Financial Planner Life Podcast

From ChatGPT to Chat SJP: The AI Revolution at St. James’s Place | John O'Driscoll & Wenyu Bai (SJP)

Sam Oakes

In this episode, Sam Oakes is joined by John O’Driscoll and Wenyu Bai from St. James’s Place to explore how AI and technology are being developed to support the future of financial planning.

Discover how SJP’s 2030 vision is being built around:

  • Advice Assistant: An AI-enabled tool already in production that reduces the time to produce advice packs from hours to minutes
  • Chat SJP: An internal GPT-style assistant that delivers fast, accurate, compliant answers to technical questions
  • Agentic AI: The concept of digital support agents acting as a virtual back office
  • The Innovation Sandbox: A safe space for financial planners to test and build new tools
  • A strategic focus on simplifying, streamlining and elevating the planner and client experience

This isn’t about replacing financial planners. It’s about giving them better tools, more time, and the freedom to focus on what they do best - building meaningful relationships with clients.

Whether you’re considering your future as a planner, leading a firm, or just want to understand where the profession is headed, this episode is for you.

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Speaker 1:

It's not that AI is going to replace advisors. It's that AI advisors, using AI, are going to outcompete the advisors who don't.

Speaker 2:

It used to take two to three hours to do that. Now it comes down to less than half an hour 15 minutes.

Speaker 3:

If you're not keeping up with modern day technology in the way that clients want to work with a financial planner, you're going to get left behind. What?

Speaker 2:

we also want to do in the next talk about 2030 is create an environmental sandbox or playground for partners to be able to play around with some of these things. And finally, the big one which everyone's talking about this year is agentic AI.

Speaker 1:

I was with a bunch of IFAs a few weeks ago and they kind of they were spending a lot of time thinking about AI but not knowing what questions to ask of providers to make sure they've done their due diligence, and they're not really knowing how to interpret those answers.

Speaker 3:

So, john, bye. Thanks so much for joining me today on the Financial Planner Live podcast. Today is a big topic. We're talking about technology and artificial intelligence. Really odd, because this week I've been approached by so many people either working in AI or financial advisors that are saying I think you should get more people on your podcast talking about tech and AI. So good timing. I was looking forward to hearing about tech and AI within the ecosystem of St James's Place, so perhaps you can both just introduce yourself first of all to our audience so they know who you are and what you do, and then we can crack on with the podcast today and get everyone educated.

Speaker 1:

So, john, yeah, so I'm John O'Driscoll. My job title is Divisional Director Business Development and Advice at SJP, but essentially I'm Director for Advice Tech.

Speaker 2:

That's kind of my job. So I'm Bai, I work for Zhuang, I'm the head of AI and machine learning at SJP.

Speaker 3:

Fantastic. Let's start with advice tech. Then you just said head of advice tech. Let's get simple here. Right? Tell us a little bit about advice tech and what's going on in the world of advice tech right now yeah.

Speaker 1:

so I guess, um, we're as a, as an industry, I think we've, um, everything used to be paper and then we've been through a process of basically digitizing paper and now we're into a, an era of actually thinking a bit more transformationally about how can we simplify the advice process, which isn't actually necessarily delivery of the advice by an advisor, it's actually all the back office type stuff.

Speaker 1:

So I think everyone's kind of looking at the CRM system and how they kind of curate their information about the client, but also, given the FCA scrutiny around ongoing advice and things, how they record the advice that's being delivered and all those kind of things, and, given that you've got platforms out there then that deal with that, and are trying to integrate financial planning software, like cash flow, attitude to risk stuff, suitability, letter writing, all those kind of things into one platform to avoid this kind of swivel chairing and re-keying.

Speaker 1:

And I guess that's where we are too. So you know, we've kind of gone on a journey with Salesforce as our CRM and our kind of chassis, if you like, for the advice process and then trying to bring everything much closer together with that to make the process of advice much more efficient so that advisors can spend more time with clients and doing what they do best without kind of I guess, what has been in the past almost kind of filling out forms to satisfy different departments of an advice firm, whether it's your money laundering or your compliance or your business submission. Actually, can we just kind of get rid of that and use technology to deal with that and let the advisor get on with the client?

Speaker 2:

fantastic yeah, I guess just want to also consider a little bit about ai. So at least at sjp, when we talk about talk about ai, it's not just generative ai, it's not just check gbt, it's the whole kind of the broad definition of ai. So you can even start from say data analysis, that's part of what we do. Sometimes the problem they're trying to ask is oh, I'm a financial advisor, how many clients I've got, how many clients in the different stages? That's data analysis. That's not really using general AI. And then you've got automation side of things. So robotic process automation, that's again part of AI, I see it. And then move on to traditional machine learning and then finally, is this generative AI bit. So I see this whole AI solution as covering all of that rather than just the final bit. So that's probably the first thing to say.

Speaker 2:

And in terms of seeing the industry and how AI applies to financial devices, I think on the positive side, people are really interested about it and there's lots of great ideas and we do see some applications kind of coming in the market and people started to using it. But in terms of actual things in production, I think it's at moments relatively kind of small steps rather than big transformation, and we'll talk about what we did at SJP, which I think are truly transformational. But it's not that easy to get. It's not just you go out and buy a tool and it becomes, you know, to solve all your problems. It's very much, you need to understand it, you need to work through it, make it work for your company. So that's kind of not on the negative side. But looking at the industry, I think there's still a long way to go to get into that stage where actually you solve all your problems.

Speaker 1:

I think that's why I talk about kind of advice tech rather than FinTech, because you need to have that it's combining what the financial advisor is trying to do with the tech. You can go and get a tool that does something but advisor's trying to do with the tech.

Speaker 3:

It's kind of it's not. You can go and get a tool that does something, but actually how do you integrate that with an advice process? Um, a bit like the old shiny object syndrome, isn't it? It's so new ai that everybody's got this solution, so they're packaging it out, they're putting it out there, selling that the product or service to an advisor, without actually the advisor really understanding how to implement that into the actual process. It's like we're going to solve your problems that you've got use ai, download this new application and it's going to save you this much time.

Speaker 3:

But in reality there's more to it than just buying a product or a service. It's the implementation of it and how does it fit in the overall process. And that analysis of the overall process is time consuming, right? Yes, it's hard graft. It costs a lot of money. If you're going to look at speeding up the whole process, you can't just put, like, a really fast engine in a car that has really terrible chassis or tires or something like that, right, it doesn't work. You need to look at the whole thing. So transformational changes that you've made at st james's place, having your you know, your eyes firmly in AI and technology. What are the biggest transformational changes that you're making and what are the biggest opportunities right now with tech and AI that really financial planners as a whole really should be thinking about?

Speaker 2:

Yeah, yeah. So I think the one that really in SAP we have in productionized and a lot of partners have already used is called Advice Assistant. So this is a kind of advice, recommendation plus business submission tool that all of our partners can use. That saves time about use. That saves time about what used to take two to three hours to do, that now come down to less than half an hour, 15 minutes. And that tool is using a combination of kind of rules-based or kind of automation, if you like, plus some of the kind of using natural language processing models. So that's kind of touching a bit more about the latest AI technology. But, as I said earlier, that combination really drives the outcome we're looking for and partners really benefiting from.

Speaker 1:

I think kind of importantly on that, it's a lot of what we see out there in industry is, as you kind of touched on, it's, it's a, it's this kind of a specific, it's an. I've got this ai thing that you can download to fix this problem. But we've tried to do is look uh, okay, how do we simplify the whole process? So, um, so, vice assistant, for example, you do your fact find, um, and basically, once you've done your fact find, in as few as 10 clicks you can get through the uh creation of the you know, a suitable set of advice that's likely to meet sjp standards. You can uh deal with the illustrations, the documents you need. We create the kind of advice set, as we call it, on our systems and you're kind of ready to go to submit the business. So it's an end-to-end kind of solution rather than just trying to fix one point in the solution one point in time.

Speaker 1:

And we've started now to get into the LLM space, into the kind of chat GPT. So we've got a solution in pilot that we're calling SJP GPT, which is kind of chat GPTs. We've got a, a, a solution in pilot that we're calling sjpgpt, which is kind of that chat GPT type interface, but trying to kind of help advisors navigate um our content around the advice, our advice framework, our business submission guides and things, just trying to make it easier to find information but ultimately in time. Where we want to get to is you know, we know what you're trying to do, we can nudge you in the right direction and you don't even need to go and swivel chair and to ask questions of a system because it's guiding you through the process. So that's the journey we're on. But you know, we started with Advice Assistant and that's been yeah, that's been live in production for a couple years now almost so that's advice, assistant.

Speaker 3:

So at what point does that become available for somebody that wants to join St James's Place? How quickly can they take advantage of that? Is it implemented within the academy, for instance? Do they start learning about it there and it's part of their actual learning journey and shaping the structure of their business and their career in the early stages. Is it something you tap into? Once you're a partner within st james's place, you know when can they use it and how quickly they take advantage of the expertise and the knowledge you're building around that yeah, so it's available to all partners.

Speaker 1:

Um, and yeah, free of charge. Uh, so, um, so it's kind of a core part of our proposition In the academy to that particular question. There's an interesting conversation with the academy guys about it because they were like, surely an advisor needs to learn how to do this before they then take on the tool that automates out and having to do it. But we've kind of navigated that so they learn about it, but they also learn the craft so that they understand what's going on behind the scenes, because ultimately the advisor still needs to take responsibility for the advice that's generated. Um, so they need to understand is this you know they will generate a suggestion, but actually the advisor knows the client better than we do and you know we only see the fact find in the data. We don't necessarily see the you know the whites of the eyes of the client. So, um, so it's kind of there's still some craft there. But, yeah, advisors can take advantage of it as soon as they start writing business simplify it for me.

Speaker 3:

Paint a picture. Okay, so I'm a financial planner and I'm interested in joining st james's place. There's multiple different things that sjp sjp can do to support me, to help me grow my partner practice right. Ai and tech isn't something that is really talked about, as I think as detailed and as often as it actually should be. Talk me through in simplistic terms exactly how AI and tech is going to help me as a financial planner in my career at St James's Place. Do you want to go first, or should I?

Speaker 2:

Yeah, I can. Yeah, so because, yeah, we have a wide range of tools for partners to use. But I guess, yeah, from when partners first joined SAP. It depends on which route. If they come from academy, as John was saying, there are a lot of trainings talking about what SAP ecosystem look like, what they can use that for, and then, yeah, when they actually become a partner, that we have, first of all, those tools are already available. They can see it from Salesforce, which again we touched on earlier, which that's their lending page almost to manage all of their clients' information, and they can see advisory system right there. Click a button, they get into it. This chat SJP thing we talked about on the chat agent thing will be on our intranet, so, again, very easy to access to it, and we have the entire SJP head office there to support. We have our tech support hub. We show all of the different techs we have in there, yes, all sorts of supporting materials there as well.

Speaker 3:

So this assistant. Then it becomes the assistant to the financial planner, to the partner assistant. Then it becomes the assistant to the financial planner, to the partner, so they can ask a question and it will give them an answer to, um, like a frequently asked question that a client might have, or an issue or a problem around the process of actually getting the advice or investment strategy. Describe it to me. So if I'm sitting here and I'm, I want to understand how it's actually going to benefit me and how ai actually does that in st james's place. How is? How is it so at?

Speaker 1:

the moment. So I mean the SGP GPT thing. At the moment, if you Chat SGP, chat SGP sorry, chat SGP, chat SGP, sorry, we kind of Sorry, my bad we. Yeah, so I don't know. So what do I need to consider when I'm doing decumulation planning and we'll bring back an answer. That kind of avoids you having to navigate our advice framework and it will kind of give you that. It will reference where the source is, but it's kind of just trying to summarize that so you can give you, I guess, give you a grounding on what you need to know. So that's where the chat SJP bit fits in. But then I guess, what is Tech and AI going to do for me as an advisor more generally? Well, the kind of the play is really to give you time back.

Speaker 1:

So obviously we're a heavily regulated industry. There are things that need to be done around the advice process. Clearly, the most important thing is that the client's assured, has had the right advice and has got the right outcome. There's a lot of kind of there's a lot of stuff that surrounds that process and what we're trying to do is kind of streamline the stuff, uh, whether it's documenting the advice, writing it up, keeping the data up to date. Um, all those things need to be done, but it's not necessarily where the massive value comes for both the client or the advisor. That's the client advisor relationship. So, um, we're trying to kind of get the process out of the way, to clear the way for better relationships and more more into client kind of interaction and also on the advice system.

Speaker 2:

I think the best part is sap when we're developing it. It's not just ai team doing it, we're working very closely with our advice policy team, with our business, which is a kind of a quality checking of all the advice team. We work with products, tax and investment, all the expertise around within SJP on this product. So it is kind of best practice by design really. And when you think about when new regulations coming out, when new budget announcement comes out, all of that is already incorporated in this. So when the first instance of those things like consumer duty comes out, right then it's already built into the system. So no one needs to worry about. Oh, what does it mean to me using that?

Speaker 1:

Yeah, a lot of it is kind of us worrying about this stuff so that advisors don't have to. So, yeah, exactly like updating for, yeah, reg change or tax tax change and things, and we kind of do by kind of talked about a number of people, we who are around device system, we're also quite well. We're also very close to advisors and power planners as well in kind of the design as well, trying to understand what are their priorities, what, what kind of what jobs are they doing that we can kind of streamline. So yeah, it's definitely a kind of it's a full ecosystem kind of thing. And then, yeah, well, I guess, as we kind of go kind of, as we look at this stuff as well, it's kind of we're obviously kind of we're worrying about, we kind of you know, we've made best friends with our data protection officer, for instance so we're worrying about all the kind of back end, the kind of the second line, third line, risk side of it as well. So, again, advisors don't have to.

Speaker 3:

You said you use Salesforce. Yeah, yeah, okay, so you're implementing AI into Salesforce, automation into Salesforce, homegrown technology, homegrown AI initiatives into sales force we at the moment.

Speaker 1:

Most of what we're doing is taking date, taking the data that is in the chassis, if you like, of sales force and exploiting that outside of sales force. Um, obviously, sales force got a big kind of play at the moment around agent force, um and there and how that we can use agents to do jobs within salesforce. We are looking at that. We haven't implemented any of that yet and there's obviously a lot in there. There's yeah, there's a lot of opportunity there within salesforce. We're not implemented within salesforce yet. There's a lot of automation within salesforce and flows and things that kind of you know. So I don't know, when I do my ongoing advice meetings, I create the meeting, we'll automatically attach a snapshot of the fact find. We'll prompt the suitability letters. We'll kind of there's some automation in there, but not AI at the moment, have you?

Speaker 3:

got goals to work towards in respect of time the time it takes for a client to be on boarded, the time it takes for a client uh to you know, for an advisor to deliver advice or chasing documentation, etc. Are you working towards time scales of improving that and decreasing the time wasted where potentially opportunities for client advice could fall through the cracks because of the time it takes? Are you sort of driven by reducing that time?

Speaker 1:

yeah, time, I mean time, time saved has been a key, has been a key metric for a while for us across automation generally at sjp, um, both kind of advisor time and head office time for that matter, um, so that's kind of a key currency. I think the strategically the kind of key point we're measuring is kind of advisor satisfaction and client satisfaction, but by saving time that will drive those things as part of the drivers for those two metrics.

Speaker 2:

I guess the other side is the quality of advice. So, we do track that side of it as well and we actually from advice assistant. We can have that comparison between cases running through advice assistant. What's the quality of that advice versus cases that are not? So it's very directly seeing the benefits of using advice assistant and similar tools.

Speaker 3:

Are you seeing a kind of need or a requirement for an app based system? Is that on the? Is that on the cards from a? What client app? Yeah, client and advisor app are you working on that? Is that's part of the overall strategy or?

Speaker 1:

not. Yeah. So I guess client tap is one of the big things we've been doing over the last couple of years. Um, we've got I think around 140 000 clients signed up now to our new app, um, which will have it's kind of currently it's got your valuations, it can show you, shows your performance over time. There's a bit of document kind of your admin documents are kind of stored in there. We're going to be, we'll be implementing the ability to, you know, secure a message with your advisor and those kinds of things.

Speaker 1:

I guess all the things that clients might expect of a kind of fully fledged client app, where maybe we have not, we've not done that in the past and I guess what we found kind of client expectations outside of financial advice are driving client expectations of their advisor, if you like. So that kind of uh, it's easy to say, it's easy to say, with that kind of amazon-esque experience, I want to. I just want to update my address. Um. Clients maybe used to kind of give that to the advisor and the advisor go and sort it out the admin center. Now they're just want to update my address. Clients maybe used to kind of give that to the advisor and the advisor again sort out the admin center. Now they're just expecting to be able to tell us what the change of addresses and should slow through. So it's kind of we want to give clients those touch points. The advisor still remains central to it. But, yeah, the client apps, a big kind of thing we're focused on.

Speaker 1:

On the partner side. We kind of we talk around. We talk around two kind of key systems. We talk around Salesforce as our system of engagement and Blue Door as a system of records. So Blue Door is our back office platform. Salesforce is where advisors and their teams kind of spend a lot of their day.

Speaker 1:

Technologically, if you like, I don't think there's that many partners who, using sales, sat punching sales also. They talk to a client, that's, but it's them. But that's kind of where we see the center of this kind of ecosystem we're trying to build and, yeah, exploiting that data that we can know about, client integrating data that we kind of capture from conversations. So we've we've implemented. For example, we got Zoom AI companions who have partners having a conversation with the client online. Then Zoom can take the conversation, summarize it or transcribe it, summarize it. Actually, what we'd really like to get to is taking the bits of that conversation and be able to update Salesforce. So bring that information back in. Similarly, kind of your clients sharing documents, be able to extract information from those documents and update Salesforce so that we've got that full picture of the client within Salesforce and we can reuse that. Then down the advice process so we can automatically bring that information into suitability letters or into the recommendations that advice assistant's producing or just trying to join all that up.

Speaker 3:

I had somebody on the podcast a little while back. I to join all that up. I, um, I had somebody on the podcast a little while back. I forgot his name. Now they're talking about generative ai gen ai and I hadn't really a clue of what gen ai was, but we got talking about it and what I. What really stood out for me was the ability for a document to talk back to me. So if I receive a policy document and I say it's 30 pages long, right, I can actually ask a question on the document and the document can talk back to me and it starts to explain things to me. So instead of me having to phone up my advisor or phone up wherever sent me it, I can actually physically ask the document the question and it will answer that question, highlight something on it and it would explain it to me as to why it does it, which I thought was really, really impressive. Is that the sort of thing you're working towards now? Is that here, or is that something you're working towards?

Speaker 2:

yeah, that's the kind of thing the chat sjp is trying to do. So at the moment what we're doing is only partner facing. So they can ask questions like exactly as you described. So they have a question about um advice framework. So, for example, when advising yes vct, that kind of not everyone do that every day, so they probably need to try to remember all what kind of risk attitude to risk I need to as a minimum requirement to be able to advise this kind of Investment. So you can just quickly ask I what, what's the ATR requirements for yes VCT? Then April backs down so from advice framework to say for this you need this. And also there here are the others Considerations you think about.

Speaker 2:

And here's the source of the original document. You can click on it and see where they come from. So that's you know. When we talk about gen ai, the first thing people think about is hallucination. That's a huge risk and that still happens in chai gpt today. So everyone needs to be mindful of it. But the way we did it is we only include those kind of gold standard documents in it. So make sure the generative AI is not taking information from the internet everywhere. It's purely from those documents we know are correct and up to date and you can see the source yourself.

Speaker 1:

Okay, in terms of narrating a kind of document in the way that I think you're describing. I've seen some pretty cool things like that kind of video, almost like that kind of you get your. So we send clients an annual wealth account that talks about their summary of their holdings and how they performed over the year. There's some cool stuff out there that we'll talk to a client about, that you can ask about how's that fund performed and it'll bring that information back. Yeah, we've probably not influenced that kind of stuff yet but, um, yeah, it's definitely out there.

Speaker 1:

One of the kind of things that we have been looking at is, uh, is avatars. So, um, you know, there's a bunch of, there's a bunch of stuff that um, uh, the the advisor kind of needs to talk to a client about. So, again, it's kind of process, but you know your simple service and cost disclosure, business cards, all the stuff that you need to do as a regulated activity, but it's not necessarily massively value additive. So we've had one partner bring us an idea and said, look, I've seen this. Uh, I'd like to record myself delivering that um, and allowing the client to say they've understood along the journey of different aspects of it, or be able to say I'd like to know more, uh, and then be able to kind of get that next level of detail.

Speaker 1:

But because it's such a cookie cutter process in terms of the stuff you have to say he's like, well, it's not a lot of value to me, it's not a lot of you know, that's. My value to the client is the them bit. It's not the generic bit, but wouldn't it be neat if I could send them this kind of link and get that kind of avatar and have that client interaction with the AI ahead of the meeting, and then we can, just when we actually meet, we can really kind of do the stuff that I'm really good at and that that we are looking at, and that's quite, that's quite exciting. It's quite scary from a kind of deep fake risk perspective, but yeah, it's, it looks like it's a yeah, kind of quite a you know, a neat use of AI to, I guess, kind of still have that client advisor interaction but also allow, yeah, that explainability of some of the documents, whether it's our attitude to risk stuff or the simple travel charge sorry, the service and gloss disclosure or whatever.

Speaker 3:

So we're doing a bit of that you mentioned hallucinations, so someone's going to be listening to this, thinking what are you on? About just explain what hallucination might be.

Speaker 2:

Yeah, yeah yeah, hallucination is basically the machine or the, the chat or whatever you call it. It's very confidently saying something that's completely made up. That's basically what hallucination is, and so, yeah, that's a huge risk and that's something when you, you know, buy an off-the-shelf tool, something, something to be really mindful of. But that's the kind of thing we are working on adding a lot of guardrails and other ways to address that.

Speaker 3:

And what are some of the benefits do you think to the partners? Let's just focus on that, the things that you're working on. Lots of people who will be listening to this, who are financial planners, people thinking about joining St James' Place. So let's just talk about the benefit of the tech and the AI that we have here at St James's Place and how it's going to enhance the advisor's career journey, professional journey.

Speaker 1:

Yes, we talked a little bit earlier around kind of giving advisors time back and I guess that's how AI is going to help me as an advisor at SJP. It is twofold I guess, well, maybe threefold actually. So on the one hand we can help give you time back to spend more time with clients. We can help drive up the quality, as Bi was saying earlier, of the advice, and at SJP the quality of advice impacts advisor remuneration and things as well. So kind of by driving up the quality, it's kind of also securing advisor income. It's the quality of the business and in our business sale and purchase when you're kind of then looking to exit, pass that business on. If we know the quality of the business that you've written in the past is good, that should, you know, secure the valuation of that book of business from a sales perspective.

Speaker 1:

But also, I was with a bunch of IFAs a few weeks ago and they were spending a lot of time thinking about AI but not knowing what questions to ask of providers to make sure they've done their due diligence and then not really knowing how to interpret those answers. And there seemed to be kind of three camps in the room. One was I'm really risked off. I don't know anything about this, so I'm not going to touch AI, which feels like a natural reaction. But then you don't reap the benefits of time and quality and things that we're trying to deliver at SJP. You have a bunch of the room who are I'm grabbing it, I'm running with it and I'll work out what happens later, which is obviously then risky from bias, touch and hallucination. But also you don't necessarily know the data is being processed or who's seeing your client's information in that sense. So that's obviously very risky.

Speaker 1:

And then the third party.

Speaker 1:

We're kind of saying, well, we're just kind of looking at what the big firms do and we'll follow suit with them. So, which obviously kind of made me kind of step back and thought, oh crikey, we better make sure we get this right. Then, if the industry is kind of following on, I kind of stepped back and thought, oh crikey, we better make sure we get this right. Then, if the industry is kind of following on, but because we worry about all that stuff and we worry about data protection, we worry about the security models, we worry about hallucination, we worry about bias Again, it frees up our advisors from having to necessarily worry about that stuff where it seemed like in the RFA community at the moment there's a kind of a lot of decent amount of kind of concern around how to grasp the opportunity safely.

Speaker 1:

And I guess so not only we can, I think I would say obviously I would say this is kind of SJP, but not only can we kind of deliver the benefits we talked about, but also we can help deliver them safely and that's safely for advisors and for clients, clients importantly as well. So that's safely for advisors and for clients, clients importantly as well.

Speaker 3:

So that's yeah, so that's why I'd say the benefit of SJPs kind of approaches, so what would you say is one of the biggest risk factors at the moment to financial planners playing around with AI and not really understanding the impact that it could have on a data perspective and a legal perspective? What are the risks they're taking at the moment that we're coming across? Because I bet you there's plenty of people out there playing with AI and just not quite fully grasping the risks they're putting themselves and their clients under?

Speaker 2:

Yeah, I'd say probably two biggest things. One is the AI application itself. So do you know what you're actually using it for, what actually comes out of it? How did they generate that answer for you? One hand, you use ChatGPT as a very generic kind of AI tool and on the other extreme, there are some very financial advisor-focused type of advice, ai applications and that's anywhere in between.

Speaker 2:

All of that has different know, different ways of um kind of how the algorithm works, how the data is being processed, how the gut rail works and does it. And also you think about financial advice and for your particular firm there are you know it's when at a very basic level, it's kind of English as the language right or any language. And then the second layer is your kind of financial industry language. So when we say consumer duty, it means something very specific which other industry doesn't understand. And the third layer is your company specific. So, like SJP, when we say partner we mean financial services, but that's not how partners understood in other kind of context. So all of that needs to be looked at very closely to make sure the tool is actually working for what you think it is doing, which in a lot of case that is not by default is that you need to do a lot of work to make that work. And also, how do you integrate that into your company's own ecosystem? So if you have Salesforce, if you have Snowflake, all of that, how does that work together? This thing can't work on its own.

Speaker 2:

So that's one side on the AI application side. The other one is obviously data. We don't need to do a lot of work in terms of understanding not only PI, so personal identifiable information is absolutely key with GDPR, all of that. Where does the data go? Is it staying in the UK? Is it in the EU, or does it go to the US? Do you use AWS? Do you use Azure? There's a huge amount of technical black hole there that I need to understand. And also even not personal identifiable information. There are still other information. You don't know how the model is trained. You don't know what a data output goes. Is it used to train further models and is that kind of legal or regulatory kind of compliance to do that? All of that kind of thing needs experts to work on it. So that's kind of what my team do.

Speaker 3:

So that is a massive layer of support for anybody that's a financial planner that wants to implement technology, specifically AI, into their business. I mean, even before AI come along, people struggle with tech. They struggle with their CRMs, they struggle with gathering data, getting the right information back using a CRM to their advantage, in the right way, in the most efficient way. Now, financial planners like to spend time with their clients, talking to clients, you know, having somebody in the background who is constantly tinkering with it, understanding the legalities of it, what's new, what's not, what's worth having, how does it, how does it work with all the rest of the technology within the business, I think it's vastly important, isn't it? It's really really important to have that confidence. It's like when you like join something like st james's place, right, the idea is that you can. It's like plug and play. You're a financial planner, you want to run a business. You don't want to be tinkering with absolutely everything around you, but you want it to feel like you're. It's your own business, right? You want to be able to lean into an ecosystem of support. Now AI is firmly within that place. Like you trust a company to deal with the compliance. Like you trust a company to look at investment solutions.

Speaker 3:

Marketing branding, uh, could be administrative power, planning, whatever it might well be to be able to free me up to go out and see clients, like it or not, ai is here, and the more you um are avoiding it, um, the more a you're putting at your risk.

Speaker 3:

You're putting yourself at risk that you no longer remain competitive, not just from an advisor to either advice firm perspective, but from a client perspective. If you're not keeping up with modern day technology in the way that clients want to work with a financial planner, you're going to get left behind. That in its own self can be anxiety inducing, right. So I guess, like you know, when you're thinking about like okay, I'm going to build a financial planning business, damn technology, ai, what we've got to do, it's a hell of a lot easier, more comfortable and risk, less risky to be plugging and playing to a company that's got a whole department, a whole bunch of experts, day in, day out, implementing, testing, trialing things. Do you do that directly with the planners as well? Then? Are you feeding back directly to the planners and seeing it live in the journey and making changes as we go along? Right?

Speaker 1:

yeah, we got a lot. We've got a lot of engagement with both, both advisors themselves, but also their teams, um, because it's often their teams that are actually doing a lot of the kind of the work behind the scenes. Yeah, um, I'm not yeah, it's not to say we've kind of cracked it and got everything 100 right. It's that constant kind of tinkering, but I think kind of what we're, because we're trying to look at the whole process end to end. I think one of the one of the risks that kind of by briefly touched on there is if you, if you kind of you could end up, you could end up procuring a load of ai solutions that fix different bits of the advice journey, but then how do you bring all that together? You end up with a load of complexity. So I guess we're trying to deliver that, that plug and play, as you kind of called it, which gives you, I guess, this, you know, a spine of running your business and then, um, there's still some variability in there. So you know if you're, if you're uh, you know if you're, if you're, if you're, if you're go-to-market proposition, in the way you want to engage your clients, is a real kind of goals-based planning type thing and you want to go and use a kind of cash flow tool, then we've got a couple of options there with Voyance and with Opal. We'll integrate the data there. You can choose to add that to your proposition if you like. It's not part of the kind of core spine but it's there as an option for you. So there's still some the data there. You can choose to add that to your proposition if you like. It's not part of the kind of core spine but it's there as an option for you.

Speaker 1:

So there's still some variability in there and it's kind of one of the things we're trying to do is then just make that easy so you can plug and play. But it's not like kind of joining the bank where everything's the same for everyone. You've still got some variability and you can go to market in slightly different ways with um, some different kind of tools and propositions. So there's um, it's a, it's a. What do we call it for? It's a. There's a phrase we had. There was a phrase we had like a little while ago, kind of talk about scalable personalization, um, and trying to kind of run that balancing act of having something that's a scalable kind of spine but also allowing that kind of yeah, that personalization to your business and to your clients. But let's look to the future.

Speaker 3:

AI is very futuristic and 2030 is a big date for St James's Place. Tell us a little bit about what you're hoping to achieve by then and what the plans are.

Speaker 1:

So from the big picture kind of corporate strategy point of view, there's kind of four pillars to this 2030 strategy. So there's bring brilliant at the basics differentiate client proposition, market leading advisor proposition and then high performing organization. And I guess within that first pillar of brilliant basics, there's this whole kind of mantra around simplify and standardize, so just trying to reduce, reduce complexity, streamline processes and give everyone more time back, frankly, advisors, but also kind of from a head office perspective as well. So I think, kind of AI and technology clearly key enablers in there. There is a whole load of process and business improvement and optimization we can do, but automation, ai are going to do a lot of the heavy lifting there, which should also then hopefully drive the differentiated client proposition, leading advisor offering and a more performance-based organization. So it's a key underpin of the strategy and an area we see ourselves continuing to invest in and focus on. But, bai, do you want to talk more specifically about?

Speaker 2:

the AI. Yeah, absolutely so. Yeah, that's the bit I'm really excited about. So I think that there are probably four or five key themes. The first one would be leverage maximum from unstructured data, because that's what really generative AI allows us to do more on that side, Even on the kind of structured side, structured data side. We know there's a lot of work we're doing and, on the brilliant basics side, doing that and the fact that we have using Snowflake as our data platform, which is a really modern platform, allows for both unstructured and structured data and to basically be able to do all of that.

Speaker 2:

And the second one is around this kind of chat agent type of thing, which is large language model retrieval, augmented generation, rack, and that's the chat SJP type of thing I was talking about. But that's really again, which, in theory, you'd imagine an ideal world where data and knowledge are all stored in the perfect manner that you can just get what you want. But that's not real life, is it? So it's always that component of saying I just want to have a question, I can search and get that answer to my question specifically using the data I want to use, not other things. So that's the power of that chat, SAP potentially. Then I think it's the things around, kind of multimodal, so things not only text but audio video, doing podcasts maybe next one we'll be doing that in a different way so that's multimodal set which really help not only head office partners but also client understanding as part of consumer duty, using different ways to get clients to fit for the way they learn things. The other one is AI workflow. So advice assistant is actually doing some of that, but we do want to enrich all the other features within advice assistant that allow AI, rules, decision automation, all of that in one workflow to streamline that end-to-end process, as John was saying earlier.

Speaker 2:

And finally, the big one which everyone's talking about this year is agentic AI which, yes, a new word has been invented, but the idea is that you have. Imagine today, I think I've seen the insurance company use case where, for a claim, people think about oh, how do we deal with this claim from insurance perspective? You probably have someone from underwriting, you have someone actually there, you have the reserve team, you have the actual people dealing with the claim itself. Looking at the pictures, the car crash, all of that sitting in one room, hopefully. But determine is there a claim? How much should I pay for? But change all those human to agents AI so I'm actually an AI agent, so they have their specific persona or roles, but then working together to come up with something, and you have a hell of an orchestrator agent coordinating between all those experts or agents doing that, and behind each of them is the knowledge I was talking about, the documents, the procedures. So bring everything together. That's kind of the next big big thing coming out.

Speaker 3:

So, yeah, that's exciting to me, agentic, yeah, yes, yeah that's internally as well at the moment.

Speaker 3:

Yeah, yeah I love the idea of that and also, as well, where that kind of adds huge amounts of value is especially around st james's place, because if I came in as a partner and I'm running my business and I wanted to just have my own business lifestyle business and perhaps I didn't want to employ anybody what an amazing way to run a business efficiently, with the most knowledgeable AI agents in my business helping me run it. All with different skills, all with different levels of expertise like that's exciting to me and that really does create a whole new dynamic to work-life balance, doesn't it? And I think that's um, that's super exciting. And that is being done now because I'm getting contacted by people who are talking to me about creating agents within what I do underneath the financial plan of life.

Speaker 3:

It's not a business that I want to grow with loads of people within it at all actually it's not and if I can create ai agents within it to help me with the areas that I struggle with. I love sitting in front of people, I love talking to people, I love business development. I love getting out there and selling and getting on social media. I don't like operations. You know. Operations to me caused me a massive headache and can actually take takes me about two hours to go through my inbox because my brain doesn't think that way. You know. I just want something to be able to understand, based on specific rules, what I can, what I want, what I don't want and where the opportunities are to create efficiencies. So I don't have to think about it, you know.

Speaker 3:

And also, I love the whole generative AI and I'm embracing like someone, like a podcaster right, there are tools out there now where I can chuck a document in and it creates two people talking yeah, in a discussion about the topic that I'm interested in. We're not a million miles away from loading up me into a system, my tone of voice you can do that now, right, but get a video of me doing it and all of a sudden, somebody can chuck anything in and have me as a host and I'm talking, I'm talking about it, so I actually think that's quite cool. I think that's a great way to create ways that somebody can absorb and learn information, because it is all about not. It's not about worrying that something's going to take your job. It's about worrying how can you get someone to understand what it is you do deeper in multiple learning styles. Right, and I love that. Like it's giving options.

Speaker 1:

There's a kind of there's a well-trodden kind of quote out there that you know is used in various kind of guises, but I guess in this context it's.

Speaker 1:

You know, it's not that AI is going to replace advisors, it's that AI advisors using AI are going to out-compete the advisors who don't.

Speaker 1:

And I think that's yeah, that's really interesting.

Speaker 1:

And from the uh, from the agentic, I mean one of the kind of one of the interesting things, one of the great things about um for well, that I find kind of working at sjp and having that kind of connectivity with advisors is that we sat in a room in this building with an, with an advisor who was, who came to us exactly on that and said I I've had this company come to me and say they can replace my back office with agents Are they kind of snake oil salesmen or is this kind of actually possible?

Speaker 1:

And we had a really good conversation with him about what he was trying to achieve and actually thinking about how that agentic kind of use case could really apply in advisor businesses and having that kind of connectivity with advisors is really helpful. Obviously, we don't want to go off and do a load of work and it doesn't actually work for the partnership. So having that connectivity is really great as well, and there's some when you've got four and a half thousand advisors out there. The idea is keep flowing in, so it's really good from an innovation perspective.

Speaker 2:

Yeah, and on that, what we also want to do, probably in the next talking about 2030, is create environmental sandbox or playground for partners to be able to play around with some of these things, so they can really try out their innovation with AI, with all the tools we can have, infrastructures we can set up for them. So really working together to get something that really works for our partners.

Speaker 3:

Which creates individuality and customization of their own partner practice, which is you don't want copy cuts of the same things across the board. You want people to be able to put their own stamp and their own mark on their businesses, like they are doing under st james's place, their own personalities within the business, and I love that. Creating a sandbox environment where someone can safely play and not mess things up, you know, and have the people in the background that are saying that you know, try this, it might work so also kind of share ideas right.

Speaker 1:

So I think kind of the conceptually, what we're thinking about is okay, well, if, uh, if, if one partner is trying to solve a problem, then there's probably at least a thousand other partners trying to solve the same problem. So actually if someone comes up with something and actually you know they play, they play around with it safely, they kind of you know actually this idea works. It's like we can we publish that to the whole partnership and allow the whole partnership to take advantage of it. I mean, some partners are already doing that themselves. We've got a few partners with um side hustle fintech businesses which are kind of solving particular problems very specific to sjp partners, and then they are selling those services out into other sjp partners.

Speaker 3:

It's kind of just trying to do that at scale it's quite interesting actually seeing a lot of um, ai and tech companies popping up within financial planning, being coming from financial planners. You know it's quite interesting. It's quite an innovative area at the moment, very, very interesting. Well, thank you so much for sharing the insight into ai and technology here at st james's place. It sounds like you've got your hands full and it sounds like the future is going to be very bright.

Speaker 3:

One thing I can take away from this is that ecosystem again, isn't it it? It's like you know, financial planners want to deliver financial planning. They're not AI tech experts, and I think we go to that idea of plug and play. What are St James's Place doing for me? How invested are they in technology and AI? Do they have their finger on the pulse, which to me, confidently sounds like they do? So watch this space. If tech and AI is something is on your radar as a financial planner, which it should be perhaps in james's place is the ecosystem that you should set your business up in. Of course, where's my check? Nice one, guys. Thanks so much for sharing your journey thanks for having us.

Speaker 1:

Thank you, thank you appreciate it.

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