Did you ever groan at your computer for taking more than 2 seconds to load a document, delete a voicemail that goes on for more than 20 seconds, or get annoyed when a text isn’t answered in 2 minutes? If so, then you may be suffering from technology-induced impatience.
We have lost the ability to just wait. Everyone seems to lament this loss of the slower pace of our pre-digital lives, but I say good riddance. Life is short; fill it up.
In this new world of instant gratification, we have the application program interface (API). Basically, an API specifies how software components should interact including those between different systems. You will hear your technical people talk about “making an API call” with a vendor; what they are referring to is sending or receiving data from another party. Machine to machine.
This can happen in milliseconds (yay, favorite word of impatient people!). API’s are the primary way that Fenris retrieves information from a multitude of data repositories all over the country, both public and private. Similarly, our clients make API calls to Fenris to get our data pre-fills and proprietary scores that enhance their speed and ability to quote policies for the public, and to market new or enhanced products to their own customers.
Let me show a before and after example of how Fenris and APIs can improve the generally arduous process of obtaining a business insurance quote.
- I call a broker
- She faxes or emails me applications from three different carriers
- I fill them out (they basically ask for the same thing, so this is a tedious and writer’s-cramp-inducing experience)
- I scan them and email them back; or I fax them (yes, you did read “fax”)
- She sends them to the carriers; somewhere along the line between the carriers and the broker, they get keyed into a system
- Carriers come back to the broker with more questions based on my answers to their applications
- The broker calls me to get clarification and asks me to make a pen and ink change on the application which I do and then re-scan or re-fax
- Those last two bullets repeat as necessary
- Finally, I get the quotes, select, call, and bind
Elapsed time = 2 months and up. Some carriers have told me that they do this in 2 weeks, but that has never been my experience. And anyway, is 2 weeks supposed to be good? Or, worse yet: how about the carrier that quotes for a small business but gets relevant information after binding and then cancels policies as a routine process? Does anyone really think that’s acceptable?
Let’s reinvent the process channeling our technology-induced impatience:
- Fill out a form online which pre-populates with Fenris information about my business; I validate that information as “correct” and then the broker sends it to carriers with a click of a button (API’s throughout this process)
- Questions are addressed by email but there are fewer of them because the data came from Fenris’s validated sources, not my error-and-omission-prone human brain
- Underwriter knows which applications to work on first, second, or not at all based on a Fenris triage score; underwriter can check for deeper information through an API-driven Fenris dashboard, if she wants
- Quote, select, bind online (API’s again)
Elapsed time = 24-48 hours and it could be even quicker if some of the underwriter’s processes were automated. The carrier that gives legitimate small business quotes within 24 hours is going to get more opportunities from the brokers. Throughput goes up, binds go up, brokers are happy, and customers have a positive experience. Everyone saves time and expense so we all can go home and wear our virtual reality goggles and further satisfy our thirst for immediate gratification. All is good in the world!
If you are interested in pursuing our API library for small business, home and commercial property, personal and commercial auto, and many more to come, give us a call.
- Dana Isaacoff is a 30-year veteran of information technology and the CIO at Fenris Inc. She has help dozens of companies grow by streamlining processes and tapping into (and taming) big data.