In brief
- Automation can help insurance companies reduce the time and effort required to purchase insurance, making it less of a "distress purchase" for customers.
- Chatbots and other automated tools can provide personalized support to customers, helping them understand their options and choose the best coverage.
- By using automation to collect and analyze data, insurers can also offer more personalized insurance products and pricing, as well as deliver faster and more accurate claims processing and customer service.
We’re living through the rarest of things; a period of rapid change in the industry with a glacial
history.
Advances in technology, AI and machine learning have made it possible to set about
modernizing outdated traditional insurance practices. A fresh approach like digital transformation
and automation broadens our terms of reference for what an insurance product can look and sell
like.
Revolutionary thinking such as bringing in automation for things like simple or common
products, or claims, can deliver profit and a positive customer experience.
Immediate settlement
Take non-traditional parametric insurance, for instance. Parametric insurance makes a pre-determined
payment for the occurrence of an agreed business or environmental trigger event like Caribbean
Catastrophe Risk Insurance Facility (CCRIF
SPC), the African Risk Capacity (ARC), or
natural agricultural hazards in developing countries. In these instances (depending on the
parametric policy) a trigger event such as abnormally excessive wind speed, rainfall or drought
generates an agreed and automated payment almost immediately.
Without this kind of
automation, the payout depends on the ability of the insured party to provide data-based evidence of
their misfortune — a long, drawn out and far from certain process. With an automated product, it’s
the other way around. The insurer accesses the appropriate data set, determines the claim and pays
out.
Getting used to innovation
Like with Lemonade Insurance in
the United States — an organization built high on automation. Built on transparency, a near-enough
immediate claims process and lower rates than the competition, Lemonade donates unused premiums to
charity each year and delivers an all-round great customer experience.
One thing which might
seem obvious but needs flagging-up straight away is that the technology insurers have in place,
currently, must be capable of adapting to innovation. A lot of new products being brought to market
don't necessarily fit a standard insurance platform.
We need to think about product
development cycles; how do we get products to market, quickly? And where we have new propositions
and products, how do we develop them on a proof-of-concept basis? How do we test them and get them
to customers, knowing that we might have to dump products that don't catch on and industrialize
those that do? “Develop fast, drop fast” — that’s our approach to building a diverse product
suite.
Help! The robots are coming
It’s easy to forget that, once they log off for the day, prominent risk managers become customers
again. They have the same expectations and anxieties as their fellow policy holders, and recognize
the need for human interaction in certain complex cases. Technology-wise, the important point is to
automate just the aspects that improve the customer service. It will also help to calm workforce
employment fears of what will happen “when the machines take over”.
The terms AI and
machine learning are often interchangeable. Machine learning is basically learning from a human who
intervenes in a process that the machine doesn't understand. While the machines are understanding
the process through determining a claim or the choice of a product, human intervention helps keep
the machine on track. As the technology develops, machine learning is going to have a massive
influence on the industry.
Horses for courses
More and more tasks will be completed by machines rather than by humans. But that doesn't alter the
fact that there are certain circumstances and classes of customer that warrant human intervention.
Handling injury claims, for example. No one wants to be told by an unfeeling machine that “we're
not paying your claim because…”. We want empathy and understanding, and that means speaking
to a human being.
It's about getting the right balance between automating tasks that provide
better service, reduce cost and deliver a better customer experience, and retaining staff for the
tasks that people are best at dealing with.
The future workforce
Career-wise, one of the reasons I moved more into analytics was that insurance is analytics. Even if
all we had were paper rate cards, somebody would still have to perform some analytics there. The
truth is, claims departments are going to start recruiting more and more data analysts. Rating and
pricing departments are going to recruit more data analysts. Fraud is going to be led by data
scientists (not by fraud investigators necessarily).
Therefore, anyone about to make
insurance their career ought to concentrate on coming to terms with data, because that’s the future.
For sure.
Is it realistic to automate the entire process?
So, we need to home in on the areas that AI and other technologies are not so good at, like customer
care. Here’s a personal and practical example from the UK floods of 2007.
A claims manager
said to me, “It's really interesting. We've got customers who were flooded out and have come to
the end of their alternative accommodation. Alternative accommodation only lasts for 12 months
and we haven't managed to dry out the properties yet, so they're kind of left
hanging.”
My reply was, “Well, why didn't you just write the house off? If a car
is beyond economic repair you write it off. Why encourage a customer to move back into a house
that's uninhabitable?” We need to look at the claims process in a new light, and come up
with better ways to handle those sorts of claims.
Give great customer service
In that circumstance, what if the automatic tool said, “Actually, we’ve worked out that it’s
going to take more than 12 months to dry out your house and reinstate you”? And then the
insurer gave them a total loss settlement, paid the value of the house on day one and let them get
on with the rest of their lives? How much better would that be for all concerned?
Insurers
need to focus on giving customers an excellent, personalized, digital experience. We have enough
information about segmentation to be able to personalize our offering to them. We just need to make
sure we can deliver on that.
Cross-industry application
Adaptix Solutions is an analytics and engineering business. It's very big in banking and capital
markets
(BCM).
Fortunately, we discovered a lot of the things we do in BCM, particularly in the analytics space,
are directly transferable to the insurance sector. I joined the company to help build out that
insurance practice, taking our BCM tools and showing insurers how we can deploy them in the
insurance industry with great success.
If you’d like to find out just how much of a positive
difference Adaptix Solutions could make to your organization, visit Adaptix.com/insurance or
contact financial
services and we’ll
chat through some of the remarkable solutions we have for the insurance industry in general, and for
you in particular.
Jeremy Owenson
During his 12 years with Zurich Insurance, Jeremy gained extensive market knowledge, from sales and the underwriting process to claims and even outsourcing (including offshore). Now, he’s concentrating on how technology can revolutionize the industry. Leveraging DXC Adaptix Solutions’s leading position in Banking and Capital Markets, Jeremy is determined to bring fresh ideas and ML-driven underwriting to the insurance sector.
