Using Social Data in Claims and Underwriting
Creating a Social Risk Profile
Abstract
Insurers should care about social networking because of who is using it and what is being posted. Usage continues to grow in absolute numbers and to expand into all age groups. Leading approaches are using the social data from these sites in operational applications in claims and underwriting.
In a new report, Using Social Data in Claims and Underwriting, Celent outlines uses of social data in core insurance operations, identifies the policy decisions that should shape an insurer’s social information strategy, and raises technical issues and possible solutions specific to the unique characteristics of social data. The objective of this investigation is to provide insurers with practical considerations to unlock the value of social networks for claims and underwriting.
“The information that is posted by individuals on multiple sites reflects their preferences, lifestyles, and habits,” says, Mike Fitzgerald, Senior Analyst with Celent’s Insurance group and coauthor of the report. “Postings from companies include descriptions of product offerings, services, and operations. In both cases, this social data can be used to build a real-time risk profile.”
However, enthusiasm regarding the potential of these new approaches must be tempered by the recognition that the use of social data is still in its formative stages. “This implementation will not be without challenges,” says Craig Beattie, Analyst with Celent’s Insurance group and coauthor of the report. “Key techniques must be developed or enhanced, including reliable authentication methods, improved data extraction tools, and more advanced analysis tools.”
In order to assist insurers and vendors in making this transition, Celent presents a five-step model to operationalize social data. The model outlines the major decisions that should be addressed in implementation: what data should be used, what technical strategy should be adopted, how to acquire the data, how to analyze it, and how to integrate social data with existing operational systems.