Adaptability

June Edition (looking at May), 2024

Thought for the month:

"We move forward when we find depth, expertise, authenticity, debate.

Averaging out things from the past, from the masses, based on frequency not depth is the one sure fire way to making life revert to the mean, not propel us ahead."?

- Tom Goodwin , Linkedin May 2024

The heirloom and continued tradition of technology in insurance

Yes, I've avoided the word LEGACY or MODERN LEGACY and used nicer words like heirloom and tradition instead.

An heirloom...a piece of property (such as a deed or charter) that descends to the heir as an inseparable part of an inheritance of real property. Or an object handed down from one generation to the next.

The definitions of these technologies vary, but the resultant characteristics are much the same, here's a few examples:

1. 1980s ownership costs, keeping all the IT risk and costs in a box.
2. Compliance requirements are always a complex challenge and constantly seen as an obligation and not an opportunity.
3. Scaling difficulties, especially in keeping up with the ever changing and proliferating distribution channels - when will it end?!
4. Slow time to market from idea or underwriting outcome to reality creating expensive product development costs and often rendering simple innovation unviable.
5. Limited scalability and flexibility, restricting new business model innovation. Relegating ideas like embedding, risk mitigating, adaptive cover and so on to the realms of future fantasy despite clear new value potential today.
6. A deteriorating end-user experience (by expectation), low ability to cross or up sell and generally a less than omni-channel capability. Making dreams of expansive ecosystems and propositions that sell "beyond insurance" frankly a waste to even think about.
7. Increasing cybersecurity risks and business disruptions, putting technology top of the agenda in and of itself.

*Just a few off the top of my head.

The good news is we are all set for change. Hurrah!

According to PWC, on average about 70% of an insurer’s annual IT budget is spent on maintaining its legacy systems.

And these systems are increasingly not fit for purpose. In today’s dynamic insurance landscape, insurers are still struggling to deliver modern experiences, with 41% of CIOs reporting legacy systems as the main barrier to tech success.?

Given this attitude, it’s no wonder that Gartner found that 68% of insurers plan to increase investments in application modernization. This market is set to grow fast.

Wired all wrong

I'd like to focus on the often overlooked cost, which is simply in the consequence of legacy based "technological wiring".

It's adds massive complexity to insurers, making change super hard to even conceive. Turning a simple request to change a customer experience and integrate with a new partner into something that baffles people into thinking it's impossible to achieve.

The systems diagram alone can end up looking like a circuit board, which it often feels like no one truly understands or can properly explain it.

And what happens when you finally go to change something is that you often then realize how interconnected and hard wired everything is.

And this interdependency puts you in a long queue of other things that are changing or planned to change as well, and guess what? This adds further complexity to the solution, it now has to keep pace with all the other changes!

This is exacerbated by the fact that most core technologies in insurance today are policy centric and most of the architecture (both business and technological) are built this way as well.

This means that a. we can't act purely centered around the customer and build all of our data-fluidity and intelligence around this (a customer and all their policy, products and interactions with me and their world I can see in data). And b. that change is manifested once and not made available many times.

This kills all sorts of things. And it creates a huge burden on insurers, an unseen tax of complexity that goes far beyond the simple metrics of CPP's alone. How much time is wasted on just discovering how we can even think about doing something?

Technology updates also clearly remain a challenge across the insurance industry.

An insurance industry trends report from Earnix shows that of the 298 insurance executives surveyed in Australia, the United States and Europe, 90 per cent don’t have full operation modernisation strategies and many depend too heavily on legacy and multiple third-party systems. This results in workflow bottlenecks, inefficiencies, errors and cumbersome workarounds.

An example, 32 per cent of respondents in the Earnix report say that it currently takes 7–12 months to make an underwriting rule change and deploy it into production.

This also came out in a recent study I participated in with 凯捷咨询 (see below), which further highlighted the need to reduce the time between an underwriting decision and getting this into the hands of a customer (among other things).

This has to, and can change, and it will massively help to demystify and democratise change further, freeing innovation and helping us all to get on and deliver new value faster.

D-Day 80

On that historic day in 1944, amid the turmoil, a 21-year-old piper played under a hail of gunfire on Sword Beach as troops disembarked from their landing craft.

This year, our industry colleague Robert Procter (who I met very recently thanks to David Clamp ) has arranged for a 21-year-old piper to play on those same shores in tribute to the fallen. In the evening, in all the capital cities of the Allies, pipers will play at a coordinated time.

And this isn't the first time he has done something like this!

My Grandfather, also a piper, had a DSM and experienced much of WW2's worst moments, in particular he got to see horror on both sides having been a spy, and one of the first to liberate a concentration camp.

Those scenes never left him and took him to an early grave, that's for sure!

My other Grandfather campaigned in the Merchant navy bringing back much needed food form New Zealand and other far flung places, all under constant attack. His own Father (GGF) in WW1 went over on the New Foundland to liberate Russia. Thankfully successfully.

These acts were not heroic in their eyes. D-Day was much the same. Tyrony was met by determination and sheer will. It was a truly horrific moment in history. And the lessons should never leave us.

Perhaps sometimes, even today, we can see echos of the past. Almost as if they have been forgotten.

This simple display brings us back to those lessons. And commemorates the veterans and the fallen. And I was more than happy to chip in. Well done Robert!!

Click here to read more and donate if you can.

AI: Is the future now?

In this Chartered Insurance Institute article in The Journal by @Fiona Nicholson, they take a look at the benefits, risks and future use cases for Generative AI.

A topic that continues to hit the headlines, and one where taking a wider view at an industry level like this is extremely useful. I've been quoted highlighting the importance of human involvement in the technology:

“AI is a double-edged sword – its ability to detect fraud is matched by its ability to commit it. We must keep a human ‘in the loop’ at all times to avoid problems.”

Click here to read more.

Ireland showed us it's aiming to be at the forefront of pioneering insurance futures

The EIS Ltd and InsTech.ie summit hosted by KPMG held Dublin in May was superb.

My thanks to all involved in organising it, and to our Marketing leadership Sara Perez and Bobby Cottrell in particular.

?? Some takeaways ??

1. Transformations are hard, think about evolution or as Lana Briggs called it "continuous change with small bangs along the way".
2. We need to move away from policy centric insurance to customer centric. Building insurers differently requires the "heart and the head" to be joined up (Richard Fisher).
3. Ecosystems are proliferating, think hard about how you can make it as easy as possible to partner and prove value fast. Engaging startups, big techs and insuretechs, putting your insurance business at the centre and orchestrating this value around your customer is critical.
4. Insurance is dead, long live insurance! We heard about some amazing tranformation stories, - ambitions fulfilled. It takes a lot to "stay the course", but it's more than worth it (Rob Stanton Roy Jubraj ).
5. Regulation is a force for good. Use it and don't work against it. DORA is coming, consumer duties and the influx of AI regs etc. Are all trying to act in the best interests of customers. These are opportunities not just obligations.
6. SaaS is trying to takeover the world (Philippe Lafreniere), but focusing on the value it brings, adaptivity and ensuring it's really understood will realise the benefits.
7. "I see customers and employees as equal priorities. Both of their experiences are critical and one often impacts the other..." - Jackie (Jac) Dunne

And many more... ??

Fraudsters are in full ambitious intelligence mode

This is a vital topic. How can we keep up with the fraudsters?

I was lucky enough to write this piece for Insurance-Edge.Net and Alastair Walker on the incredibly important topic of Fraudsters and AI.

See why I say things like:?? "Fraudsters, as I now know to call them, are always looking for weak spots, and unlike our mental image of them, a lot are highly professionalised, organised, and now digitised." ??

And there's a cheeky reference to my mate Matt Gilham, of course, couldn't really talk about fraud without this reference tbh.

Click here to read more.

Why is embedded insurance so popular right now?

Good question, right!?

Information Age and Charles Orton-Jones asked some great questions on this hot topic to René Schoenauer Nelson Castellanos and Caleb Rockstone.

He asked me: Q: How big is embedded insurance going to be?

And I got to unpack the true meaning of embedded and how it's far more than just an interrupted purchase experience.

Click here to read more.

Unpacking the unique opportunities for data professionals in insurance

I got to talk to Andy Davis on the Evolution podcast about:

?? Unpacking the unique opportunities for data professionals in the insurance sector. ??

So I quickly tuned into my inner Lisa Wardlaw, Nigel Walsh, Sabine VanderLinden, Margeaux Giles, Curtis Goldsborough and Ema Roloff! And yes I realised early on that this is a benchmark too far! ??

I did however have a marvelous time with Andy and we covered a lot of ground:

?? Why insurance is a great place to work right now

? Data at the heart of insurance business models and adaptive futures

?? Rich diversity and why it's a superpower

? The often polarising impact of London on the UK market

?? And why we have a data talent problem and correspondingly a massive opportunity

I've said this probably way too much and for far too long - the future defining competitive characteristic for success in insurance is adaptivitiy.

The higher your organisations AQ the more success you'll have. Data is one of the most critical and foundational elements of this.

And when combined with a business model built around the customer, a fusion between data to outcome and an ever proliferating and enriching ecosystem - you'll have the first dominant ecosystem driver and modular producer models in the market. Increased knowledge of the customer and an increased ability to act on that knowledge.

Click here to listen.

Where next for insurance ecosystems?

How can you be customer-centric if your business is designed to put the policy and not the customer at the center? You can't. ??

Insurance Thought Leadership gave me an opportunity to unpack this topic extensively, and I am very grateful for the opportunities they provide to dig in a bit deeper. ??

Lisa Wardlaw and I have talked a lot about this on and off of her amazing podcast series, whenever we think of what it will really take to unchain insurance from its "industrialization" era we always come around to this bigger need for fundamental change. ??

And equally I've often covered this with the likes of Oliver McGuinness, Margeaux Giles IRYS Insurtech when I met her recently in London, Nigel Walsh when I met him in Google Cloud a couple of months back and so on.

And I have some pretty strong views on the changes we are seeing and need to see, but make no mistake this is an enterprise design change most still struggle with. Obviously this includes me when trying to conceive it across every business process and function at once. Insurance is necessarily complex.

As Yanna Winter once said to me in a round table - you eat this elephant one mouthful at a time. This doesn't mean one-off "innovation" as a working model approach to transformation, lots of sticky plasters won't solve it, it means with the right foundations and clear vision and then you can evolve your ecosystem and business model in tandem.

Click here to read more.

Underwriting trailblazers

What a lovely thing to receive over a breakfast from the Capgemini crew.

Thank you Luca Russignan Cyril Francois and Elias Ghanem, much appreciated.

And if you're interested in becoming an underwriting trailblazer, and you need to chart your transformation across a shifting risk landscape fear not you can get a copy here: https://lnkd.in/e-pbAskV

Feels like Human Intelligence (HI) is back in vogue!

GenAI has so far mostly proved utter pants at generating meaningful content and good at mimicking the average (or just producing gunk). This will change.

Whereas, for example, fulfilling research with a human in the loop it seems to add a good amount of value to certain tasks already. This will improve further.

In terms of determining what it is and isn't good for at the moment though - you can't really conclude this stuff easily.

Maths and neurons at this stage are as good and bad at stuff as we engineer them to be. So the answer is always - it depends!

You need to invest time and effort into understanding it more, continuing to focus on where you can create customer value, and then building on solid reliable data and operational foundations.

Making sure there's always a human in the loop and a human in control.

Take the basic content generation of GenAI, which we are already seeing in social media and old media like email.

Even before GenAI was popularized and systematized in the way it is now, a lot of communication and linguistic output was all largely templated, generic average waffle anyway!! The real problem is when that is the training data of the LLM. It just scales the problem and distributes rubbish even wider and faster. So we have always got to think data first.

This just commoditizes widely available open AI quickly, and premiumises humans and fusing them with machines.

As I say often, if everything is averaged and machine driven your competitive advantage often becomes pretty straight forward.

?? HI x (AI + Responsibility) = greater value potential ??