Farbod Nowzad is the Co-founder and CEO of Cashmere AI, a company dedicated to enhancing client acquisition in the wealth management space through intelligent solutions. As the first-ever data science graduate from UC Berkeley, he leverages his deep understanding of machine learning and anti-fraud strategies to build and optimize business growth technologies. Before Cashmere AI, Farbod contributed his expertise to the anti-fraud machine-learning team at Lime. He is a progressive leader harnessing AI to transform traditional business practices, especially in the financial sector.
Here’s a glimpse of what you’ll learn:
[2:17] Farbod Nowzad discusses how Cashmere AI is changing client acquisition for wealth managers
[4:45] The AI adoption challenges in the wealth management industry
[7:41] The role of clients in driving financial services toward tech integration and AI solutions
[10:43] The three client acquisition modules of Cashmere AI's platform
[20:01] Farbod shares the engagement strategies that modern wealth management firms are employing for successful outreach
[21:53] The challenge of AI hallucinations and the innovative solutions employed by Cashmere AI
[24:37] Advice on the use of AI
[27:11] Farbod’s leadership style and the importance of focusing on what's best for the company
In this episode…
Are you finding client acquisition challenging in the ever-evolving financial services industry? What if there was a way to seamlessly integrate luxury, efficiency, and intelligence into your customer acquisition strategy?
Data Scientist Farbod Nowzad delves into how his company uses AI to enhance client acquisition in the wealth management sphere. He stresses the significance of AI and how Cashmere AI’s three-part system — identification, enrichment, and engagement — enables advisors to efficiently pinpoint and nurture relationships with potential clientele through AI-driven insights and personalized outreach. He elaborates on the data-driven methodologies that can propel financial advisors toward incredible growth and client engagement.
In this episode of The Customer Wins, Richard Walker interviews Farbod Nowzad, Co-founder and CEO of Cashmere AI, about AI-powered client acquisition in wealth management. Farbod discusses how Cashmere AI is changing client acquisition for wealth managers, its three client acquisition modules, engagement strategies modern wealth management firms employ for successful outreach, and innovative solutions for AI hallucination.
Resources Mentioned in this episode
"[AI Series] The AI Edge: Supercharging Financial Advisors With Denis Konoplev" on The Customer Wins
"[AI Series] Empowering RIAs for Personalized Customer Wins With Cormac Murphy" on The Customer Wins
"[AI Series] AI for Wealth Management Marketing With Jonathan Michael" on The Customer Wins
"[AI Series] Streamlining Operations With Cutting-Edge AI Technology With Babu Sivadasan" on The Customer Wins
"Scaling Business Through Community as an RIA With Joe Moss" on The Customer Wins
Quotable Moments:
"We help financial advisors acquire new clients in a really intelligent and efficient manner."
"Financial services are historically not necessarily like the early adopter of technology."
"Having the right tools and technology now that they're available, is really important to be able to have a thriving business in the future."
"Eventually, if we can build a full suite of tools and products, it could be quite powerful."
"If somebody came along who was better than me at being a CEO for this company, I would happily step aside."
Action Steps:
Leverage AI for client identification: This optimizes prospect discovery times, ensuring advisors interact with potential clients at pivotal financial moments.
Incorporate AI-driven customer insights: Creating richer client profiles can significantly qualify leads, enhancing the probability of successful engagements and long-lasting relationships.
Utilize automated engagement strategies: Adopt AI systems for outreach and follow-ups to personalize interactions and maintain consistent communication with potential clients.
Stay informed about AI limitations: Understanding AI's capabilities and inherent limitations can prevent an over-reliance on technology and inspire a blend of human creativity with machine efficiency.
Prioritize company-wide objectives over personal ambition: This leadership approach ensures decisions are driven by what's best for the business, fostering healthier growth and adaptability.
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Episode Transcript:
Intro 0:02
Welcome to The Customer Wins podcast where business leaders discuss their secrets and techniques for helping their customers succeed and in turn grow their business.
Richard Walker 0:16
Hi, I'm Rich Walker, the host of The Customer Wins, where I talk to business leaders about how they help their customers win and how their focus on customer experience leads to growth. Today is a special episode of my series on AI, and today's guest is Farbod Nowzad, founder and CEO of Cashmere AI. Some of our past guests in this series have included Denis Konoplev of Munin AI, Cormac Murphy of CacheTech Advisor Solutions, Jonathan Michael of Wealth I/O and Babu Sivadasan of Jiffy AI.
Today's episode is brought to you by Quik!, the leader in enterprise forms processing. When your business relies upon processing forms, don't waste your team's valuable time manually reviewing the forms, instead, get Quik! using our Form Xtract API, simply submit your completed forms and get back clean context-rich data that reduces manual reviews to only one out of 1000 submissions. Visit quikforms.com to get started. Now, before I introduce today's guest in full, I want to give a huge thank you to Joe Moss, the founder of ProAdvisor Suite, go check out his website at ProAdvisorsuite.com to join their thriving RIA community.
All right, Farbod Nowzad was the first-ever data science graduate from UC Berkeley. How cool is that. He started Cashmere AI with a co-founder to bring an effective, intelligent client acquisition platform to the wealth management space. They've raised 3.5 million from top-tier venture capitalists, and are working with all types of clients across wealth management. Prior to Cashmere, he worked at Lime on anti-fraud machine-learning team. Man, you got a great background. Farbod, welcome to The Customer Wins.
Farbod Nowzad 1:57
Thank you for having me Rich.
Richard Walker 1:59
I'm excited to talk to you. So for those who haven't heard this podcast before, I talk with business leaders about what they're doing to help their customers win, how they built and deliver a great customer experience, and the challenges to growing their own company. Farbod, let's understand your business a little bit better. How does your company help people?
Farbod Nowzad 2:17
Yes, so, we started this business almost out of serendipity. My co-founder and I, we went to high school together. We've known each other for over a decade now. We came together, and we ultimately just wanted to kind of solve problems for people, but didn't know what problems we wanted to focus on. We were engineers, data scientists, machine learning people, so we knew we kind of had a skill set and kind of had that entrepreneurial itch. We were spending a lot of time with people in the financial services industry, specifically wealth managers, financial advisors, and kept kind of hearing this very consistent narrative around how they were going about doing business development, client acquisition.
And what was interesting to us was that, here's an industry that has $60 trillion in assets under management, just in the US alone, the clients that they get kind of look like enterprise sales. If you close a five, 10 million account in wealth management, that can be 50, $100,000 in recurring revenue, essentially forever. But the way that firms were going about acquiring this new business was archaic. They essentially just rely on word of mouth and referrals. They don't have any infrastructure, any really data-driven solutions for finding the right clients, the right prospects the right time, and kind of engaging them in an efficient manner. And so we kept, kind of hearing from the market that people wanted a solution around this, that they needed more efficient, effective ways to acquire new business and kind of move out of that old realm of prospecting, that old way of growing their revenue.
And so we felt like just kind of given our backgrounds and our understanding of the space, that we were uniquely situated to actually solve this problem. So in short, how we help people is we help financial advisors, wealth management firms acquire new clients in a really intelligent and efficient manner.
Richard Walker 4:20
Okay, that is awesome. And historically, financial services has been slow to adopt tech and sometimes behind other industries entirely. But sometimes there's a reason for that, so I'm kind of curious, did you guys have any trepidation or fear that the old way was the only way it could work? Are you creating something that actually wouldn't work as impossible? And did you face that kind of dark moment in this business?
Farbod Nowzad 4:45
We've definitely faced dark moments and moments of doubt around kind of the efficacy and need for what we're building. And really, I think the solution there was just trying to create as many touch points as we could with potential customers, understanding their needs and kind of iterating the product and the solution that we were building to really align with kind of the problems that they needed solved. And I think if you can kind of take that customer-first approach to problem-solving and really kind of being able to read between the lines and provide what people need, ultimately, if you build a great product that I think addresses those things head-on, the market kind of does its job. But it is interesting, because you're right, financial services is historically, not necessarily like the early adopter of technology.
There are a lot of existing systems in place, compliance bureaucracy. And what was interesting in wealth management is that you have kind of a older kind of generation that is in control a lot of the assets that is playing kind of the role of financial advisor. A lot of them have built up their books over a number of decades, and so no, they're getting recurring revenue. They don't have customers that churn. It's a really kind of cushy situation for them. Why change something if it isn't broken. But I think now as we're kind of seeing a younger generation of advisors coming in, obviously, one of the largest wealth transfers in history, where those people who are kind of in charge of the assets today will not be in charge of the assets tomorrow.
And so a lot of the forward-looking institutions and just individuals who care about their own business want to stay ahead of that curve. They don't want to be left behind as this wealth transfer is occurring. And so having kind of the right tools and technology now that they're available, is really important to kind of be able to have a thriving business in the future.
Richard Walker 6:49
Okay, there's two really, I think, very distinct things to talk about here. First of all, when you talked about how you listen to your customer, you put them first, and that creates the right product, and therefore they will buy it. That's a mic-drop moment in my mind. That's what I was expecting. Like, boom, we're done. Because you just defined how to build the best product. Is truly listen to your customer, and even though you have those dark moments, those fears, those challenges of like, could this work or not?
And believe me, oh my gosh, I've had so many in my business, if you're truly delivering what your customers are asking for, they're going to buy from you, and you do have a product, so thank you for stating that. But the other thing I want to talk about with this industry, because you're right, there's a transition going on between old ways of doing things and new ways of doing things. How much do you think the client is driving that with younger clients having the expectation of better tech, different experiences than they're used to?
Farbod Nowzad 7:41
I think that's a huge piece of it. That's a huge piece of it. The younger generations are used to a completely different customer experience. And so, if there's a dislocation between how you've spent kind of your entire life dealing with service providers, and then now that you're coming into wealth, having to almost revert back to an outdated way of receiving a client experience, the technology that you interact with, it's just not going to work out. And I think a lot of new businesses have identified that opportunity.
There's a number of RIAs wealth management firms that are built on the ground up over the last few years, with kind of technology in mind and that younger generation, that new type of client in mind. And so I think that is one of the big kind of macro factors in terms of how wealth management and financial services evolving as a whole, is just a completely different set of kind of client expectations for what a great experience should look like.
Richard Walker 8:42
So it makes me wonder, though, does that mean your product is viable because of this younger generation, because of that expectation, like if you had taken your product back 30 years ago, would it work? Would the clients actually respond to it the way they are today?
Farbod Nowzad 8:58
It's a great question, I think, like, first of all, I think our product would not have been able to work 30 years ago, but I think that's largely due in part to the fact that a lot of what we've built is based on the data that we get. Data availability has become quite mature over the last few years or decade, the ability to clean data and make it actionable and human-readable has become so easy and cheap also, thanks, in part, due to GPT, right, where you can take large amounts of unstructured data turn it into something which is consistent, right, if it's a specific schema.
And so what this enables is a startup like ours to be able to look at dozens of different data sources, public data, third-party data partnerships that we have, government data, and then parse that at scale without having to spend millions of dollars to do it, but rather maybe hundreds or 1000s of dollars to do it, and then ultimately transform that into a product that advisors and firms can, like, really take advantage of. And so I think there is a unique opportunity today to actually build a platform that finds the right prospect for the right firm at the right time, and essentially, replicate what a human could perceive is like a great prospect, and kind of codify that and turn it into like a real, like technology platform.
Richard Walker 10:31
All right, let me get a little bit more specific about what your product does. Is it prospecting? Is it helping a prospect move into client, onboarding. What is it technically you're doing?
Farbod Nowzad 10:43
Yeah, that's great question. So our platform handles the prospecting process from start to finish. When we first started this business, we thought we'd be able to just scrape some data and sell it, and it would be a done deal, but we've realized that we've really had to own, kind of the entire prospecting and sales journey, from the very beginning, from discovery all the way through to engagement and kind of beyond helping our own customers set up their processes. So there's kind of three main modules for our platform, and they all kind of work in concert together.
So the first piece of it is around identification. We've built a lot of data infrastructure that is looking at private data, public data, government records, to identify prospects kind of at the right moment in their lives when they really need access to financial services, when they really need access to wealth management, insurance, accounting, all these different things. And so we're looking for kind of certain signals and attributes that tell us that this is a qualified client, and that right now is the time to actually go after them and make a sale. Some of the things we're looking for are money-in-motion events. So maybe somebody sells their business, maybe they get a promotion or a new job that puts them on a new income track. We look at things like stage of life.
So if you have kid, if you went through a divorce, had an inheritance, just moved, these are some of the signals that are interesting to us and really actually change a lot of the efficacy around sales. If you go out, if you go to somebody after they just had a massive liquidity event, they're much more in need of wealth management than when they were broke. And so those are some of the interesting patterns that we look for. The next piece of it is around...
Richard Walker 12:35
Hold on real quick, before we go to that the identity piece, it sounds like you're finding just names, just people. So these are cold, or is this within an advisor's prospect list that they've already been working on?
Farbod Nowzad 12:49
Yeah, so we can do both. So we're able to find stuff cold just kind of looking at like the whole kind of universe and global population, but we are able to also kind of overlay a lot of these signals and patterns on top of an existing set of prospects or leads. So, there's a firm we're talking to that has 100 million people in a CRM, and so they want to understand what's actually happening in these people's lives, who they should be going after?
Richard Walker 13:19
Because that's one of the hardest things in sales. A mentor of mine said it like this, think of a plane takes off, cruises and lands, right? If you talk to somebody who's still on the runway, they're not ready. If they're just taking off, they're not making a decision. If they're cruising altitude, maybe they're in decision-making. If they're landing, they're implementing like they're ready to go. And you want to find these people who are going on that downward curve, right? So those are different times in people's lives, or stages of business, or whatever it is, is that what you're helping identify then?
Farbod Nowzad 13:48
Exactly, that's a great, I'm gonna start using that analogy actually, I like that.
Richard Walker 13:52
I'll have to say hi to Steve Mednick from USC then, he's the one who gave that to me.
Farbod Nowzad 13:56
Okay, I'll give credit to Steve.
Richard Walker 14:00
So go on to the next phase.
Farbod Nowzad 14:01
Okay, so the next phase, then we've identified names we know that people is actually building understanding around them, so that we call this kind of like enrichments and insights. We're getting things like their personal backgrounds, professional backgrounds, wealth, information, income, the things that would really qualify them for a financial advisory business and really just develop a deep understanding of who this person is across, again, kind of dozens of different attributes that really help us filter down to the ideal client profile that somebody cares about. A lot of the kind of AI components are integrated at this step where we look at priority scores, so for any given kind of firm or team, who is the best prospect for them to be going after.
And the way we've kind of built that out is really quite interesting. Think what we found is that the decision from an investor, from a consumer to go with a financial advisor is one that is very oriented in just the personal relationship. So obviously the brand of your firm does make a difference. It does instill trust, but ultimately you make a decision on who do I feel like I can have a real relationship with? Who do I get along with, who has kind of the areas of expertise or understanding of my unique situation? And so we leverage AI to actually look at all the users of our platforms, all the financial advisors and their personal backgrounds, their areas of expertise.
And then on the other side, look at all these prospects that are kind of coming in through our data infrastructure, and really match the advisor with the prospect who's best fit for them, and vice versa on kind of a number of these more personal and experiential attributes, and that ultimately, creates a lot more success for the advisors as they're figuring out who they need to be focusing on as potential prospects got it.
Richard Walker 16:06
Got it. I mean, look, one of my biggest questions I want to ask, but I haven't heard phase three yet, is, could a brand new advisor succeed with this? I mean, could this just build their business? It would give them such an edge to have all this potential prospect pool to work with.
Farbod Nowzad 16:22
I hope eventually it could be that simple, and we can really own a lot of the other I think, like second-order variables that matter here. I think the brand you build around your institution matters. Being able to actually provide a great service for your clients matter, especially once you start having that conversation and the clients asking you, who have you worked with in the past? What have you done before? Do you actually understand my situation? I think those are things that we can't really abstract away for our users just yet. But the third phase of this, actually, the third kind of component is around engagement piece. So what we found was that a lot of advisors, they just don't have enough time.
They don't have enough training in how to actually engage these prospects, what to say, being consistent in sending messages, follow-ups, doing all the scheduling. And so we've built a lot of automation, actually, on behalf of the advisors that use our platform to help them actually do email outreach, do follow-ups, content that's really personalized the situation. And so the idea there is, in theory, you could just like you're saying Rich, turn the machine on and kind of have it work on your behalf, behind the scenes, really, without having to interfere too much manually with the process. So, hopefully one day, we'll be able to, kind of allow somebody to go a billion-dollar book from zero without doing like any work, but I think there's still some more left.
Richard Walker 18:04
So you're right. I don't know that my question is truly fair, because somebody who hasn't established their brand, they haven't established their history, it's really hard to work with them. It's hard to trust them if you're an investor. And so maybe it's more aligned with the junior planner who joins a firm that is established, or somebody who's coming up through the ranks or somebody who's just fairly new, but has a bigger team to work with, and you want to help push some leads and opportunities to this person, help them grow and establish their own book of business. Maybe it's going to help accelerate that process.
Farbod Nowzad 18:36
Exactly, exactly. And a lot of people are trying to do some of this work manually these days, and so even being able to just create a lot more efficiency for them to run this process, start to finish, give them insights that they wouldn't have had otherwise. That allows them to be able to focus on, I think, what matters most, which is serving their existing clients, right, managing kind of those relationships and those assets and so outside of kind of growing your AUM, it just gives you a lot more kind of time back to focus on kind of the places where you find the most flow, right, and do the work that's most fulfilling for you as an advisor.
Richard Walker 19:17
Man, my head is spinning because I've had so many guests on the show that could benefit from meeting you, frankly, because what if you could plug into their systems and give them scores or give them engagement or give them better ways to match to the person that they're trying to match up with? So I interviewed the guy whose website is freefinancialplan.com. Anybody can go sign up for a Free Financial Plan and they match you up to an advisor. But what if your system helped them match up to an even better advisor, and so they're far more likely to win and then engage them, et cetera? So you hit on something, I think that's pretty, pretty cool. When you talk about engagement, what does exactly that mean? Are you doing emails, social posts or sending articles? What does that actually translate in to?
Farbod Nowzad 20:01
Yeah, so emails is definitely one of the low-hanging fruit, easy to automate. We're able to set up drift campaigns and get quite creative with like, the complexity and sophistication of how we set those up. Who receives which emails. I think this kind of goes a little bit to how we're thinking about how we provide a service for our customers is beyond, automating email outreach, for example, or LinkedIn outreach. How can we provide a service that really helps them think through their brand presence online, right? So that when somebody sees them or hears about them, they're kind of putting their best foot forward and establishing that trust with that person, because that first impression matters so much.
And even if you're using our platform, if your brand sucks, it's a lot harder to have success. Doing a lot of the sales here, putting together marketing content, right? How can we take some of the data, for example, that we're able to provide, and translate that maybe into targeted advertising campaigns, right, to a known set of individuals who are going through a very specific set of circumstances that they've defined. So I think today it looks a little bit narrow, focused on email outreach, LinkedIn outreach, starting to provide some support on kind of marketing and advertising. But eventually, if we can really build a full suite of tools and products and kind of connect all the different pieces of the funnel together, I keep thinking, be quite powerful man.
Richard Walker 21:30
Man. All right, I want to ask you a challenging question. With all the nuance of large language models and AI, there's a lot of talk around hallucination, right? The AI invents things and comes up with the wrong answers. How do you guys, if you're using large language models, I'm making this assumption, how are you avoiding those types of pitfalls and errors so that you're not kind of screwing up the relationship that you're nurturing here?
Farbod Nowzad 21:53
Yeah, okay, that's great. So I can give you a really, like, a fun example. So one of the things we do is we leverage AI to come up with, like suggested content for, let's say, email outreach messages. And exactly, hallucinations are totally a thing. You want the email to write a certain way, you wanted to say certain things, but it's a little bit probabilistic what the exact outcome is going to be. So one solution that we've come up with is something called a discriminator model. And so what that is essentially an adversary to the original model that's creating content. So it's kind of two AIs competing against each other. And so what we do is we have the first AI actually create the content based on a set of criteria. We give it sample content so that it can mimic that tone of voice. We give it a set of criteria around what it should be writing, and then it generates an output.
Then we have a second AI that is judging the output of the first AI based on a different set of criteria and a different set of sample content that we believe are of high quality. And so what's cool here is that it can essentially come up with some sort of judgment on, was this a good piece of content or not? Was it truthful, right? So you can maybe reduce the, they call it temperature, right, so that it's hallucinating less and is a little more strict on the outcome. And then if it does not pass, basically the second AI's test it then puts it into a loop to rewrite that content based on the issues. And in theory, you know, this loop could kind of go on forever until it's fully correct or up enough, or at some point maybe you just have to kind of call it quits.
But that's been a really interesting strategy that we've been leveraging to kind of reduce hallucinations and create content the way we want it to. Ultimately, I think part of it is the models are just going to get better, and already, if you look at the models today versus what they look like six months ago, 18 months ago, the improvement is pretty dramatic. And so, if something is kind of working today using these models, you can make a pretty sure bet that it's like really going to work in the future. And so I think there's a lot of opportunity for other kind of businesses and founders to think through stuff that might be not fully ready for production or enterprise today, because the models aren't good enough. But if it's kind of working, you can make the bet that the models are going to eventually get there, and you're very minimal hallucinations.
Richard Walker 23:02
Man, that is so clever to have them compete against each other. So it sounds like agents that are working on your behalf behind the scenes you've essentially programmed and said, do these jobs and check each other's work. Super smart. My gosh, okay, look, I have so many questions, and we can't go on forever, but I do want to ask a very like pointed AI question, because you're an AI scientist, what is something that you know that most people don't know about AI but should be aware of and think about?
Farbod Nowzad 24:37
That's a really interesting question. That's a really interesting question. So I think something to keep in mind is that these models are limited by the human understanding. So they are trained on our existing knowledge. They're trained on our existing way of doing things. They don't really have the ability to, quote, unquote, be creative. And so I think that's something to keep in mind as people are trying to explore new and novel ideas that have not been explored yet, is to not become too reliant on these AIs, just because there are kind of limitations there. I think eventually we might create models that are trained in a way that they are able to come up with completely new ideas that we haven't thought of ourselves. And so I think having a little bit of hesitation maybe, or apprehension around the full capabilities of these things is probably wise.
Richard Walker 25:59
Yeah. Okay, that's really, really smart. Because even like the pharmacist companies that are combining new elements together faster with AI and coming up with new ideas, it's still regurgitating what we know. It's not finding a new plant in the Amazon rainforest and bringing it out and figuring out something new at that. So the idea of invention is really hard. That's good. Man, we're gonna have to wrap up. But before I ask you my last question, what is the best way for people to find and connect with you?
Farbod Nowzad 26:30
The best way would be to go to our website, cashmereai.com or they can just shoot me an email farbod@cashmereai.com easy.
Richard Walker 26:40
Do you guys have some affinity with cashmere that you chose that name?
Farbod Nowzad 26:44
No, not especially, but the idea is that we are a fabric that sits on top of your existing systems, existing infrastructure. And cashmere is the most luxury, the best fabric and has some ties to wealth.
Richard Walker 27:02
I love it. I love it. All right, so here's my last question, who has had the biggest impact on your leadership style and how you approach your role?
Farbod Nowzad 27:11
Yeah. So there's a gentleman, Chase Gilbert. He's the CEO of Built and what I've learned from him is that you kind of have to take yourself out of the role. That it's not about me Farbod, the CEO, but really ultimately about Cashmere, the company. And my role is not to better myself, my role is ultimately to be kind of a shepherd for the business. And so, with everything that I do, I really do try to take my ego and self out of it and ultimately make a decision that's best for Cashmere. And what Chase once said to me was that, if there was somebody who came along who was better than me at being a CEO for this company, I would happily step aside because that's how much it's not about him. And so I think that's a really kind of powerful mentality to have.
Richard Walker 28:11
I do share that mentality, by the way, I've always said to my team, check your ego at the door. It's not about who. It's about what we're trying to solve, and it's really, well, it's about our customer what they want. So I really, really cherish that, and I applaud you for adopting it. Man, honestly, I still want to talk to you, but I don't keep these episodes too long, so I want to give a huge thank you to Farbod Nowzad, founder and CEO of Cashmere AI, for being on this episode of The Customer Wins. Go check out Farbod's website at cashmereai.com and don't forget to check out Quik! at quikforms.com, where we make processing forms easy. I hope you enjoyed this discussion, will click the Like button, share this with someone and subscribe to our channels for future episodes of The Customer Wins. Farbod, thank you so much for joining me today.
Farbod Nowzad 28:59
Thanks so much Rich.
Outro 29:02
Thanks for listening to The Customer Wins podcast. We'll see you again next time, and be sure to click subscribe to get future episodes.
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