The terms and conditions wormhole
The latest episode of the Netflix Black Mirror series, Joan-is-Awful, hits a Terms & Conditions box ticking raw nerve when Joan finds herself hamstrung by the small print she thoughtlessly agreed to. Just hours after the show aired, Google searches peaked with people nervously wanting to know more about Netflix’s T&C’s.
It’s not just Netflix customers who are anxious about whether they understand T&C’s - the FCA is keen that – at least for financial services – consumers know what they’re agreeing to. The forthcoming Consumer Duty Act impacts how insurance customers view their T&C’s – they must be clear, customers must know what they are signed up for - and additionally the product has to fit their needs.
Most of us are like Joan: policy terms & conditions can be in the ‘too-hard’ bucket. But like Joan (who starts the film as a Tech Executive), we’re not all blessed with a legal education. The challenge the FCA is laying at the door of insurers is to be more inclusive and consider for example those who struggle with complex vocabulary or face a different challenge such as lack of fluency in the language of the policy.
Enter a good news story about Generative AI, which is able to play a role in making sure customers have a clear understanding of what they’ve actually purchased. The Key Facts section of a policy is a good place to start. We can generate a tailored Key Facts in a language the customer will recognise and understand what the policy terms mean to them. The Key Facts can be personalised every time, for every customer - without compromising the core policy conditions and terms.
A good example where this can be applied is travel insurance - a policy conditions minefield. If you’re worried about what happens if your medical condition flares up on holiday, the Key Facts can precisely call out our level of cover and how you gain access. Alternatively, if white river rafting is your thing, the Key Facts could call what you’re covered for and compliment it with an easy link to upgrade your coverage for another activity. Same policy, different priorities, for potentially very different customers with different levels of understanding – both serviced by very different intelligently personalised Key Facts.
Key Facts is not the only area where generative AI can help - together with other technology available today – it can take a conversation or webchat, extract learning from it and match it to the policy to create personalised output. The output can be used as a prompt for a Contact Centre Agent to ensure both compliance and customer understanding during the sales process.
Art imitates life with quantum computing
While the Ts&Cs setup Joan’s predicament in the Black Mirror episode, a sinister quantum computer twists the knife on her world every day. Its owner (the CEO of the fictitious corporation Streamberry) says, “We're still not sure how it works, it's a bit like magic”. This is not a bad summary of what Quantum means to most people.
But what does Black Mirror get right and wrong about Quantum? And does it do a good job showing the art of the possible? We should know, NTT DATA has one.
They got this one right: Yes, you don’t really need to understand how Quantum works but it’ll transform many industries and insurance will be one of the first.
Because of its ability to problem solve in parallel, quantum has the potential to far exceed the transformational impact of Large Language Model platforms such as ChatGPT. In fact, while the need to regulate AI is still being debated, the power of Quantum was quickly realised and controls have been in place for 5 years.
They got this one right, too: Yes, Quantum is superb at solving complex optimisation challenges at mind boggling scale and speed, ideally within a constantly changing environment.
Quantum’s already proved how it can quickly build very personalised journey experiences – most likely the inspiration for Joan-is-Awful. It also provides a good hint as to how insurers could in future provide personalised policies and experiences that represent a benefit for the insurer and the insured.
Moreover, having already proved itself in supply chain optimisation, Quantum has the potential to reduce claim inflation for motor Insurers feeling the pain of increasing cost of replacement car parts.
The underlying cause is limited supply and consequently the burgeoning cost of customers holding onto rental cars for much longer. With the benefit of a Quantum computer, at any given moment, an insurer can identify the optimum they can achieve with the parts and time they do have available to them.
And if the situation changes - a part doesn’t arrive when scheduled - Quantum will identify the next best optimum – for example, parts could be shipped elsewhere to close another claim. The sheer number of variables to consider makes true optimisation of these kinds of problems impossible using conventional tech.
They actually got this one right, sorry: Quantum is available now and we’re running pilots for a surprising number of customers.
They got this one wrong, though: Unfortunately, a quantum computer actually looks like an unassuming plastic box and no-one we know has an axe in a cupboard near it (you’ll have to watch the episode).
It’s just another type of computer that just happens to be really good at solving particular types of mathematical problems that insurers like to solve.
Unlike Joan, insurers are not net yet backed into a corner. Now is an ideal time for the sector to get on the front foot with how to fulfil the principles of Consumer Duty using large language model technology. At the same time, Quantum can cut costs and drive far more accurate risk premiums through a level of optimisation we could only dream of five years ago.
NTT DATA can help ensure there’s a happy ending to the story – please get in touch with us if you want to write your own script.