Fintech Insider Podcast by 11:FS
00:07:24 · Matthew Goldman
[00:07:24] S3: I think absolutely the problem still exists. The, you know, the currency may be different, but the aspect of consumers have money, need advice, but don't maybe have millions of of dollars, you know, to pay a financial adviser is very much the same challenge. And I think with AI, everyone's just doing this for themselves. Right? They're asking their their chatbot of choice. And in The US, we've seen all of them, all... You know, ChatGPT, Claude, Perplexity investing in things like, you know, open banking links so that they can bring in that data and provide it to you. But what we don't know is if it's any good. Right? Or if they're misleading consumers. We know that AI can do that with other aspects like medicine and mental health, and we've seen the the downsides of that. I have not seen any indication that there's the kind of regulatory innovation here of this middle ground. And I think right now, we're still stuck. And officially, there is all these sites that give you financial advice and then have a disclaimer that says, but this is not advice because they don't wanna get, you know, sued or or fined or whatever. And then very expensive financial planning. And some of the big firms have tried something between where you get a financial plan for hundreds of dollars, but those are actually quite poorly done. Right? They're very generic. So I'm I'm really excited. I was really excited to learn about this from from The UK because I think a similar thing would be very helpful here. People want that advice, but they also don't want to make mistakes. And an interesting kind of last point is I started to see the marketing from large financial firms echo this. Like, there's a new Fidelity Investments campaign, which is basically like, I wanted help from a person along with AI. So it's kind of talking in the same language. And the the message is I can use Fidelity's great web tools, but I can also still talk to a person. And I think that's still where a lot of consumers want to go.
00:09:20 · Kate Moody, Brad Wiskirchen
[00:09:20] S0: Yeah. Absolutely. Brad, what was your what was your take on this? Can you take your perspective? [00:09:24] S4: You know, I I I think I think you hit it head on. First of all, explainable AI is difficult with LLMs and and neural nets in general. And that's because LLMs aren't necessarily deterministic. They give different answer... Different answers if asked the same question. So, you know, one of the big questions is how do you ensure AI generated solutions are reliable, explainable, and based on appropriate customer information. But, Dan, I'd I'd ask you, how are how are you approaching the balance that was just referenced between automation and human oversight as Plum develops a service? Then what happens when the AI system produces a recommendation that isn't appropriate for a particular customer?
00:10:05 · Daniel Wills
[00:10:05] S2: Yeah, absolutely. I think, the way we're looking at it is, like a staircase. So I guess on the bottom steps are the everyday questions. So, how much did I spend eating out last month, or how much should I put aside for the holiday? I think the the technology can handle those sorts of questions brilliantly. I guess as you climb the stairs and the decisions get bigger and more personal, I guess, the human element, would start to to creep in to those conversations. A big part of my role, I guess, is reviewing our AI assistant the way I'd review a newly qualified financial adviser. So what we're focusing on here at Plum is making sure that our assistant is just as good, if not better, as a human in terms of how we're interacting with our customers. Right? So there was a study done by the Journal of the American Medical Association whereby people had a conversation with a human being in terms of their medical issues and then a chatbot. And then those answers were assessed and actually came back to that the bot was more empathetic, was more understanding, provided better quality answers than than the human. So something that we need to focus on, especially when it comes to finances, where particularly in The UK, it's... There's almost a stigma attached to talking about money. So for our customers, this is the very first time that they've had any sort of conversation around money, let alone kind of financial guidance or targeted support. So we want to make sure that we're testing it as much as as possible. We're we're doing the checks, getting those in place ahead of time to kind of preempt and prevent any misadvice, wrong advice going out. But of course, if it does happen, then taking accountability, I guess, is the most important thing to be doing, not just for ourselves, but across financial industry. So, for me, I guess the technology gives us the reach, there's massive opportunity here. But people behind it will give it the judgment and then the human role grows, I guess, as The states rise in terms of complexity.
00:12:25 · Kate Moody
[00:12:25] S0: Yeah. No. Absolutely. I guess the other thing I was keen to get your take on, Dan, is I think Plum's in a really interesting position because you are a, you know, an intelligence player that sits on top of mostly other people's accounts, Whereas some of the other players that you mentioned who have already moved into the Tata sports space, know, Aviva, Barclays, I'm assuming are mostly kind of focusing sort of inward on their own sort of product suite. Has that shifted how you've thought about the potential of targeted support? You know, obviously you are looking into other people's accounts potentially. We know that customers have in many cases, in multiple parts of world, like quite fragmented financial lives where their money is in multiple different places across different accounts. So yeah, suppose I'm intrigued whether potentially Plum has a bigger opportunity with targeted support because you're not just looking into your own universe and trying to make it better within the bounds of your own, your own bank or investment platform.
00:13:19 · Daniel Wills
[00:13:19] S2: Yeah, absolutely, Kate. I think when we do that, what we, what we find is a lot of our customers, what they like to do is save money in cash. Right? And I think that feeling of safety deserves a lot of respect, wanting the security of cash. It's not an irrational feeling, especially when, you know, today's news, not just today, but ongoing, is full of uncertainty. We just had the budget here in The UK and household budgets are stretched, and that's part of what our Auckland budget was focusing on. So I think the approach is to show the way, not push our customers down a particular direction. So we want to be honest about the trade off. So cash obviously protects you from the short term ups and downs, but over longer periods with rising prices, obviously, that can erode cash's value in real time. So investing has historically offered a lot of potential for growth, but the value can obviously go up and down as well. So you need to be comfortable wearing that level of risk. But it is something that we want to talk to our customers about through the bot. If we feel like it's the right thing for our customers, I think it's just as important for the bot to say it's not right at this present time. But we want to make that experience as personal as possible. And we feel we're already doing that, particularly when it comes, for example, to retirement. We can show someone the age they'd like to retire based on a conversation where they've selected that age and what they're currently on track for and obviously giving them that opportunity ahead of time to to bridge that gap rather than getting to to retirement and not being able to retire on your own terms. So giving people, you know, support through this new targeted support is how we feel, you know, it's a massive opportunity and we consider it a really an important responsibility to deliver good outcomes for our customers.
00:15:16 · Kate Moody
[00:15:16] S0: Yeah. Yeah, as I think we've alluded to throughout this conversation so far, obviously, it's a new initiative. We're still kind of seeing how it's how it's playing out with multiple different players in the market. So kudos to to the team at Plum for for getting the approval and getting it live and yeah, we'd be excited to keep an eye on this to see how it how it plays out in the customer experience and how customers interact with it as well. Okay. On to our next story, and this has been taken from the papers, and that is Chargebacks911 launches indemnification for AI agent purchases. US based dispute management company, Chargebacks911, has launched a new service designed to protect merchants against qualifying chargebacks arising from purchases made by AI agents on behalf of consumers. As AI agents increasingly search, compare, and purchase products for consumers, questions are emerging around authorization, liability, and who bears the cost when a transaction is disputed. The service uses AI technology, behavioral intelligence, and dispute data to identify agent initiated transactions, assess their risk, and determine which qualify for indemnification. It operates alongside merchants' existing fraud prevention and payment infrastructure without requiring changes to their checkout systems. Brad, I'm obviously gonna come to you first on this one. Congratulations on the launch. Obviously we've touched a little bit on AI already in discussion of Plum's story, and obviously I'm guessing it's a massive focus for you guys as well. Could you maybe talk our listeners through kind of how you've got to this offering, kind of again we'll have a mixture of levels of understanding of of AI and its complexity amongst our base. It'd be good to understand a bit more about you. What made you decide to to introduce this service?