RightCapital Introduces Prospecting Tool For Narrower Financial Plans (And More Of The Latest In Financial #AdvisorTech – September 2025)

RightCapital Introduces RightExpress To Expedite (Limited) Planning For Advisors To Demonstrate Their Value To Prospects

One of the challenges for financial advisors with converting prospects to clients is in demonstrating the advisor's value in a tangible way. An advisor can talk about their own expertise and what sets them apart from the advisor down the street, but in the spirit of "show, not tell" it can be much more powerful to have a concrete example of the advice the client might expect to receive. This is essentially the aim of proposal generation and sales enablement tools like Riskalyze and VRGL, which work broadly by comparing the prospect's current investment portfolio to the advisor's proposed portfolio and highlighting the differences between the two in areas like risk, diversification, fees, etc. Ideally there will also be some quantifiable metric (e.g., Riskalyze's Risk Score and VRGL's 5-pillar analysis) that clearly shows how the advisor's version is better.

But while proposal generation tools might work well at demonstrating value from an investment management standpoint, financial planning-centric advisors often prefer a planning-centric way of showing their value, i.e., something that demonstrates how the advisor will help the client achieve their overall financial goals, rather than solely focusing on their portfolio. The traditional way of doing this has put together a full initial financial plan for the prospect, showing how the client can stand to benefit from the advisor's recommendations in terms of overall net worth, cash flow, taxes, etc.

However, there are two main drawbacks to creating a full financial plan upfront. First, creating a comprehensive financial plan can be incredibly time- and resource-intensive, taking an average of 16 hours or more of team time according to 2024 Kitces Research on Advisor Productivity – which is a lot of time to spend on planning for a prospect who isn't even guaranteed to become a client.

The second issue is that delivering an entire comprehensive financial plan might actually be overkill for the purposes of demonstrating the advisor's value to a prospective client. People don't generally go to financial advisors because they want a comprehensive financial plan; more often, they go because they have a specific problem or concern that needs addressing. An advisor likely doesn't need to go through the work of putting together an entire financial plan if they can show the client how they'll help solve their most pressing problem. As a bonus, a plan focused on the client's main pain point will show the client that the advisor really does listen to and understand what's most important to them, establishing not just their expertise but their ability to develop a trusting relationship.

In this context, it's notable that RightCapital has recently added a new feature called RightExpress, which allows advisors to create targeted, topic-specific planning deliverables for areas such as Social Security, retirement, debt planning, and risk management. Each area is essentially a streamlined version of RightCapital's full financial planning module for that topic, which makes it possible to upgrade the prospect's RightExpress plan to a regular RightCapital plan once they become a client, without having to duplicate the data entry for that area (in contrast to, for example, MoneyGuide Pro's MyBlocks, which similarly provides topical financial planning modules but doesn't integrate directly with MoneyGuide's core financial planning software).

On one level, it's reasonable for RightCapital to release a more prospect-friendly version of its software, which doesn't require the intensive data gathering and analysis of a full financial plan. As platforms like Riskalyze and VRGL have shown, demonstrating an advisor's value doesn't necessarily require a full report with all the bells and whistles – there just needs to be a clear way to highlight how the client can benefit from the advisor's recommendations. If that can be done while targeting the client's specific pain point, it can potentially have as much (or even more) impact than a full financial plan, while taking a small fraction of the time to prepare.

But at the same time, RightExpress represents a notable change in direction from RightCapital, which has consistently leaned further into going upmarket with more sophisticated and complex planning tools over the years while avoiding the mini-trend of 'simplified' planning tools such as MoneyGuide's MyBlocks or eMoney's Foundational Planning module. The strategy has largely worked out for RightCapital, which in the newly published 2025 Kitces Research on Advisor Technology gained market share from eMoney and MoneyGuide and had the highest satisfaction ratings among financial planning software tools. It seems curious, then, that RightCapital would introduce an "express" version of its software despite the evidence that planning-centric advisors have largely shunned "simplified" financial planning tools.

The key question, then, will be how well RightExpress can strike the balance between expediting the planning process for prospects enough to save meaningful time for the advisor, and producing detailed planning deliverables that actually do a good job of highlighting the advisor's value. If RightExpress's streamlined data entry and workflows sand down too much of the detail and analysis from the plan, advisors might find it too limited to be of any use for demonstrating their planning expertise. On the other hand, if it turns out to be just as detailed as what would be included in a comprehensive financial plan – only limited to one or two planning topics instead of the full scope of the client's financial situation – it might reveal enough of the advisor's 'real' planning value to be of real use in converting prospects. Or put differently, the success of RightExpress might depend on whether it aims to provide simplified planning (which hasn't proven popular with advisors), or if it's instead just a narrower version of the planning that advisors already do (which could actually help advisors demonstrate their value more efficiently)?

Altruist Introduces Basis-Point Custody Subscription Model, But Isn't (Yet) Fully Embracing Fee-Only

It's notoriously difficult for RIAs to determine how much revenue their custodial platform earns from their clients (i.e., what clients are actually paying) in exchange for the services that the client (and the advisory firm) receive. Custodians make money in a variety of ways, ranging from spreads on cash sweeps to mutual fund revenue sharing to payments for order flow to margin and securities-based lending interest and beyond, none of which are itemized on a statement or otherwise readily apparent in any way to advisors or their clients. And the amount of custodial revenue can vary wildly from one client to another: A client who has a high cash balance, invests in mutual funds, and borrows money against their securities can be very lucrative to the custodian, while one who keeps minimal cash in their account, uses ETFs, and doesn't borrow anything can be worth next to nothing in terms of custodial revenue. Which means that the more-productive clients effectively end up subsidizing the less-productive clients on the custodian's platform, even though they may both be getting the same level of service. And similarly, the advisors with more-productive clients end up subsidizing the advisors with less-revenue-productive clients on the custodian's platform, even though the firms may also be getting the same level of service.

In recent years, many advisors have gotten better at figuring out custodians' sources of revenue, and have subsequently taken steps to minimize the ways that their clients generate revenue for their custodial platforms. This has resulted in fee compression and shrunken margins for custodial platforms; for instance, Charles Schwab's revenue from Advisor Services shrank from $4.9 billion to just over $4 billion from 2022-2024, even as its total client assets grew from $3.2 trillion to nearly $4.4 trillion – a decrease in total revenue yield from 15.5 bps in 2022 to 9.2 bps in 2024. And while Schwab is unique among major custodians in reporting its revenue numbers (since it must do so as a publicly traded company), the phenomenon is by no means limited to Schwab, as recent developments from the 2023 acquisition of Shareholder Services Group (SSG) by Altruist and the 2024 acquisition of TradePMR by Robinhood, to Fidelity's reported push to encourage advisors on their platform to use more Fidelity funds that generate more revenue for Fidelity, highlight the need for smaller custodians to align with bigger platforms to stay alive.

The irony is that custodians could avoid this cat-and-mouse game, while also earning enough revenue to profitably serve clients on their platform, if they simply charged a transparent custody fee for client assets (and advisors to service them on the custodian's platform). Rather than employing numerous opaque and indirect methods of revenue generation which advisors inevitably seek to identify and minimize – as many view as being part of their fiduciary duty to ensure their clients are paying reasonable expenses for investment management – a simple basis points-based fee for all clients would help to ensure that each client is effectively paying the same amount for the same level of service, while incentivizing custodians to pay better rates on cash and potentially lowering the cost of on-platform mutual funds (since asset managers have to lift their own expense ratios to have the dollars available to forward some of that cost on to the custodian in the form of revenue sharing payments).

Which is why it's notable this month that Altruist has announced the launch of Altruist One, a basis points-based subscription model for its custodial and advisor technology platform. For 12 bps per year (a mere 0.01% per month!?), clients of Altruist one get access to higher rates on cash products (4.25% APY on high-yield cash accounts and 2.0% for sweep accounts versus 4.0% and 0.2% respectively for non-Altruist One clients), $0 transaction fees on most mutual funds (including Vanguard funds, which traditionally come with higher ticker charges since they don't pay revenue sharing to custodians), Altruist's automated tax loss harvesting suite (which itself normally costs 10bps per year), and discounted fees on portfolios in its Model Marketplace. Altruist also plans to add automated cash allocation levels, asset location optimization tools, direct indexing, and lower-interest margin investing to the list of Altruist One features.

Notably, Altruist had already been experimenting with basis point-based fees for various add-on features of their platform: Purchased on their own, the tax loss harvesting tool alone costs 10bps per year, while the marketplace models have a range of different basis point fee schedules (as it typical for asset management solutions). However, while Altruist will be trading off some of its margins on cash accounts and transaction fees to simply earn its revenue with a custody fee, it will still have other ways of earning indirect revenue from Altruist One clients, namely fully paid securities lending and payment for order flow. In other words, Altruist one isn't truly the "holy grail" of a pure "fee-only" custody model, where all of the custodian's indirect revenue sources are replaced by a single, transparent subscription fee. Rather, it's more of a bundled package of Altruist's existing add-on features (i.e., tax loss harvesting and the model marketplace), with extra benefits (i.e., better cash rates and lower transaction fees) thrown in as an added incentive.

Which raises the question of whether it's worth it for advisors (or their clients, whom advisors have the option of passing the Altruist One fee to) to spend 12bps per year for a combination of bundled technology and asset management, plus incentives on cash and lower transaction fees. The tradeoff could net out well for advisors who already use Altruist's tax loss harvesting and/or model marketplace, for whom the 12bps bundle would be a reduction from what they're paying now. It could perhaps also benefit clients with big cash balances for whom the boost in cash yields would make up for the 12bps fee on all of their on-platform assets. But for advisors and clients simply looking for a pure basis points for custody model (and pay for access to ‘superior' lower-cost products on the shelf that typically come with an upfront fee), Altruist has yet to fully meet that standard. And in fact, by making Altruist One an optional subscription package, Altruist may end up losing out on the deal by having clients with high cash balances – who would have generated more revenue for Altruist under the traditional model – opt into Altruist One, while those with little or no cash (who make Altruist relatively little money) stay where they are. More generally, this means that Altruist One still leaves advisors and their clients with a potentially confusing choice between options, and advisors who ‘play the game' well could leave some clients and advisors paying substantially different amounts for the same core set of services from Altruist (to Altruist's detriment).

That said, it's at least notable that Altruist has begun to dip a toe into the bps-for-custody waters, while its biggest competitor Schwab has so far resisted charging direct fees for custody and Fidelity reportedly charges platform fees only to advisors who don't meet its asset minimums. (Interestingly, the other Big 3 custodian, Pershing, has recently introduced a new bps-based custody fee that it will charge "some" RIAs on its platform but not necessarily all of them, creating similar challenges to Altruist in that it risks having ‘profitable' advisors under the traditional model choose the custody fee alternative, while those who are the least profitable under the traditional model simply stay there and cause the custodian to lose money.)

In the end, though, it seems inevitable that custodians will move increasingly towards charging fees for custody. If only because advisors have been systematically dismantling the traditional custodial business model by managing their clients' money to minimize the amount of revenue earned by their custodians, and the simple reality is that custodians need to earn some revenue to stay in operation. While it may be slow in coming (since after all it requires restructuring the entire business model of the multibillion dollar custodial industry), it's clear that the momentum is starting to shift towards upfront custodial fees and, hopefully, more transparency if not outright lower combined (direct and indirect) costs for clients on RIA custodial platforms.

TaxStatus Launches An Enterprise Lead Generation Platform To Qualify Incoming Prospects With IRS Tax Data

There are a lot of ways financial advisors can use information from their clients' tax returns. Return data can unveil key details about clients' financial lives (for advisors who know where to find them), from income sources to the nature of their investments to the contours (if not the full details) of their net worth. Tax returns can help spur tax planning conversations as well, with information from the current return serving as the base case against which advisors can test different scenarios such as Roth conversions, charitable giving strategies, and capital gain (or loss) harvesting strategies. And because few clients tend to even know what's in their tax returns beyond their tax due or refund receivable at the end of the year, advisors can add value by providing a high-level summary of the return to give the client more awareness of their tax situation.

Holistiplan is arguably the best-known technology platform for using clients' tax return data for tax planning, since it was the first to offer the capability to upload and scan returns and automatically pull out the key information for summarization and planning purposes. Today, other tools like FP Alpha and RightCapital can similarly "read" uploaded client tax returns for planning purposes. But more recently, TaxStatus has emerged as a player in the tax planning domain with the unique feature that instead of scanning an uploaded copy of the client's tax return, the software can (after the client gives permission) pull the client's tax return data directly from the IRS's electronic records. Which means one less data gathering obstacle for advisors in the planning process (since once the client gives permission, TaxStatus will automatically update with the most recent return data), while also giving the advisor access to historical data showing how the client's situation has changed over time. TaxStatus compiles this information into a "Financial Baseline Report" summarizing the client's income sources, account types, loan information, and other useful nuggets of tax information for planning purposes.

And so it's notable that this month, TaxStatus has announced a new "TaxStatus LeadGen" solution that it is rolling out to enterprise advisory firms, expanding the use of IRS tax data from planning into the prospecting realm.

The goal of TaxStatus LeadGen is to provide advisory firms with leads that come with a trove of data from their IRS records, with the key idea being that the IRS data will result in a more complete and accurate picture of the prespect's financial situation than if the prospect simply self-reported their own information. The process would begin with a prospective client filling out the form to give their name and contact information and provide permission to share their IRS data with the advisor. Next, the advisor receives a report with key information gleaned from the prospect's tax data, including income, asset and business ownership information, and employment history. All of which can help give the advisor a relatively complete view of the client's financial picture – and potentially a good idea of whether they would meet the advisor's asset minimums or otherwise be a good fit for the advisor's services – before they even pick up the phone for an initial call.

That said, the biggest question about TaxStatus LeadGen is how it will generate a reliable flow of prospects for advisors to realize the benefits of their IRS-sourced data. Most lead generation services work by drawing in prospective clients to a single place (e.g., by content marketing such as SmartAsset and NerdWallet's platforms or SEO and advisor ratings such as WiserAdvisor and Wealthtender) and referring them out to advisors in their network. In contrast, TaxStatus LeadGen is built to run off of advisory firms' existing marketing channels, which means that the firm needs to already be effectively drawing in prospective clients in order for its solution to be of any use. LeadGen's role, then, seems to be less about generating new leads than it is about enhancing the information collected for prospects that are already reaching out to contact the advisor. Which is why it makes sense that the offering for now appears to be limited to enterprise-scale firms, whose branding and marketing power means they don't typically have any issues attracting new prospects but can run into problems with efficient screening for qualified prospects. Still, even though the idea works in theory, one wonders how many prospective clients might not feel comfortable giving permission to share their IRS tax data with an advisor they haven't hired yet.

The key point, though, is that there are use cases for collecting tax data that go beyond just serving existing clients, and that are enhanced when the data can be streamed directly from the IRS (provided that the client is comfortable with allowing the advisor to do so in the first place) rather than handed to the advisor in paper or PDF form. TaxStatus has an inherent advantage for those use cases, having already built out the data feeds between itself and the IRS. Which makes it worth wondering if (or when) other tax planning platforms like Holistiplan or FP Alpha will build out similar data feeds to compete more directly. If TaxStatus LeadGen really does turn out to have a demonstrated impact on prospecting, it seems likely that its competitors could follow suit to further enhance their own value propositions.

FMG Suite Acquired By GTCR As It Looks To Continue Its PE-Backed Acquisition Of Advisor Marketing Tech Solutions

Technology can have many uses in advisor marketing, from the top to the bottom of the sales funnel. Prospecting platforms like Catchlight, FINNY, and Aidentified can help advisors identify and reach out to prospects who could be a good fit for their services. Lead generation platforms like SmartAsset and Wealthtender can enhance inbound marketing, taking prospects who are already interested in hiring an advisor and matching them with advisors users of the platform. Digital marketing platforms like FMG Suite, Snappy Kraken, and AdvisorStream can help to automate content creation and distribution across channels like email, blogs, and social media. And sales enablement tools like Nitrogen/Riskalyze, VRGL, and Exhibit A can help advisors make their final pitch to prospective clients by generating proposals and helping advisors demonstrating their value proposition.

But despite the sheer number of use cases for technology in business develop, most of the individual technology providers live separately from one another in an advisor's tech stack. Which has to do at least in part with the wide variation in sales and marketing techniques used by advisors: For example, advisors who lean heavily on outbound prospecting aren't likely to also use inbound lead generation, and vice versa (while still others might rely more on social media content or referrals, and need neither prospecting nor lead generation tools). Unlike other areas like investment management where a handful of providers seek to serve as a single end-to-end solution (e.g., Orion, Envestnet, or Advyzon), most marketing and business development tools stay relatively narrowly focused on a single specialty.

The exception to this rule, however, has been FMG Suite. With its roots as a provider of advisor website templates focused primarily on the enterprise broker-dealer market, FMG Suite has now been on a nearly decade-long spree of private equity-backed acquisitions to expand its scope and user base. There were essentially two phases in this expansion: First starting in 2016, when under its original private equity backer K1 Investment Management FMG Suite bought competitors including Advisor LaunchPad and marketing automation providers Agency Revolution and MarketingPro. Then, after K1 sold FMG Suite to fellow PE firm Aurora Capital Partners in 2020, FMG Suite began a string of higher profile acquisitions, including website provider Twenty Over Ten in 2020, content marketing platform Vestorly in 2022, and client texting platform MyRepChat in 2023. All of which has resulted in FMG Suite becoming what is today one of the only – if not the only – self-proclaimed "all-in-one" digital marketing solutions for financial advisors.

It's notable, then, that after five years under Aurora Capital Partners' ownership, it was announced this month that FMG Suite is being acquired by yet another private equity firm in GTCR.

Prior to this most recent acquisition, FMG Suite was already the closest thing there was to a digital marketing rollup in advisor technology. Its private equity backing has allowed it to grow through acquisition from what was focused mainly on websites to eventually encompass email, social media, event promotion, and texting (including templated messages, scheduled text, and auto-replies) while increasing their focus on RIAs in addition to their original core user base of broker-dealer enterprises. And that expansion seems likely to continue now with FMG Suite getting fresh capital under its new owners to fuel even more acquisitions.

Which makes it more than likely that we'll see more news about one or more of the smaller advisor marketing and business development technology providers on the market being snapped up by FMG Suite in the near future. That could be in an area where FMG Suite has yet to make any acquisitions, like AI-driven prospecting (such as Wealthfeed, FINNY, or Wealthawk), proposal generation (like VRGL, Elements, or Capintel), or marketing and communications compliance (like MessageWatcher or Compliance Approved). Or alternatively, FMG Suite could make more acquisitions of adjacent digital marketing platforms – perhaps even including its main competitor Snappy Kraken.

It should be noted that FMG Suite's string of acquisitions has come at no small cost to the satisfaction of its users, with FMG Suite scoring the lowest in satisfaction among digital marketing providers despite having the highest rate of adoption in the most recent Kitces Research on Advisor Technology. Which may be at least in part due to the platform's rapid expansion over the years: With so many different parts cobbled together over time, it can be difficult to make them perform as a well-functioning whole (a lesson also learned by platforms like Orion and Envestnet, which similarly grew by acquisition only to struggle to integrate everything together and subsequently suffer from low user satisfaction). To that end, then, FMG Suite could also deploy some of its fresh capital to improve the integrations and quality of its existing technology (or acquire more modern tools to integrate into its own offerings that would improve its user experience).

The bottom line is that FMG Suite's change in ownership is likely to signal less of a shift in direction than a continuation (and even amplification) if its current focus on growth through expansion. Smaller tech firms, and even bigger ones like Snappy Kraken, could see their phones ringing in the near future as FMG Suite seeks to put its new capital to work – but time will tell if the result will be an even more disparate (and potentially unwieldy) collection of tools, or a more modernized and streamlined version of the technology that FMG Suite already features.

FINNY Launches Enhanced AI Prospecting Features, But Will It Entice More Advisors To Adopt Outbound Prospecting?

Outbound prospecting has always been a part of building a career as a financial advisor, from the early product sales-centric roots of the profession when advisors needed to always be closing to earn their next commission all the way to the present when, even though advisors skew towards the ongoing advice-based model, they still often need to search proactively to find their earliest clients. But while many advisors engage in some kind of outbound prospecting at the beginning of their careers, few tend to stick with it voluntarily: According to the most recent Kitces Research on Advisor Marketing, fewer than 5% of advisors engage in cold prospecting, and those who do have a poor view of its effectiveness.

It's not hard to imagine why most advisors don't do outbound prospecting. Few people enjoy calling up someone unsolicited to ask for their business, when the answer is almost always likely to be a no. At some level, too, many advisors understand that nobody likes to be bothered by sales calls – the advisor themselves included. But every now and then a cold prospecting call will lead to a "yes", which makes it at least a plausible way for those getting started in their careers to acquire their first few clients. A high enough volume of calls is bound to result in a few genuine prospects, and while it takes time and persistence to bear any results, advisors with few clients tend to have plenty of time on their hands to devote to prospecting – at least until they gain enough clients and revenue to allow them to scale back on cold calling and invest in other channels, like content marketing and referrals, that can generate inbound leads requiring less time and effort from the advisor themselves.

Despite the overall low number of advisors who engage in prospecting, there have recently been a number of new solutions aimed at easing the process of identifying and reaching out to prospective clients. Providers like Catchlight, Wealthfeed, Aidentified, Wealthawk, TIFIN AG, Equilar Exec Atlas, and Reply Assist all use some version of AI to find leads meeting various specific criteria (e.g., by scanning LinkedIn profiles and crawling public sources for news like company acquisitions, equity compensation grants, or home sales to identify "money in motion" events), qualifying those leads to match with the advisor's minimums or client niche, and/or automating outreach to prospects via email, text, LinkedIn, or other channels. But the outbound prospecting solution that has arguably gained the most buzz to date is FINNY, which made news in late 2024 after raising $4.3 million in seed funding, and then made news again earlier in 2025 when Ritholz Wealth Management CEO (and TV and internet personality) Josh Brown took a personal equity stake in the company.

And now FINNY has announced a new feature called Intent Search which it claims will help advisors find prospects who are likely to be actively searching for a financial advisor. The tool identifies prospects who have recently researched topics like rollovers or charitable giving (presumably by purchasing data from companies that track consumer behavior across the internet). Advisors can then prioritize those prospects and send them targeted outreach messages (also automated by FINNY).

The implication of Intent Search for financial advisors is that it can take some of the pain out of prospecting by narrowing the search down to individuals who, as evidenced by their research of financial topics, could be in the market for a financial advisor and therefore might be more willing to set up a call with an advisor who reaches out to them. Which is of a piece with the broader AI-driven prospecting space, which seeks to increase the success rate of outbound prospecting by finding and qualifying prospects and/or make prospecting more scalable by automating the outreach process via AI-generated messages targeted towards the prospect's specific situation.

But the fact remains, however, that few advisors see prospecting as a viable business growth strategy. While those who already use prospecting could potentially stand to benefit from a solution like FINNY if it can increase the hit rate of their prospect outreach even by a few percentage points, it's an open question as to whether that will be enough to convince advisors to adopt outbound prospecting who aren't already doing so – especially since many of those advisors likely did some kind of cold prospecting early in their careers and abandoned it as soon as they were able to.

That said, a big part of the reason that advisors largely shun outbound prospecting is the perception that it's inefficient and ineffective. If tools like FINNY can make meaningful improvements on both fronts by helping advisors with more targeted and automated outreach, then perhaps more advisors will see prospecting as a feasible long-term business development solution. Even if just 10% of advisors decide to adopt outbound prospecting, it would more than double the existing market for such tools today. Although it's worth noting that if AI-driven prospecting solutions become too successful, that might ironically hurt their long-term viability, since prospects who are flooded with AI-generated messages and voicemails might become even harder to reach effectively.

Ultimately, then, the success of FINNY – and the outbound prospecting category overall – may hinge on whether the potential of better results from prospecting can entice more advisors to adopt (or re-adopt) prospecting as a business strategy. Which in large part depends on those tools' effectiveness at generating a relatively consistent flow of prospects who agree to set up meetings, since the major pain point for advisors tends to be at the top of the funnel, i.e., getting prospects who will book meetings with them at all, rather than winnowing down a pre-existing list of prospects. In the meantime, though, they'll need to contend with the challenging reality that the large majority of advisors aren't necessarily looking for a solution to make prospecting better, but are instead focused on getting to the point where they don't have to prospect to begin with.

Large Enterprises Are Turning To AI To Solve Their Efficiency Problems, But Is It Just A Short-Term Patch For Long-Term Problems That Need A Non-AI Fix?

When enterprise firms grow and merge together over time, they accumulate technical debt. Technologies, capabilities, and processes that, in a perfect world, would be re-architected and improved each time the enterprise grows bigger or merges with another firm, instead get cobbled together and strung along through short-term patches due to a combination of resource constraints and simple inertia. Technical debt can accumulate for years or decades – e.g., a surprising number of government and payment systems still run on 1970s-era COBOL code, despite a dwindling number of programmers fluent in it – and is often only addressed when a critical system breaks and short-term patches are no longer enough to fix it.

But while it's easy to criticize organizations for accumulating technical debt instead of simply keeping their systems continuously up to date, the reality is that some amount of technical debt is inevitable in almost any organization. Particularly in situations where companies merge together, integrating one firm's systems with the other means resolving innumerable conflicts between technology, processes, and workflows. And with limited amounts of people and time to sort out every single issue, firms need to triage to make sure the most important problems get the highest priority – with the inevitable result being that the issues that can be more easily solved with a short-term patch than with a long-term fix, or which don't pose a threat to any critical systems, are set aside until the point that they do become a problem. In other words, similar to the finance world, not all debt is bad, and sometimes there are prudent uses of a little (technical) debt leverage!

Still, when a system or process becomes so out-of-date that it imposes a meaningful drag on productivity, it can be worth investing in ways to update it. The question then is: whether to tear the whole thing down and rebuild it in the way it would be if it were being built from scratch, or to apply another quick fix to improve things (which inevitably leads to the problem resurfacing again in a few years, repeating the scenario)? The answer invariably depends on the cost in time and resources for both options, and how near the issue is to the critical systems that keep the firm up and running.

It appears that in the post-AI world, the calculus has changed somewhat around which issues demand a complete rebuild and which can be resolved with a short-term stopgap. For example, LPL Financial has recently announced a new AI-powered tool that will purportedly allow advisors to more easily navigate their complex payout grids and understand "how to earn more". Which, in a vacuum, seems like a good example of an investment in AI, since AI can be ideal for pulling together complex information into a simple, easily understandable format, and helping advisors increase their pay can at minimum result in happier advisors who are more likely to stick with LPL and can maybe also generate additional revenue for LPL as well. But at the same time, the AI tool doesn't solve the underlying issue that LPL's payout system is so complex that it requires an AI tool just to understand it. Simplifying the payout structure so that advisors can clearly understand their own compensation would be more beneficial for both advisors and their clients in the long run, but for now, AI can serve as a workaround that gives advisors a little more clarity without requiring a complete retooling of employment agreements and pay grids.

In other cases, enterprises are employing AI as an overlay in order to improve legacy processes to the point where they are at least closer to what they would be if they were rebuilt with modern non-AI technology. For instance, Cambridge Investment Research has announced its own AI-driven tool that reportedly reduces the time it takes to open an account from nine days down to 'just' 17 minutes. Which again represents a meaningful improvement in efficiency given the time savings per account over thousands of accounts per year opened at Cambridge… but in a world where custodians from Betterment to Altruist to even legacy players like Charles Schwab allow for nearly instantaneous paperless account opening without using AI, Cambridge's announcement serves as more of a commentary on the technical debt of their systems than as a groundbreaking new use of the technology. Again, while the optimal path in hindsight would have been to make technological improvements to integrate and simplify systems, rather than to stack so many legacy systems on top of one another that an AI is needed to knit them all together, the existence of AI allows Cambridge to defer having to invest in making more fundamental updates to its systems while still implementing an expedient improvement that really does improve on their near-term productivity and advisor support.

The broader question in such cases where large enterprises rely on AI tools to 'fix' problems created by technical debt, is whether AI itself is the long-term solution, or if it represents just another short-term stopgap that will inevitably need addressing in a few years. It still takes a lot of resources to rebuild an existing technology, or to rip it out and replace it from scratch, and with AI as a potentially cheaper solution to an increasingly complex set of problems, it will be tempting for enterprises to use AI as a Band-Aid to provide relief in the short term. But in reality, such thinking is exactly how technical debt is created and accumulated to begin with: By prioritizing short-term expedient solutions rather than making substantial investments to solve the core problem. Which suggests that in the future, AI will find even more use as a way to patch together legacy systems rather than rebuilding them (including systems that are already being patched together with AI!), as a way to extend technical debt rather than a path to paying it down.

So amidst the pervasive hype that has surrounded AI and the claims of AI replacing broad swathes of workers across the economy, it's worth recognizing that, at least among some of the largest enterprise employers in the advisory industry, one of the most concrete impactful uses of AI has been simply to bring systems and processes up to get closer to the point where they would have already been if the firms had been able to allocate the time and resources to keep them up-to-date along the way. Which may certainly represent some material improvements for those businesses given that even incremental improvements in efficiency can add up to a substantial impact over the scale of a mega-enterprise. But it's a far ways off from the promise of AI as the productivity revolution of the future when in the present, it's proving more useful as a short-term loan to pay off long-term technical debt.

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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? How 'simple' can a financial plan become before it fails to adequately demonstrate an advisor's value? Is it worth paying basis points for custody in exchange for better cash yields and (some) technology discounts? Is it better to have an improved outbound prospecting experience, or to avoid outbound prospecting altogether? Let us know your thoughts by sharing in the comments below!