Insurance: the business of uncertainty
“Change is the only constant in life" - Heraclitus, a Greek philosopher
There is so much uncertainty out there, and change is inevitable- regardless of the fight for humanity to keep many things constant in their lives when things are familiar. We are all familiar with change and unfortunately, it’s not all good. Things like accidents (workplace and otherwise), natural disasters, etc. Do happen regularly – like a pandemic! This is why it’s good to have back-up in those times of uncertainty. As any other business, insurance needs growth to survive and it’s important to do this in an ethical manner. Help people when they need it. But it is a business…
Protect and Thrive
There are insurance agencies that have learned to help those in need and develop a better way to recoup savings. Insurance like many other industries is also in the business of big data, and if you want to be efficient you need to adopt Artificial Intelligence. When it comes to data, generally getting down to the basics is important. Remember your 5 V’s! (Velocity, Volume, Value, Variety and Veracity). You can recoup savings by streamlining the automation of processes and improve innovations utilizing one type of Artificial Intelligence technology - Natural Language Processing (NLP) to transform your semi-structured and unstructured data..
Insurance adopters of AI/ML are seeing significant benefits
Take a moment and look around your company. How many platform solutions do you have that do something similar? There is valuable information hidden in text (claims, call center transcripts, client documentation, competitors’ offerings etc.) Why make it more complicated than you need to and use multiple platforms for your unstructured data when you can use one for many needs?
It’s not just theoretical- NLP Data Factory
A large US Insurance organization decided they needed to adopt an NLP solution to replace their manual efforts. Utilizing NLP Data Factory, for its unstructured needs they started with just risk and underwriting algorithms and are now looking to expand into other areas
What were the results?
- Improved models in days (not months)
- Fast feature development environment (minutes vs days)
- Eliminated large data storage requirements
- Processing 8M documents/hour and automatically extract 500+ features
You can streamline data processes- not people
People are complicated- situations change and we all need protection sometimes. Insurance companies (those specific to healthcare or otherwise) need to thrive under difficult circumstances while continuing to protect and help their members. But data processes don’t have to be as complicated, flexibility is possible- one platform for many uses.