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How Machine Learning is Helping Personalize Travel Insurance Offers

In yet another example of how machine learning is being used to help humans make better decisions, Allianz Travel Insurance has  upgraded its online platform with added personalization based on machine-learning and artificial intelligence technology to deliver better travel insurance policy recommendations, fighting the perception that a travel insurance partner is a poor place to buy an insurance policy.

This new platform selects from  100 different offerings in a matter of seconds, and gets more effective with customer use. According to a recent article in Forbes:

“The technology behind this customization is impressive. Allianz collects anonymized information to power a personalization engine from a partner like Priceline to help it find the right product for the customer. That reduces the time spent researching companies and products and virtually eliminates the chance that customers will pay for coverage they don’t need… The engine itself takes multiple trip and traveler attributes into consideration, selecting from about 100 different products. What’s more, the personalization engine gets smarter every day.”

The utility demonstrated here underscores how machine learning can make decisions based on far more factors than a human mind can process at once. Just a few of the factors that the system takes into account are:

  • customer service hours
  • self-managed vs outsourced travel assistance services
  • in house medical team vs outsourced
  • trip length
  • connecting flights
  • trip cost
  • group size
  • age of travelers
  • reasons for travels
  • connecting flights
  • timing of trip

This type of complex decision making enabled by machine learning algorithms is now available to InetSoft customers, incorporated alongside interactive visualizations, striking a balance between human and machine generated decisions. InetSoft’s flexible data layer also makes incorporating even off premise data (such as the anonymized customer data from a third party provider in this example) easy and intuitive.

For example, the InetSoft sample dashboard pictured below displays flight delays across the United States in real-time, by continuously pulling the data from the FAA website. Click on the screenshot below to open up the live dashboard. The data is accurate and up to date, so you can even use this dashboard to check and see if your flight is ontime!

 

 

 

Keep following The Mashup for more on the latest in business intelligence, machine learning, and data visualizations.

 

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