Articles - Unlock the Value of Sensor-based Data


It is not often that an entire industry has the opportunity to re-engineer its fundamental value proposition. Yet the emergence of sensor-based data technology is allowing insurance companies to do just that. Now, the once futuristic concepts in telematics, wearable technology that tracks behaviour and promotes healthier living, and real-time risk underwriting can all be integrated into operational capabilities.

 By: Kevin Koenig and Steve LaValle from Ernst & Young
  
 The usage-based “pay-as-you-live” business models will transform product innovation, and enable insurers to connect with customers directly and relevantly based on greater visibility into their changing needs.
  
 Personalization is Key to Engaging Customers
 Sensor-based data can help insurers create usage-based products to personalize the value proposition. These will be tailored to the individual consumer, such as linking life and automobile policies or creating “name-your-price” models. Such models essentially assign more value to people willing to pay more and less value to those who are not. Rather than forcing consumers to pay for insurance they do not need or for miles they do not drive, the usage-based meter becomes a mechanism for personalization.
  
 And usage-based insurance is clearly gaining traction with buyers. According to EY data, there are an estimated 5 million active policies of their kind in 35 countries worldwide and EY projects a 15% market penetration in Europe, Asia and the Americas by 2020. That is good news for insurers and customers. Findings in EY’s recent 2016 Sensor Data Survey: Disrupt or be disrupted show that these products can benefit both insurers and consumers by reducing claims costs by up to 40% and policy administration costs by up to 50%.
  
 Beyond usage, companies are becoming smarter about understanding the risks associated with individuals. Sensor-based data provides deeper insights into individuals and, more importantly from an insurance perspective, their behaviours and expectations. Once insurers understand the risk, sensors will afford a unique opportunity to price products accordingly.
  
 Learning lessons from other industries
 One imperative for insurers is to look to other industries for insights on using sensor data. Insurance has traditionally lagged behind in three critical areas: the need for self-reported data, the challenge of optimizing long-term value and the ability to provide customer value by utilizing insights from new data sources. Looking deeper, industry leaders in data use continually seek to prioritize the integration of external sources. They see three times more opportunity to leverage sensor and other new data and have a bias toward continuous improvement.
  
 Avoiding Adverse Selection
 For insurers, they are looking at a period of rapid change – moving away from the status quo. It is time to rethink and challenge some basic assumptions. If insurers apply usage-based methodology without increasing their knowledge of the customer, they risk adverse selection, which can occur when consumers’ demand for insurance correlates with their potential for loss. This “do-nothing” strategy is the equivalent of a “going-out-of-business” sale and is not an option for the industry.
 Insurers can improve performance by assessing risks more precisely, designing new products faster and pricing them more profitably, using analytics to better understand their customers, and enhancing claims and service experiences. Those who move quickly to leverage sensor-based data will be the ones to disrupt their competition.
  
  
 Kevin Koenig is Insurance Data Excellence Leader at EY, where he guides some of the world’s largest brands through diverse customer and business-related data transformation. Steve LaValle is a principal in the Advisory Services practice at Ernst & Young LLP, where he assists financial services clients in monetizing technology disruption, advanced analytics and business innovation.
  
 The views reflected in this article are the views of the authors and do not necessarily reflect the views of the global EY organization or its member firms.
  

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