Spatial Risk Diffusion: Predicting risk linked to human behavior
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The spatial risk diffusion model predicts risk propagation linked to human behavior, highlighting the need for insurers to adopt modern analytics methods to compete with digital disrupters. This model, based on social constructs and peer-reviewed studies, analyzes customer behavior, enabling insurers to identify influential groups and the speed of behavioral changes. By leveraging this advanced understanding, insurers can enhance their risk assessment and gain a competitive edge in the industry.
Spatial Risk Diffusion: Predicting risk linked to human behavior
- 1. Spatial risk diffusion Predicting the propagation of risk inked to human behaviour
- 2. Competing with digital disrupters Traditional Insurance Carriers: • Cannot rely on only usual analytics methods, internal data • Must adopt modern risk-assessment methods Those that do not move out of their comfort zones will be left behind by their competitors Digital Disrupters exploit data to: • Run efficient, agile, profitable operations • Take marketplace leadership positions They will use data from the digitalization of our lives to maximize their risk-assessment capabilities
- 3. The Spatial Risk Diffusion Model Does not assess risk just as it relates to past events Is unlike generalized linear modeling Is a sophisticated predictive human behavioral model Examines risk as a function of: • Customers’ individual and collective behavior • Linkages, influences of behavior across customer segments
- 4. The Spatial Risk Diffusion Model At the heart of the model—the theory of risk as a social construct: Societal norms are formed through social network interactions and influence risk-taking by individuals in the group
- 5. The Spatial Risk Diffusion Model Scientific support: Peer-reviewed medical studies on smoking cessation, obesity by: • Harvard Medical School • University of California – San Diego At the heart of the model—the theory of risk as a social construct: Societal norms are formed through social network interactions and influence risk-taking by individuals in the group
- 6. The Spatial Risk Diffusion Model Our theory: Applied to various behavior-driven risks, insurers could understand the propagation of risk trends throughout the population and predict: • Which groups will influence other groups’ behavior • How long behavior will take to spread
- 7. The Spatial Risk Diffusion Model In partnership with researchers at Stevens Institute of Technology 12-week research study tested: • Theoretical foundation of the model • Our more expansive application of the theory • Predictive capabilities of the model
- 8. The Spatial Risk Diffusion Model The study: Examined 12 years of NHTSA data on teen driving Applied the model to teen driving behavior Accurately predicted changes in driving behavior Identified leaders, laggards in behavior among population groups
- 9. Population data (Census) Time series analysis Significantly correlated Not significantly correlated Pair-wise cross correlations and time lags between crash data time-series of states Highly correlated The Spatial Risk Diffusion Model US States AL AK AZ AR CA CO CT DE FL GA HI Etc AL 0 -3 0 0 0 0 0 0 0 0 0 AK 3 0 6 2 2 3 1 4 3 1 0 AZ 0 -6 0 0 0 -2 0 2 0 -1 -2 AR 0 -2 0 0 0 0 0 -2 -1 -1 -2 CA 0 -2 0 0 0 0 0 0 0 0 -2 CO 0 -3 2 0 0 0 0 1 0 0 0 CT 0 -1 0 0 0 0 0 0 0 0 0 DE 0 -4 2 2 2 0 -1 0 0 1 0 FL 0 -3 0 1 0 0 0 0 0 0 0 GA 0 -1 1 1 0 0 0 -1 0 0 0 Arizona lags Colorado by two years HI 0 0 2 2 2 0 0 0 0 0 0 (Correlation 0.727) Etc Colour represents correlation Number shows lag time in years (2000-2012, Age 15-19) Fatal crashes (NHSTA)
- 10. The Spatial Risk Diffusion Model Significant potential impact on insurers’ financial performance Teen risk attitudes becoming more conservative by about 4% annually Insurers could improve loss ratios by 60 to 100 basis points by accounting for risk diffusion effects gleaned from state-level data Loss-savings opportunity could be larger as analyses refined to more granular zip code or county level For example, in U.S. auto market:
- 11. The Spatial Risk Diffusion Model Insurable behavior-driven risks that could be better assessed include: Workers compensation Automobile Burglary Employers liability Health
- 12. The Spatial Risk Diffusion Model Loss reserving Marketing Public policy campaigns Other areas the model can help:
- 13. Build behavioral-assessment capabilities needed to apply spatial risk diffusion concept within regulatory framework: The Spatial Risk Diffusion Model Identify data points of most value, with highest predictive potential Incentivize customers to share personal data to gain behavioral insights Consider partnering opportunities
- 14. Conclusion The Spatial Risk Diffusion Model would help insurers gain a competitive advantage in risk assessment by allowing them to identify the population groups whose behavior influences other groups. It also would enable insurers to track how long that behavior takes to propagate throughout society. They would become the industry’s disrupters, rather than the disrupted. With this advanced understanding of risk diffusion, insurers would improve their positioning against competitors—including the industry’s digital disrupters—while growing their business.
- 15. For more information and to download the full report visit: www.accenture.com/us-en/insight-spatial-risk-diffusion