Text mining is a new concept which will speed up the process of buying protection.
Customers will notice a better experience, particularly at the underwriting stage of their policy. Advisers will welcome the increased speed and accuracy it brings but also how it will make it easier to secure cover for clients with complex medical histories.
Text mining is one application of natural language processing, which is a subset of artificial intelligence (AI), a general term for machines acting like or interacting with humans.
Natural language processing is the specific ability for machines to translate content that humans can read into content that machines can read.
Text mining is the creation of useful knowledge or insights from that content.
Financial services companies are already using text mining even though it’s not something we hear much.
Companies are using text mining for reading and understanding the intent of financial contracts and in customer services for email, triage and routing.
Financial research is a wide area where companies are using it and corporate releases and reports are all now being read by algorithms looking to help spot trends and pick stocks for investments.
Quick and fair process
From a protection point of view, we ultimately want to help customers experience a quick and fair process when applying for life insurance.
But for clients with complex medical histories the application process can be long and drawn out, a poor experience for the customer and a frustrating process for the adviser to manage.
We want all customers to have the opportunity to receive the quick and transparent service that automation brings with the knowledge we are assessing their individual situations fairly and accurately.
Using data to help with this through automation is key.
But when that data is in unstructured formats like medical records, machines can’t read it which means those efficiency gains brought by automation are not available to a whole segment of customers who require underwriting based on the medical record.
Text mining is the missing piece in the automation puzzle. It fills the gap that in the past has left customers with complex medical histories having to endure a dramatically different experience when applying for life insurance.
First steps
The first step is to make that unstructured data machine-readable, making it structured and coherent. And that’s done by text mining.
We know that some see underwriting as quite an intrusive process and we’re keen to work on anything that would make the process a better experience for customers.
Innovation in text mining has come a long way in recent years. It’s at a stage where the skill level of natural language processing means machines can do the cognitive tasks that previously could only be done by humans.
And so, reading and understanding medical reports is a challenge that text mining is probably now mature enough to begin to tackle.
So, text mining can help to improve the underwriting process but it’s still relatively unknown.
Collaboration in text mining lab
To make it easier for people wanting to have a go, we’ve created the Text Mining Lab where we are encouraging partners to put text mining skills into the hands of many different people in different roles throughout their business to discover where they see the greatest value and to help them measure what impact text mining might have for them in the future.
The lab will help us discover what works for partners and what does not in a very collaborative way. It’s effectively beta access to the text mining skills we’ve developed.
Participants at the lab will have access to the lab portal, which allows them to upload the unstructured medical reports and then receive back the enriched structured data reports.
We also regularly meet with lab partners to help design experiments and to share feedback.
It’s meant to be a very lightweight way of testing potential applications across the underwriting and claims customer experience and giving partners the opportunity to test those big ideas in a quick way.
The Text Mining Lab is now live in the UK and the US, with plans to extend the lab to include Asia and Australia.
Short and long-term efficiencies
I mentioned earlier that we must be careful about customer trust as data, particularly medical data, is a sensitive area. The sensitivity of the data we are working with is something we need to be water-tight on.
I’m convinced text mining will make the underwriting process a better experience for customers and advisers in future. As insurers begin to adopt it, we’ll see an increase in straight through applications.
In the short term, the insights that text mining enables will highlight efficiencies, reduce risks and even help to redefine referral processes for some conditions, reducing the impact of the slow and expensive manual processes we face today.
In the longer term, text mining could close the gap completely and give all customers the same buy now experience.