyholder risk reduction 22
4. Creating an enabling environment for the application of technology for risk assessment and supporting policyholder risk reduction in insurance 47
5. Conclusion 58
References 59
Table 4.1. Regulatory sandbox design elements in India, Indonesia and Malaysia 53
Figure 1.1. Share of insurance companies that expect to increase investment in 2022 selected technologies 7
Figure 1.2. Technology developments relevant for core insurance business functions 8
Figure 1.3. Technology applications in risk assessment and supporting policyholder risk reduction 9
Figure 2.1. Leveraging data for risk assessment and support for risk reduction 13
Figure 3.1. Potential regulatory limitations to applying new data or advanced analytics in underwriting and pricing 39
Boxes
Box 2.1. Incorporating earth observation imagery into property insurance underwriting and pricing 14
Box 2.2. Data sharing and integration: the role of APIs 15
Box 2.3. Providing access to advanced analytical capacities: the role of cloud computing 18
Box 2.4. Automated underwriting systems 19
Box 2.5. Digital health and wellness platforms offered by insurance companies: selected examples 21
Box 3.1. Consumer willingness to share data 25
Box 3.2. NAIC's draft Consumer Privacy Protections Model Law 29
Box 3.3. The use of analytics for price optimisation, price walking and differential pricing 33
Box 3.4. Evolutions in rate and form regulation in India 36
Box 3.5. Phased de-tarrification of property and motor vehicle insurance in Malaysia 38
Box 3.6. IRDAI Guidelines on Wellness and Preventive Features 41
Box 3.7. Supervisory guidance and requirements on (cloud) outsourcing by insurance companies 44
Box 3.8. Data localisation requirements 45
Box 4.1. Measuring impact of artificial intelligence and machine learning models on customer outcomes 49
Box 4.2. Revisions to the NAIC Unfair Trade Practices Act (United States) 50
Box 4.3. International efforts to build trust in cross-border data flows 51
Box 4.4. Regulatory sandboxes: effective design features 55
Box 4.5. Responding to financial education and consumer protection implications of digitalisation 57