Claims: Predictive model scoring can determine the probability of fraudulent claims so resources can be focused on high-risk transactions. Using predictive analytics, potential high severity or high-frequency claims can be identified early in the claims process, providing the opportunity to mitigate their financial impact.
Location-Based Risk: Identifying where incidents are most likely to occur can help companies more accurately focus resources and allocate costs. Monitoring social media and regional sensors can inform companies of safety issues or the potential for incidents in specific geographies.
Anticipating & Responding to Crises or Disasters: Weather and seismic sensors can inform companies of the probability of a natural disaster, granting time to move people and resources from damage zones. Real-time data from sensors and social media can maximize situational awareness during and after a disaster, and minimize continued risk. In 2012, researchers from the University of Tokyo examined how Twitter could be used for earthquake detection. They referred to Twitter users as “social sensors and regard each tweet as sensory information.” 
If a company has offices in an earthquake-prone area for example, sensors can immediately inform risk managers of a quake and prompt emergency procedures before the people on the ground can even react. Social media data might raise a red flag about rising civil unrest that would necessitate locking down facilities or evacuating personnel.
New Platforms Poised to Reinvent Risk Management
Managing risk is now a continuous process. Risk managers can keep C-suite executives abreast of changing risk conditions in real time for key decisions. Dynamic dashboards, collaborative tools, and on-demand reporting will replace static reports. Risk management platforms that bring it all together will close the capability gap. As a result, the C-suite will no longer be looking in the rear-view mirror with respect to their risk exposures, but will have real-time navigation technology enabling dynamic risk management.
 Takeshi Sakaki and Yutaka Matsuo (2012), “Earthquake Observation by Social Sensors,” Earthquake Research and Analysis—Statistical Studies, Observations and Planning, Dr. Sebastiano D’Amico (Ed.), ISBN: 978-953-51-0134-5