The findings from the Capgemini Research Institute’s World Property and Casualty Insurance Report 2024 shed light on the current landscape of underwriting in the insurance industry, particularly regarding the adoption of artificial intelligence (AI) and machine learning (ML) technology. Here are some key takeaways from the report:
1. **Complexity of Underwriting Process**: A significant portion (42%) of policyholders find the current underwriting process complex and lengthy, highlighting a need for simplification and efficiency.
2. **Acceptance of Automated Recommendations**: While nearly half (43%) of underwriters regularly accept automated recommendations from predictive analytics tools, there is still some hesitation among underwriters to fully trust decision-support tools.
3. **Criticality of Predictive Models**: The vast majority (83%) of Property and Casualty (P&C) insurance executives believe that predictive models are critical for the future of underwriting, indicating a recognition of the importance of AI/ML in driving underwriting decisions.
4. **Challenges and Concerns**: Reasons for underwriters’ reluctance to fully embrace AI/ML tools include perceived overcomplexity (67%) and concerns over data integrity (59%).
5. **Need for Explainability and Transparency**: Insurers must ensure that AI/ML models are explainable and transparent to gain the trust and buy-in of underwriters. Continuous assessment of progress is also crucial.
6. **Emerging Data Sources**: There is growing interest among underwriters in leveraging data from emerging sources such as drone image data and connected devices for real-time information about assets. However, insurers are currently ill-equipped to effectively support and analyze these data sources.
7. **Impact of Incomplete Risk Evaluation**: Incomplete risk evaluation impacts a significant majority (77%) of insurers, highlighting the need for better data resources and analysis capabilities.
8. **Call for Modernization**: Adam Denninger, global insurance industry leader at Capgemini, emphasizes the need for insurers to modernize core systems and deploy advanced technologies to drive better outcomes and transparency in underwriting.
Overall, the report underscores the importance of embracing AI-driven insights and automation to drive competitiveness and profitability in the insurance industry. However, it also highlights the challenges and hurdles that insurers must address, including concerns about data integrity, complexity, and the need for transparency and explainability in AI/ML models.
Source: insurancebusinessmag.com
