Assistant Vice President of Research and Development
Get the full picture when disaster strikes
SAS® Visual Analytics dashboard gives Aviva Canada executives up-to-the-minute information about claims
In June 2013, days of torrential rain inundated the city of Calgary, Alberta, and surrounding areas. The Bow and Elbow Rivers overflowed their banks, causing the evacuation of 26 neighborhoods and 100,000 people. Four died, and a state of emergency was declared in 32 communities. The Insurance Bureau of Canada called it the costliest natural disaster in Canadian history, with insurable damages of more than $1.7 billion.
Data from that disaster led Charles Dugas, Assistant Vice President of Research and Development, to model a catastrophe dashboard in SAS Visual Analytics. “During the flood, executives could easily monitor the amounts of claims coming in, and by geocoding them, we could map them out and see which customers and brokers were most affected.”
Throughout the company, Dugas says, use cases for SAS Visual Analytics fall into two categories: reporting, like the dashboard above, and exploration.
“The exploration side is really for analysts who want to better understand their data and check for relationships, one-to-one relationships and one-to-many relationships,” he says. For example, certain loss causes shouldn’t be associated with certain types of coverage; analysts can perform a “sanity check” on the data, he says.
“SAS Visual Analytics is so fast, you move from asking a few questions of a data set to entering into a ‘chat’ with a data set,” Dugas says. “You ask a question, the answer comes back immediately. That generates another question, and the loop goes on. You can gain intelligence about your data much faster that way.”
On the reporting side, Dugas hopes to use SAS Visual Analytics to automate what can be a very manual process.
SAS Visual Analytics is so fast, you move from asking a few questions of a data set to entering into a ‘chat’ with a data set.
“We have a lot of people working on reporting, spending a lot of time in an assortment of different tools,” Dugas says. “With SAS Visual Analytics we want to not only streamline a lot of these processes, we want to enhance those static reports and make them dynamic. So an executive can look at an aggregated, high-level view of the business and start drilling down through different segments, different policies - even down to an individual customer.”
Dugas says there are clear benefits to the business, though they haven’t been synthesized into a single return on investment number: customer retention, fraud detection, better intelligence for agents and brokers, and even the ability to become more competitive by adjusting pricing in months rather than the normal two-year cycle.
And there’s more to come. High-performance analytics in a Hadoop structure and neural networks in a visual analytics environment are on Dugas’ road map.
“In a couple of years, what I’m hoping for is to have a much cleaner, clearer path from data sources all the way to the scores, modeling those scores, and monitoring those models,” Dugas says. “That’s what I’m hoping for.”
Quickly help thousands of vulnerable customers get their lives back on track after a disaster.
- Speedier claim fulfillment.
- Better customer retention.
- Fraud detection.
- Faster competitive pricing.