The Latest In Financial #AdvisorTech (June 2024)

Altruist Raises $169M To Cement Its Status As The #3 Custodian (But Can It Ever Reach #1?)

Building an RIA custodian from scratch is a massive, not to mention risky, undertaking. There is an immense need for capital in order to first build the backend custody and trade clearing functions that are the custodian's core services, and then to cover overhead expenses until there is enough revenue to keep the lights on. For that reason, very few of today's RIA custodians were actually built from scratch: For example, Charles Schwab and Fidelity, the largest two RIA custodians by far, arose as extensions of their firms' much larger retail brokerage platforms, which gave them the pre-existing size and scale to branch out into custody without having to build it from the ground up.

There's a natural wariness that advisors might have about working with a custodian that also has a significant retail presence, since many can't help but wonder to what extent they're in competition with their custodian for their own clients. In reality, however, it seems like the 'Big 2' custodians do a more than adequate job of keeping their retail and custody divisions separate (as, despite the worries, the actual number of clients reportedly taken from advisors by their custodians appears to be miniscule), and ironically there have historically been significant benefits to working with a custodian with a strong retail presence. For example, smaller independent advisors who have little name recognition on their own can benefit from the credibility that comes from aligning with a 'name-brand' platform like Schwab or Fidelity. Additionally, having retail and RIA custody all under one roof allows clients to move money into (or away from) an advisor's management without the need to transfer funds from a different institution. Which ironically has meant that, although custodians rarely pilfer clients from the RIAs on their platforms, RIAs have shown no such reluctance about taking clients from the custodians' retail arms – a fact that doesn't seem to bother the custodians, for whom it makes little difference whether a client's assets are on their retail or custody side as long as they remain on the platform. Custodians have even encouraged advisors to pull from their retail customer base through the use of advisor referral programs that move retail clients to the advisor custody side (with the custodian getting a cut of the resulting advisory fees).

However, the downside to Schwab and Fidelity's custodial platforms being built on their pre-existing retail platforms, as well as their entrenched status as market leaders among RIA custody, has been that the firms have been notoriously slow to adopt technological improvements, like paperless account opening, automated rebalancing, and performance reporting, that have become increasingly important for advisors to scale their investment management offerings as investment management itself has become more commoditized and financial planning has become more central to many advisors' offerings.

Into this environment came the 'upstart' RIA custodian Altruist, which sought to become the first major RIA custodian to build its platform from scratch solely to serve RIA firms. In the 5 years after its founding in 2018, Altruist collectively raised over $280 million in capital to systematically rebuild the RIA custodial stack layer-by-layer, including account opening, trading, performance reporting, and in the wake of breaking off from its original custodial partner Apex Clearing in early 2023, its own layer of custody and clearing. All of which allow a level of technological efficiency that simply hasn't been possible at any other custodial platform (none of which have been willing to overhaul their entire retail operations simply for the benefit of improving their advisor end).

Against this backdrop, Altruist announced in May 2024 that it has raised another massive $169 fundraising round, bringing its total capital raised up to $450 million and its total market valuation to $1.5 billion. The fresh capital will likely buy Altruist more than enough runway to achieve breakeven cash flow, firmly entrenching it as the #3 custodian behind Schwab and Fidelity, and likely putting to bed any questions from advisors about whether the 'startup' custodian will overcome the high barriers to entry in the custodial market.

In fact, the new question is really just how big Altruist can get. From an advisor perspective, Altruist's positioning itself as the most tech-savvy RIA custodian – with better straight-through processing for account applications and transfers (and a resulting drastic reduction in NIGOs) and a more modern advisor dashboard – makes for a smoother experience than its competitors, while a growing number of add-on capabilities (like performance reporting and automated trading) reduces the number of additional pieces of third-party technology that advisors need to buy. At the same time, however, being on a platform that has no existing retail clients means that there are no retail clients on Altruist for advisors to convert or be referred to. And from a client's perspective, having their money at Altruist might actually feel like a 'riskier' proposition, being that it lacks the built-in name recognition of Schwab or Fidelity, and if the client ultimately decides to leave the advisor, they can't simply switch their account to the retail side since there's no retail side to switch to.

And so while Altruist has cemented itself as the #3 custodian, it still has a long uphill climb to even approach the top 2 status of Schwab and Fidelity. Which on the one hand gives it a lot of headroom for growth: With around 15,000 RIAs reportedly on the Schwab platform right now and many thousands more at Fidelity, getting even just a low-single-digit number of firms to break off from the incumbents – well within the range of normal technological 'churn' – could win Altruist hundreds of new firms and billions of dollars of new assets. Which is on top of already winning what appears to be a disproportionate share of newly created RIAs that either don't meet other custodians' asset minimums or have little interest in being a very small fish in a Fidelity- or Schwab-sized pond.

In the long run, however, while it's one thing to win a few percentage points of business away from dominant competitors via the natural level of churn that all platforms experience, it's another thing to actually find a wedge that can effectively peel off larger firms with the bulk of the custodial assets to switch to Altruist – particularly when there is no referral program or retail presence to make Altruist more appealing from a business standpoint. Nonetheless, for the skeptics who initially doubted whether Altruist could even survive among the cutthroat competition for custodial assets, the latest fundraising news makes it clear that they're here to stay (even if it will be some time before they can challenge the #1 and #2 spots).

Archive Intel Raises $1M To Broaden Compliance Archiving Beyond Email And Social To iMessage And (Eventually) WhatsApp

All financial advisors are subject to oversight of their written communications with clients, either in the form of pre-review and approval of any advertising or marketing messages, or after-the-fact archiving and review by firm compliance staff. At a base level, advisory firms are tasked with supervising their employees to verify their compliance with firm policies and procedures, and a key component of that supervision is reviewing written correspondence to catch performance guarantees, misleading statements, or anything else that might raise a red flag for compliance.

The challenge for compliance departments (and by extension, the advisors that they oversee) is that the amount and variety of written client communication have exploded since the advent of computers and the Internet, and keep evolving continuously to this day. When the regulations around supervision of client communication went into effect, the vast majority of advisors' client interactions were non-written, instead happening in person or on the telephone. But as computers began to take over the workplace, more and more communication shifted towards electronic media, beginning with email in the 1990s, continuing with texting and social media in the 2000s, and more recently encompassing a plethora of phone-based messaging apps like WhatsApp, Signal, and iMessage. All of which, despite being a far departure from the typewritten memoranda of the mid-20th century, nevertheless fall under the umbrella of written communication needing to be archived and reviewed (about which regulators like the SEC and FINRA have taken a clear stance that essentially states, "if it can be archived, it must be archived").

From a compliance perspective, the explosion of electronic communications needing to be archived and reviewed almost by definition necessitates a technological solution to store communications as they're sent, and pull them up later for review. Meanwhile, the ever-changing landscape of different electronic communication channels puts pressure on the providers of those solutions just to keep up with the channels that firms are using. Because although compliance departments can in theory limit their advisors' communications to only those channels that the firm's compliance technology can archive and review, the reality is that clients' communication preferences – and advisors' desire to cater to those preferences – can be perilous for firms to ignore, especially if the preferred communication channel for most clients is one that the firm's compliance department isn't equipped to supervise (as recent shown by a series of major fines levied by industry regulators on firms that have failed to properly archive and monitor client communications via messaging apps).

All of which makes it notable that this month, recently-launched compliance technology solution Archive Intel announced that it had raised $1 million in seed funding as it builds what is nominally 'yet another' compliance archiving solution, but more significantly, is built to capture not only traditional channels like email and social media but also popular messaging platforms like iMessage (which is available on the platform now) and WhatsApp (which is not available yet but is reportedly coming soon).

From an advisor perspective, the significance of a solution like Archive Intel that can archive communications sent via messaging app obviously depends on the extent to which the advisor (and their clients) use those apps to begin with. Firms whose clients are comfortable communicating predominantly via email – which may be the case when most of the firm's client base is made up of older generations who prefer email over text or app-based messaging – might be happy with their existing solution if it reflects the preferences of their client base. However, as clients and their communications preferences change, there will be increasing pressure on advisors to adopt solutions that allow them to continue to communicate on their clients' terms – which subsequently translates to pressure on the compliance technology providers themselves, which will need to evolve themselves or else risk being replaced by another solution that does.

But while it sounds simple enough to expect compliance technology solutions to adapt themselves to the ever-proliferating number of electronic communications channels, the reality is that each app or service has its own set of considerations and challenges for the provider's developers to overcome before it can be added to the lineup of approved services: Each app has its own restrictions on the types of data that can be accessed via third parties, and also has its own API for developers to build their code around (and which might be changed without notice, requiring further coding and development resources). Which ultimately raises the specter that compliance archiving will become more and more expensive over time as the number of platforms to be archived – and the subsequent coding and development challenges – continues to proliferate. At which point advisors will need to either accept the higher compliance cost as necessary for doing business, or else start to hold the line with clients on communicating only via the channels that can be most effectively archived – and perhaps charge higher fees for clients who insist on communicating via channels that come with a higher compliance cost.

In the long run, however, since regulators aren't likely to change their stance anytime soon that firms must archive any written electronic communications (and perhaps soon even un-written communications, like video calls, as well), the pressure will remain on compliance technology solutions to keep up with the shifting landscape of communications channels, or risk being replaced by upstarts like Archive Intel that are built to cover all the channels used by RIAs today.

RightCapital Introduces RightRisk Risk Tolerance Tool In An Ominous Sign For Standalone Risk Assessment Software

One of the fundamental rules of investing clients' money is that the risk in the client's portfolio needs to be aligned with their actual tolerance for risk. Which is a best practice both in terms of reaching the client's desired outcome (since when clients take more volatility risk than they're comfortable with they may be more likely to make a poor choice like panic selling during a market decline) but also from a liability and regulatory standpoint: In many cases, an advisor who puts a client in a riskier portfolio than they can handle can be found financially liable for any losses the client incurs as a result, in addition to incurring fines or sanctions from regulators for violating the standards of care due to clients. Because of this dynamic, assessing a client's risk tolerance has long been part of the investment onboarding process for any investment adviser or broker-dealer, and in most cases the client's dollars cannot be invested until the advisor has completed that step.

But despite the fundamental importance of assessing clients' risk tolerance, its treatment by firms over the years has often been as more of an obligatory box to be checked, and therefore a cost to be managed. While the risk of incurring financial liability and regulatory sanction meant that firms couldn't simply ignore risk tolerance altogether, it also didn't generate any revenue for advisory firms, and so the standard questionnaire was usually an internally-developed risk tolerance assessment that was seen as the most cost-effective way of checking that particular compliance box (although some firms turned to more specialized risk tolerance tools like FinaMetrica, which while scientifically validated to achieve a better understanding on the client's actual tolerance for risk, are ultimately more expensive to implement than an in-house questionnaire).

The prevailing view towards risk tolerance as a check-the-box obligation changed fundamentally, however, after Riskalyze came onto the scene in 2011. Though it was at first nominally a risk assessment tool that gauged a client's ability to stay the course through market volatility, Riskalyze's key feature was to highlight whether the client's own portfolio was consistent with their risk tolerance, and whether the portfolio recommended by the advisor would be a better fit. In other words, it gave a clear demonstration of the value that the advisor could provide if they were hired by the client, which led to Riskalyze's astronomical growth not on the strength of its risk tolerance tool alone, but because it turned that obligatory compliance checkbox into a 'sales enablement' tool for business generation – a concept that the company further leaned into in more recent years with its rebranding as Nitrogen and new self-description as a 'growth platform' for advisors.

The success of Riskalyze spawned a proliferation of competitors in the Risk Tolerance category of the AdvisorTech Solutions Map – but because risk tolerance was never truly the core purpose of Riskalyze/Nitrogen (which reflects its current inclusion in the 'Sales Enablement' category), competitors that more resembled pre-Riskalyze 'pure' risk tolerance solutions like FinaMetrica struggled to gain significant traction, since without the sales enablement component, risk tolerance alone still represented an additional (though obligatory) cost to the advisor that could be more effectively managed with an in-house solution.

Which makes it notable that financial planning software RightCapital has now released its own version of a risk tolerance tool, dubbed RightRisk, that uses a psychometrically designed risk tolerance questionnaire (the 13-question Risk Tolerance Scale designed by Dr. John Grable and Dr. Ruth Lytton), which is included in RightCapital's premium and platinum subscription tiers.

As a risk tolerance tool embedded directly in financial planning software, RightRisk will likely be especially attractive to its user base of planning-centric advisors, for whom the financial planning process typically precedes any investment of client assets, and who can now fit risk tolerance seamlessly within that process on the same platform as the advisor's other core planning tools. And while RightRisk's assessment isn't groundbreaking in and of itself – the Grable & Lytton scale has been widely used throughout the industry since its introduction in 1999 – the close proximity of risk tolerance to the financial planning process makes it arguably easier for advisors to apply the results two-dimensionally, i.e., to frame the risk tolerance discussion in terms of not only the level of risk that the client is willing to take, but also the level that the client needs to take in order to achieve their goals.

And so from an industry perspective, RightRisk puts newfound pressure on an already challenged field of standalone risk tolerance assessment tools, since RightCapital users who employ other tools like PreciseFP, DataPoints, or FinaMetrica for risk assessment purposes can simply choose to use RightRisk at no additional cost to what they're already paying for the financial planning platform. Which represents yet another instance of RightCapital taking a function for which advisors previously paid for a standalone tool – e.g., for one-page financial plans, client visualization tools, and now risk tolerance – and building it directly into its own software, leaving one to wonder what they plan to bring in-house next. Retirement income guardrails? Tax return analysis? Or maybe its own Nitrogen-esque sales enablement tool? At this point, almost anything seems possible.

Ultimately, however, the launch of RightRisk highlights that while risk tolerance can be used as part of a sales conversation (as proved by Riskalyze/Nitrogen), for most advisors it remains a part of the investment and/or financial planning process, where it's both necessary for regulatory purposes and a best practice for achieving good client outcomes. And from that perspective, it makes the most sense for risk tolerance to be integrated within the existing systems advisors are already using – either financial planning software for planning-centric advisors, or digital onboarding/portfolio management software for investment-centric advisors – rather than having to buy a separate standalone solution.

Couplr Partners With American College Of Financial Services To Provide AI-Driven Lead Generation  - But Will It Attract Enough Leads To Be Worth It?

One of the odd paradoxes about the financial advisory industry is that while in the aggregate there is more demand for financial advice than there are advisors to supply it, it can still be an enormous challenge for any individual advisor to find new clients. On one side there are huge, name-brand firms with the budget to advertise on TV and magazines, and on the other is a sea of small, independent firms vying for clients' attention – and so while there will always be consumers looking to hire an advisor, the chances are still very low that they will hire any particular advisor.

In recent years, the challenge of attracting clients has led to the emergence of a number of lead generation platforms, which promised to solve the challenge of finding prospects by attracting consumers who were looking an advisor to hire, and then serving them up to advisors who had signed up to be listed on the platform (in exchange for a fee, typically either in the form of a monthly or annual listing fee, a flat per-prospect fee, or a percentage of revenue from converted clients). The caveat, however, is that clients don’t necessarily want to just hire the first advisor who shows up on their screen: they want to be assured that the advisor can be trusted to solve their problems, which may be varied and unique enough that only a small subset of advisors really represent a good fit, and of those advisors there may be fewer still whose personality and communication style mesh with the client's own so that they're actually comfortable with working together. Which is incredibly difficult for any consumer to ascertain just by looking through profiles of advisors online and trying to pick the right one(s) to explore with further.

And so the twofold problem of lead generation platforms has been not only how to acquire a steadily growing number of consumer leads, but also how to most effectively match each particular lead with the 'right' advisor for them (improving the experience for the consumer, and the likelihood of conversion for the advisor). Historically, lead generation platforms have tended to focus more on the problem of simply bringing in enough leads in the first place, than that of matching them effectively with advisors – relying instead on simple criteria like ZIP code (for consumers to find a "local" advisor) and asset minimums (to ensure the advisor won’t reject the prospect) to dictate which leads were served to which advisors – and as a result, the most successful firms on those platforms were generally the ones that were big enough to serve any type of client (especially if they had multiple locations to cover multiple ZIP codes) and simply needed the raw number of leads to keep the growth machine running.

However, the matchmaking problem does still exist, and as the rise of increasingly niche-focused advisory firms in recent years has shown, there is a nontrivial number of consumers who are more likely to hire an advisor who solves for their specific need, whether that be planning focus, industry or profession, or general interests and affinity. And so Couplr, a technology solution founded by financial advisor Derek Notman that matches clients with advisors using what it describes as an "AI-driven matching engine", has sought to fill the void by leveraging data science to improve the fit between lead-generation clients and advisors. In other words, Couplr has 'decoupled' the marketing and advisor-matching functions of lead generation, providing the advisor-matching 'guts' on an outsourced basis to advisory firms that would otherwise need to hire a business development staffer to handle the screening and matching of inbound clients to advisors, and/or to platforms that want to go beyond the standard ZIP code/asset minimum criteria to ensure a better fit between prospects and advisors but but don’t have the capabilities to do so internally.

In this vein, it's notable that Couplr this month announced a partnership with the American College of Financial Services, which provides a number of designations for financial advisors (including the ChFC, RICP, and WMCP designations) and has plans to launch a find-an-advisor platform for its designees (similar to CFP Board's "Find a CFP Professional" platform for its certificants). With the idea being that the American College will leverage its brand and reach to bring consumers onto the platform, while Couplr will provide the technology to match those consumers with advisors using client and advisor criteria (and its own data-science secret sauce).

On the one hand, the partnership makes sense, as advisors struggle with organic growth, the CFP Board's "Find a CFP Professional" platform is popular with advisors (even if actual results for any particular advisor have been limited, per Kitces Research on Advisor Marketing), and the American College has the opportunity to seek to build a consumer presence and wider brand recognition for its own designations. Bringing in clients for American College designees also incentivizes advisors to keep those designations, and may perhaps convince more professionals to pursue American College designations like the RICP as a supplement to CFP certification to ‘also’ get access to their new find-an-advisor platform. And for advisors who opt into the American College's find-an-advisor tool, Couplr's technology provides the opportunity for more efficient business development by providing better-quality leads – and thus requiring fewer resources to screen out the poor-fitting leads – than traditional lead generation services (at least for the subset of advisory firms whose problem is too many poor-fitting prospects rather than simply too few prospects at all).

On the other hand, the real question is how many prospects American College can generate for its designees via a find-an-advisor platform offering in the first place. The CFP Board supports its "Find A CFP Professional" platform with a $160/advisor surcharge for its public awareness campaign – which amounts to nearly $16M/year, that it pours into marketing the CFP marks to consumers, and has for more than a decade every year since its public awareness campaign started. And even then, relatively few CFP professionals say they have even gotten more than a client or two (if any) from the service. Is the American College really prepared to invest enough into consumer marketing (or raise its re-certification fees on existing designees enough) to generate real results?

From the Couplr perspective and AdvisorTech more broadly, though, the remaining question is just how big the market is for platforms or firms that already have a large and reliable flow of prospects where the only 'problem' is matching too many prospects with too many advisors… rather than simply attracting prospects to begin with, which has long been the primary challenge for both advisory firms and lead generation platforms. And if the market for Couplr as an outsourced client-matching technology is too small, it may face the choice of whether to sell to an existing platform that wants to bring its technology in-house, or to transition into a lead generation platform itself – which while being a tempting business opportunity by the economics of earning lifetime percentages of revenue from client fees, is also very capital-intensive to build and sustain in order to bring in a steady flow of prospects (and remain afloat for several years until the recurring revenue from its converted prospects actually becomes profitable).

The biggest unsolved question, however, is simply whether a standalone find-an-advisor platform that asks consumers questions to match them to the ‘right’ advisor is really something that consumers want or need, since the service that by far the most consumers go to first when looking for a financial advisor today is Google. In other words, will improving the matchmaking function of lead generation attract a critical mass of users on both the client and advisor side such that advisors see a steady flow of well-matched prospects and prospects can reliably filter down on their needs enough to find an advisor who would be a good fit? Or do search engines do at least a 'good enough' job of leading prospects to advisors that are the right fit for them – by searching through the website of every financial advisor in the country, as Google already does – that there simply isn't demand for a standalone service, no matter how good its matching function? Time will tell, but it at least appears that Couplr is betting it has the technology to make lead generation more reliable, and thus more relevant, for consumers and advisors (at least for those whose problem is that they have ‘too many’ leads in the first place and need a way to filter them down more efficiently and effectively).

XYPN AdviceTech Competition Applications Open To Emerging AdvisorTech Providers

Tech startups for financial advisors have a uniquely difficult challenge in navigating the road to success. Elsewhere in the world of fintech, most solutions are direct-to-consumer, which means they have the opportunity to reach literally hundreds of millions of Americans, or billions of global consumers, meaning that getting 'just' 1% market share can equate to millions of users of which only a small percentage need to be monetized to have a viable product and positive cash flow. But the addressable market for financial advisors is fundamentally different: There are 'only' 300,000 or so advisors according to Cerulli, and arguably only a fraction of those are in the 'advice' business with just over 100,000 CFP certificants, and of those a sizeable proportion work for large enterprises where tech decisions are made from the top or built in-house – leaving only a small pool of independent RIAs (likely number in the tens of thousands) who can be early adopters that can build traction for a new tech solution. And on top of everything else, the majority of these independent firms have just 1 to 5 employees, meaning that growing an advisor software company often happens literally one customer at a time.

The result is that startup AdvisorTech firms face two similarly unappealing paths. Either they can hunt for the 'elephants' by trying to land large enterprises with large headcounts of users which could immediately bring a critical mass of revenue, at the risk that the software provider runs out of cash and folds before they can find and close a sale of the requisite size. Or else they provider can pursue small and independent RIAs, where the good news is that the firm owner, decision maker, buying unit, and end user are often the same person – but with the caveat that finding and selling to one user at a time can result in an excruciatingly long path to sustainability, especially in an environment where the average advisor only changes the units of their tech stack every 10-15 years.

Either way, startups often die on the vine because they can't get a critical mass of users at a time when it's still hard to reach advisors one-on-one, and the traditional one-to-many paths like conferences are effectively crowded out by asset managers and advisor platforms who are willing to buy conference booths at high rates that are inaccessible to the typical SaaS provider (since their typical bps fee model means that even one new client who signs on at a conference can result in millions of dollars in new assets, and thousands in new revenue, whereas the typical AdvisorTech solution charges in the range of $100-$300 per month, requiring many more new clients to justify the cost of a typical exhibitor booth).

Recognizing this dilemma for startup AdvisorTech providers, XY Planning Network launched its inaugural AdviceTech competition in 2016 with the goal of helping emerging AdviceTech solutions to become 'discovered', and leveraging XYPN's user base that new numbers over 1800 independent advisors/RIAs, all of whom are focused on advice and readily positioned to become early tech adopters (with an average age of 40, meaning many years ahead to try out and implement new software tools) to give new companies an opportunity to show their wares at no cost and gain initial traction. In its first 8 years the AdviceTech competition debuted a number of today's emergent tech providers, including 2016 winner Snappy Kraken, 2017 winner Vestwell, 2019 winner Holistiplan, and 2022/2023 winner Income Lab. (Other finalists have included Altruist, Pulse360, Bento Engine, College Aid Pro, and other notable names on today's FinTech map).

This month, XYPN has announced that applications are now open for its annual AdviceTech competition to take place at its annual convention in Minneapolis in October. Notably, the competition is uniquely focused on emerging companies, which means first and foremost they need to be focused on the advice part of the process (not necessarily just insurance or investment product sales), and they actually need to be new or emerging solutions (defined as less than $1M of revenue, launched in the last 12 months, or being a substantively new offering from an existing company that is separately offered for its own standalone price). The first deadline for application submissions is July 12.

For advisors, XYPN's AdviceTech competition is a particularly appealing way to see the industry's newest emerging technology, appealing to that subset of financial advisors who like to be early adopters and enjoy trying out tech on the bleeding edge. It can also offer advisors a glimpse of where the industry is going: because XYPN doesn't charge exhibitor fees to participate in the competition, it's able to showcase the newest of new startups that can't afford to exhibit in the traditional way rather than those that are already dominant in the industry.

In the AdvisorTech industry at large, AdviceTech competitions like XYPN's can also become an appealing opportunity for potential sponsors (e.g. VC and PE firms, along with strategic acquirers) to spot emerging technology that they may want to invest into or even acquire someday in the future. Which feeds a positive growth loop for the industry: More visibility for emerging technology to an audience of early adopters, sponsors, and acquirers fuels a cycle of user growth and investment, and ultimately the possibility of acquisitions/exits that further fuel the cycle of innovation.

With the AdviceTech competition in only its ninth year, it still remains to be seen if these types of competitions really do help spur innovation and success of startups in the AdvisorTech space in the long run. If the success of early winners of XYPN's competition is any indication, however, it really does appear that giving high-quality emerging AdvisorTech solutions a chance to prove themselves can really change the shape of the advisory industry – if only they get the opportunity to be seen in the first place.

Here Come The AI Meeting Note Tools!

Although it feels like an eternity ago, it's been barely 1 1/2 years since the public debut of ChatGPT, which took the world by storm and achieved the fastest-growing user base of new software in history in late 2022 and early 2023 by giving everybody the experience of what it was like to ask a computer questions and have it respond with what sounded like intelligent and thoughtful answers. Almost immediately there were questions about the implications of ChatGPT for financial advisors – since if you could just ask a computer how to plan for retirement that it can draw from its 45 terabytes of training data to answer in a clear and understandable way, why would you pay a human advisor for the same task? – but it soon became clear that although ChatGPT was impressive, it was by no means perfect. For one thing, ChatGPT and Large Language Models (LLMs) of its ilk lack the deep knowledge in specific domains of human subject matter experts, making them less useful for anything deeper than surface-level questions; for another, LLMs proved prone to 'hallucinations' where a seemingly intelligent answer turns out to be completely made-up (as, for instance, some attorneys found out when they were sanctioned for submitting a ChatGPT-generated legal brief containing fictional legal citations).

More recently, the hype around ChatGPT and AI tools and general has largely shifted from proclamations that AI will replace all knowledge-based professions to focusing more directly on use cases based on what the AI tools are actually good at. Namely, while they can't necessarily create a financial plan or client email from scratch (or at least one that an advisor wouldn't want to review and edit carefully themselves before sending), they can do a good job at generating alternative text or interpretations of an existing block of text; e.g., a large document or conversation that the user wants to summarize and pull out key information from without reading the entire thing. In the financial advisor context, the most common place where lots of language occurs is in conversations with clients – e.g., prospect meetings, plan presentations, and annual reviews – and advisors tend to do a large amount of grunt work around preparing for and following up after these conversations, with Kitces Research on Advisor Productivity showing the average advisor spending 1 hour each for meeting preparation and follow-up for every hour spent actually meeting with clients. In other words, the opportunity is ripe for a tool that can help advisors process and distill planning documents and conversations – e.g., scanning planning materials to create a meeting agenda, processing meeting transcriptions to generate written notes to be loaded into CRM, and composing the all-important client follow-up email with key points and action items automatically derived from the conversation – which is a job that seems tailor-made to the current abilities of LLM-based tools.

In the past few months, a bevy of new AI-for-advisors solutions have emerged to solve for client meeting notes and the subsequent functions that occur around every client meeting. The last two years alone have seen the debut of startups like Finmate.ai, Jump, Vega, Filenote.ai, Zocks, and FieldKo – and that's on top of the nonspecialized, general-purpose AI meeting note software like Fathom, Otter, Fireflies, and Zoom's built-in AI meeting summary tool. Which while giving advisors no shortage of options to choose from, also creates the dilemma of which meeting notes tool to use, since realistically advisors may only be able to test and demo 1–2 solutions before choosing one to go with – while in the meantime, the technology itself is changing so fast that today's inferior solution could become next year's category leader. With such a fast pace of change it seems most practical to re-evaluate and change software if necessary once every 12 months or so, which is practically the blink of an eye for an advisor who is used to changing their software tools only once every 10–15 years.

Still, the sheer amount of time spent around meeting notes and follow-up, multiplied by hundreds of client meetings per year for even a 'small' advisory firm, creates a bona fide opportunity for a good client meeting notes solution, and in general, AI seems well suited to do the job cheaply and effectively. The question of which tool prevails will depend both on the quality of the AI itself – i.e., which tool actually does the best job of capturing and transcribing spoken conversation, recognizing context and idiom and all the nuanced information that can come from sentence fragments and nonverbal utterances – as well as which tool does the best job of connecting that information with where it needs to go, e.g., loading the meeting notes into CRM, archiving recommendations for compliance purposes, and generating follow-up tasks for advisory firm staff. Ideally (though this isn't a reality yet), the software will be able to go beyond 'just' the meeting notes and into the actual post-meeting action items – for example, when advisor says they will send the client the paperwork to open a Roth IRA, the AI immediately kicks off the appropriate workflow so the application is ready before the meeting is over. The biggest question is to what extent advisors will want to fully automate those processes, given that the technology will always have limitations that necessitate guardrails to avoid a "Sorcerer's Apprentice" scenario where it mindlessly repeats the wrong action with disastrous results.

In the long run, however, AI seems well poised to do what other technology booms (like the rise of the Internet and electronic communication, and more recently the robo-advisor movement) have similarly promised to financial advisors: To winnow down the amount of back-office support needed by reducing the staff hours needed to complete inefficient (but necessary) actions. The question remains about how many years it will take for actual AI solutions to live up to their implied promise – because at the end of the day, advisory firms and client needs are complex, and although the technology is catching up, it's still a tall task to distill those needs into executable software code.

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In the meantime, we've rolled out a beta version of our new AdvisorTech Directory, along with making updates to the latest version of our Financial AdvisorTech Solutions Map (produced in collaboration with Craig Iskowitz of Ezra Group)!

So what do you think? Is it problematic for RIA custodians to have retail platforms that can theoretically compete with their own RIAs, or do the benefits outweigh the potential for conflict? Are clients eager enough to communicate via iMessage or WhatsApp to make it worth changing to a compliance service that can archive them? Do AI meeting notes tools live up to their promises about the time they can save in meeting prep and follow up? Let us know your thoughts by sharing in the comments below!