How cognitive and mobile can provide help during natural disasters

By Wyatt Urmey, on | Banking

Share:

There is a lot of innovation in the marketplace today. Many of these innovations feed on themselves, pushing our own expectations higher — so we want even more seamless experiences when we travel, work with our bank or buy insurance.

However, there are important circumstances where we still need groundbreaking innovation quickly because lives are on the line. In these cases, mobile is the best way to provide this innovation, and it is even more effective when it is supercharged by cognitive and contextual data.

We already combine innovations in new ways to solve problems every day, but we are often limited because the full spectrum of data is not available. Or, if it is available, it is unstructured and therefore will not quickly produce helpful insights. Though mobile offers immediacy, it can’t do all the heavy lifting of processing. We settle for mobile push notifications as a “solution” when a comprehensive cognitive solution is what we really need and want.

Cognitive analysis: The key ingredient

Mobile can offer alerts that an earthquake is coming but may fall short of providing a real-time understanding and situational awareness of the earthquake’s progress and direction. From where did the earthquake originate? Should we expect tidal changes? Which locations are currently the safest? Social media can provide much of this unstructured intelligence immediately, and mobile can be our best guide in times of trouble through its knowledge of our location and understanding of traffic and other changing circumstances. What is missing to make it happen? Cognitive analysis.

Similarly, mobile has wildfire apps that provide danger meters and fire meters, but synthesizing the on-the-ground situational and real-time information from sensors, traffic lights and road cameras could be a game changer. Wildfire can move faster than humans can run, and having the advantage of a navigator app that tells us wind speed, traffic conditions, fire team deployments and other data can help lead us to safety. So, what’s missing? Cognitive analysis.

Providing smart guidance based on unstructured data and sudden, changing circumstances is something that is still ahead of us. Much of this is because of the massive calculations involved in processing that unstructured data and turning it into insight.

Mobility as our safe harbor

According to Inside Towers, mobile networks are becoming more reliable in times of crises. For example, during the latest major hurricane, there were even tests of flying mobile cell phone towers to keep people connected in the storm’s immediate aftermath.

Natural disasters killed 1.35 million people around the world between 1994 and 2013, according to ReliefWeb. The World Economic Forum reported that between 2003 and 2013, these natural disasters cost more than $1.5 trillion globally. Some have already postulated that mobile is proving to be the most effective and efficient means of reaching and informing the public during natural disasters.

So, who takes this problem on? Though governments have a huge opportunity, insurance has the best chance of putting mobile and cognitive to work to make for improved mobile operational risk evaluation. Insurance companies can help their property and casualty lines as well as homeowners insurance by deploying solutions that could improve on-the-ground situational knowledge during natural disasters. And, they’d become heroes to their customers in the process.

So, what’s stopping us?

According to the Institute for Business Value’s 2016 report on innovation in insurance, a majority of insurers still lack the impetus to create groundbreaking innovations, and a majority still focus on innovation at the product level rather than game-changing innovations such as those that offer support during natural disasters or other serious circumstances.

We’re looking forward to new solutions that offer cognitive capabilities through mobile gateways — especially in the moments we need them most.