HomeGame 6

You got everything you normally get from a lang cat event, but this time it was in Leith – our actual home. It was mostly Scottish.

/ The Summary

HomeGame 6 wasnโ€™t just another HomeGame. It was a homecoming for the lang cat. We brought our annual event to just a few hundred metres from The Lang Cat Port Authority (thatโ€™s our head office) and we wanted to invite you to join us for an event quite unlike any other.ย 

HomeGame 6 landed at a time when the financial advice market had lots of new things to think about. For decades now, the profession has had a trump card โ€“ โ€œyeah but if you want actual financial advice then this is the only place you can get it.โ€

Thatโ€™s not true any more โ€“ or is it? We already knew that general AI tools were widely used by clients not only to find out what to do with their money, but even to check recommendations or provide guidance on what to do when you meet an adviser. Alongside this, the D2C market was exploding; growth of the two channels used to be like tramlines but now the direct market is sprinting ahead.

All in all it was a good time to work out whatโ€™s what out there. And thatโ€™s what we did.

We knew that AI was giving advice, or what consumers perceived to be advice. What we didnโ€™t know was how consistent that advice was, or how good it was.

Hereโ€™s how it worked.

The storied, dilapidated, regenerating and peerless Leith Theatre was our communal AI lab for the day and hosted an event unlike anything financial services had seen before. The audience weren’t sitting and listening. They worked in teams, made decisions, prompted AI tools and โ€“ possibly โ€“ disagreed loudly with each other whilst having a thoroughly enjoyable time.

Before that the day opened the way a lang cat event always opens: with research, honesty, doomed attempts at entertainment, and the scene set for the sessions to come.

Then we did something really risky.

Every table became a client: the same client. Every client had an AI terminal already hooked up to one of the big generative models that clients typically use. They received a client brief, written the way a real person writes about their own financial life: incomplete, slightly emotional, and missing the things they don’t know they don’t know. We asked the audience to don a veil of ignorance and pretend to be a client โ€“ no cheeky prompts saying โ€œare you sure my portfolio will be optimised according to Markowitzโ€™s efficient frontier theory?โ€ or anything like that. Each table had a Highheidyin[1] to make sure everything runs smoothly.

At the end, they asked their AI to summarise what it told them and to recommend next actions. We gathered that all together using witchcraft and Ancient Wisdom and gave the audience an initial playback before fuller details are published in the future.

Throughout, a small crack team of roving camerapeople and hosts er, ‘roved’ and found out how everyone was getting on.

While all this was going on, a small team of financial planners went through the same exercise also enabled with AI, but rather than a general system they used a leading adviser-focused AI tool. They didn’t agree on everything, but they needed to come up with a consensus view. That gave us a benchmark against which we measured the outputs from the tables.

At the end, we had 35 or so exercises which were all based off exactly the same data, produced at exactly the same time. The only difference were the prompts each table/client chose.

From that we learned a lot. We saw if the โ€œadviceโ€ was actually advice or not.

This took up most of our day, but we did have a bit of time spare to talk about wider industry issues, heard from planners doing interesting things, thought about the regulatory response to all of this and how to navigate that, and more.

No-one has tried anything like this before in our sector; possibly anywhere. It was quite a ride. And it all happened in our home โ€“ Leith. We donโ€™t ask you into our house unless weโ€™ve got something very special prepared.ย [1] A boss, in Scots, literally โ€œhigh head oneโ€.

 

THE PRACTICALITIES

The date to mark in your calendars was Wednesday 7 October.

Thanks to the generosity of our sponsors, tickets were free for advice professionals working at an advice firm; so advisers, planners, paraplanners, compliance and admin fill your boots (if you work for a huge provider with an advice offshoot you only qualify if youโ€™re in an advice-giving or paraplanning role).

Everyone else was asked to buy tickets at a cost of ยฃ100 plus VAT.

 

CPD

This event provided 5 hours of structured CPD. Certificates will be sent out to attendees in the weeks following the event.

/ Book Now

HomeGame 6

Leith Theatre

October 7, 2026

/ Schedule

10.30
Doors open
11am
Welcome
11:10
How this is going to work
11.50
AI Lab: Round 1
12:20
AI Lab: Round 2
12.45
Leith Theatre: Why we’re here
12.50
LUNCH
13.50
AI Lab: Round 3
14.20
Panel: Making AI Sweat
14.50
Alyn Smith MSP, Minister for Innovation and Technologyย 
15.15
BREAK
15.45
Keynote: Hollie Davidson
16.25
Playback / Close
17.00
Drinks and nibbles

/ Anchor sponsor

/ Also sponsored by

/ Charity partner

Sponsor

/ Event videos

Impact of poor service

/ White papers

The Impact of Poor Service

We provided the research for a report, in conjunction with Parmenion, which reveals how far short of expectations many adviser platforms are falling. The research found that over the last 12 months, 88% of advisers needed to apologise to at least one of their clients on behalf of a platform, and that poor service delivery from platforms impacts 91% of advisers every day.

Impact of poor service

/ White papers

The Impact of Poor Platform Service

We provided the research for a report, in conjunction with Parmenion, which reveals how far short of expectations many adviser platforms are falling. The research found that over the last 12 months, 88% of advisers needed to apologise to at least one of their clients on behalf of a platform, and that poor service delivery from platforms impacts 91% of advisers every day.

/ White papers

Answering the Call

Service means a lot of things to a lot of different people. Itโ€™s so subjective it can be hard to put your finger on. This paper aims to challenge the status quo and inertia thatโ€™s built up in the sector for many years.