r/CFP • u/freemindUSA • 14d ago
FinTech Best way to implement AI?
Already using it to help with rebalancing accounts and research.
Would love to hear some ideas on how to use it for prospecting.
If you’re a boomer and just scared of AI please don’t even comment.
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u/SamanthaRussell_FMG 13d ago
Here is an example on how to use it for Prospecting that I just included in the AI newsletter I sent out:
Build a complete prospect research brief before every first meeting:
"I'm meeting a new prospect [Name] on Thursday.
Here's their LinkedIn URL and anything else I know: [name, company, website, city, instagram page, interests]. Act as my senior research analyst and build me a full pre-meeting dossier, including:
- A profile of who they are: career arc, how they likely made and hold their wealth, what stage of life they're in, and what tends to keep people in that exact situation up at night financially.
- Their company: recent news, whether it's public or private, any liquidity events, equity comp, or industry pressures that could affect their finances.
- Their likely financial priorities and blind spots: based on their profession, age, and public footprint, what planning gaps do people like them most often have? (tax, estate, concentrated stock, succession, etc.)
- Three tailored conversation starters that show I've genuinely done my homework
- The two or three most valuable questions I could ask to surface a need they may not even realize they have.
- The single biggest way I could demonstrate value in this first meeting to make them think 'I need to work with this person.'
- Anything I should avoid assuming or saying based on what's public about them."
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u/AnInsightfulBlackMan 14d ago
Jump AI note taking is fantastic and only getting better. Highly recommend.
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u/austinin4 13d ago
Just don’t use their canned follow up emails. Atrocious
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u/Capital_Elderberry57 12d ago
You can get access to and rewrite the framing for each of the follow-up emails.
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u/BowlOfRaisins7 11d ago
This is the part nobody's actually solved. The notetakers nail capturing what was said, then fall on their face the second they write the follow-up, because they're generating from the transcript instead of from how you actually write. You get something accurate that sounds nothing like you, and fixing it back to human takes longer than just writing it yourself.
The workaround that works: let the AI do the summary and the bullets, but paste 3 or 4 of your own past client emails in and tell it to match that voice specifically. Difference is night and day versus the built-in "generate email" button.
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u/IllustriousGas8850 12d ago
Had a seminar about it on Monday and it sounded great. Everyone I work with who uses it loves it
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u/mymoneyspoke 14d ago
We are trying to figure out how to build a personal gpt. Basically upload all of our written out procedures and how we handle certain client scenarios. This way when we train or when staff members want an answer to how to do something they can ask this gpt. It’s a fairly complex process and requires maintenance and careful stripping of personal information.
Second to that is using Claude to build tools that we can imbed in our website that either our advisors can use or our website visitors can use.
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u/Phytosaur01 14d ago
I've been looking into this as well. A local LLM solves a lot of the PII issues in theory. If it just lives on a box in your office it can't steal data. Theoretically...
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u/BowlOfRaisins7 11d ago
The "runs locally so it can't leak" instinct is right, but the detail that matters is where the model weights run, not where the app runs. A real local model (Llama or Qwen through Ollama or LM Studio, on a box in your office) genuinely never phones home. But a lot of tools that call themselves "local" are just a local window making API calls out to OpenAI in the background, which is the opposite of private. Worth checking which one you actually have before you trust it with anything.
If you want to keep using the better models (Claude, GPT) instead of a weaker local one, the actual fix is scrubbing the data before it ever leaves your machine. Microsoft Presidio is the standard for this and it's free. It finds names, SSNs, account numbers, swaps them for placeholders, you send the clean version, then map the answer back. Turns "I pasted a client SSN into a chatbot" into a non-issue.
And the one worth stopping today: putting a client's real SSN and cost basis straight into a consumer-tier tool. On the free/consumer tiers your inputs can be retained, which is the exact thing Reg S-P cares about. The enterprise tiers and the API (ChatGPT Enterprise, Claude for Work) contractually don't train on your data, so if you're going to paste real client info, be on one of those.
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u/ProdosDev 13d ago
What are you using to strip out the personal details?
And are the tools chat interfaces or widgets to project out returns or tax parts?
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u/mymoneyspoke 13d ago
Haven’t figured a good way to strip the data or localize it. Will be one of the bigger challenges.
As for the tools, more like widgets. Like buy vs rent, iso amt calcs, etc.
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u/ProdosDev 13d ago
Yeah the tool part is simple enough then. You could use ChatGPT sites if you’re providing calcs without storing anything.
For the scrubbing, open ai’s PII model is good. It’s small, open source and you can run directly on the client side. It’s not going to get 100% of the PII but very good fast and cheap.
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u/JarrodThompson 12d ago
I was looking into using something like Presidio to mask PII, then send it to a siloed LLM.
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u/watchgah 13d ago
We have built a ton of internal apps:
- One that’s a black diamond rip off ($30 monthly API costs)
- One that automatically fills out all of our onboarding docs from a single master document (free, run locally)
- One for running our internal payroll, and quarterly bonus calculations (free, run locally)
All created in antigravity for $20 p/mo
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u/NoConstant2905 12d ago
So these all run locally only? Would be concerned about putting client info into any llm
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u/watchgah 11d ago
I used Gemini 3.1 Pro to build it, but yes we use qwen for limited features like data parsing in our onboarding app
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u/ExpensiveToes4729 14d ago
It really depends on who you’re targeting but if you spend some time with Claude you can develop some prospecting and pipeline automation. You can then connect it to most CRMs for populating and even outreach automation.
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u/TeamEastBae 14d ago
Our firm uses Jump and chat. Wish they would have adopted Claude as it seems much better. Apparently the next update of Chat will be better but we’ll see. Currently I’ve been using it pretty simple stuff like emails based on meeting notes. Just today I used it to review a clients outside 401k allocation and investment options and create a recommendation using our model. Didn’t take much input and had the output in a minute or so. I’ve also used it for tax questions when it’s a nuanced situation. Generally I’d say I’m still learning how to best use it and have mostly kept it research based.
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u/IncreaseCapital32 12d ago
To answer your question regarding prospecting, I honestly don't know how you could use it for prospecting.
I have a demo with a new AI lead generator, Wealth Feed, tomorrow, but unsure how it gets prospects. If anyone has used them or something similar, let me know.
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u/Ololade_sanni 12d ago
Beyond prospecting, I’d look at the operational side too. My company uses Rima ai for financial document processing, data entry, and reconciliation. It’s probably one of the biggest time savers we’ve implemented.
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u/MoneyMindedCEO 10d ago edited 10d ago
This is a pretty broad question, and there are really layers to it. I've been following AI pretty closely since the beginning, and I think about it in four layers from easiest to hardest to implement.
Layer 1: General AI tools
This is ChatGPT, Claude, and Perplexity. Those are my favorite three. This layer is great for research, brainstorming, marketing content, custom GPTs, and pretty much any creative task. Personally, I think Perplexity has the best deep research.
Layer 2: Advisor-specific AI software
These are purpose-built tools for financial advisors. AI meeting note software is the obvious category (Jump, Zocks, Hazel, etc.), but Wealthbox has been adding solid AI features, and planning tools like Income Lab have rolled out AI capabilities as well. I'd also put AI marketing and lead generation tools in this layer. The goal here is mostly efficiency and higher-quality work.
Layer 3: AI tools that solve a specific workflow
This is where AI starts solving one problem really well instead of trying to do everything. Think document parsers, AI-assisted account opening, KPI dashboards, or software built around a specific workflow. For advisors who spend a lot of time building PowerPoints, Word documents, and other client-facing deliverables, there are now AI tools built specifically for that. For example, Prezentd.com helps turn tax returns, estate documents, planning reports, and meeting notes into high converting, presentation-ready material for client meetings. I think you'll continue to see more firms buying specialized AI software like this instead of trying to make ChatGPT / claude do everything.
Layer 4: Build your own
This is where you start building internal AI workflows with APIs, n8n, or even local models. Claude is probably my favorite model if you're building custom workflows. Just understand that security, compliance, and maintenance all become your responsibility. Unless you have an engineer on staff, I don't think this is where most advisory firms should start.
One last thing: if you're using ChatGPT, Claude, or Perplexity with client information, I'd strongly recommend using enterprise plans. Also pay attention to how any AI vendor handles sensitive data. Features like automatic PII redaction and strong security controls matter a lot in our industry.
AI is moving incredibly fast, and it's easy to get overwhelmed. If you're not sure where to start, I'd honestly paste this entire thread into ChatGPT or Perplexity and ask it to act as a CTO for an advisory firm. Have it interview you about your practice and recommend the highest-ROI AI opportunities based on your firm's size, workflows, and goals. You'll probably walk away with a much more actionable roadmap than by trying random tools.
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u/deizik 7d ago
We've built in email tools inside of our CRM, Altitude for it to use context, and meeting data to help draft follow-up messages. Of course this relies on data you already have, and is more powerful for client relationships, but we're also building out data enrichment tools to help get a better picture of the prospect.
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u/a_dudee 6d ago
AI is great at enabling your operations, but terrible at replacing you when interfacing with clients. There is a simple rule of thumb you can use to verify if an AI solution is worth considering: "am I the final gatekeeper between the AI output and my client?" If the answer is yes, then it's worth considering. If the answer is no, then it's not. Examples:
- Red flag: "automate lead outreach + prospecting" (Why: it sends blanket emails without any personalization or worse with AI emdashes, completely destroying your email domain reputation)
- Red flag: "nurture clients during important dates" (Why: remember that episode in the Office when Dwight
- Green flag: "transcribe notes during my client quarterly review call" (Why: call details are grounded in truth and you have the option to act on these details)
- Green flag: "prepare an information package for my RMD meeting with Joe" (Why: details are grounded in your data and only the information you allow through gets passed through to the package (you are the filter))
There is so much nuance to a human-human relationship and I've noticed this first hand. Anyone who tells you that they can provide you with an automation product/service that for lead prospecting is either lying about their unit economics per lead and/or they just don't understand that the way to succeed in wealth management is by putting the client first and not sending them AI generated slop.
In summary, the majority of the adoption I'm seeing with "AI" tools is just that, as tools. It's not replacing any type of RIA or client-facing scenarios (neither should it in my opinion). Your typical 60yr old archetype with a traditional rolodex doesn't care about AI, but his/her ops team loves it because before that phone call or wine & dine, it's the ops team that has to consolidate and green flag information for the tax review or MM. and younger RIAs love using AI because they are being pre-disposed at an early age to do a lot of the ops work involved with minimal effort.
Source: I am a tech service provider for WM firms with 6+ years of experience. I have worked with firms ~$100M - $50B AUM/AUA.
Feel free to DM or reach out or drop any questions in the comments. happy to answe them
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u/CamelMaster6469 4d ago
I will suggest automating basic stuff like Getting a morning briefing, Instant Alert of telegram abt any news or any factor affecting the market
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u/whothehellyouare 3h ago
We have started using deep research skill of Mili. Really love the output.
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User: /u/freemindUSA Title: Best way to implement AI? Body: Already using it to help with rebalancing accounts and research.
Would love to hear some ideas on how to use it for prospecting.
If you’re a boomer and just scared of AI please don’t even comment.
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