Wealth management
Wealth management software the compliance review will not send back
Advisors sit on custodian data and a fee an AUM client can see. The software has to justify both.
What makes this vertical different
4 things that decide this
- 01Client data usually already lives at a custodian. Schwab and Fidelity expose it through an API, and the build has to read that data rather than re-collect it.
- 02The SEC Marketing Rule governs any performance claim or testimonial an advisor's software shows a prospect. Get the disclosure wrong and the software is the liability.
- 03A client paying a fee tied to assets under management expects the software to look and behave like it is worth that fee. A generic dashboard undercuts the pitch.
- 04Tax and portfolio decisions compound over decades, so a projection tool has to show its assumptions alongside its output.
The software has to prove the plan
A wealth management build rarely starts from a blank slate. A custodian already holds the balances, the positions, the transaction history. The engineering problem is pulling that data through an API, then building a plan a client can act on.
Most of that plan involves documents. Tax returns, K-1s, 1099s, statements. A tool that reads those documents and checks its own extraction earns trust fast. One that asks a client to retype numbers into a form does not.
IRS Escape Plan runs this exact pattern. It reads 1040s, K-1s and 1099s and checks the figures. It runs more than 50 rules against the client's profile and produces a report in under 30 minutes. That is what a wealth platform needs: real documents in, a checked plan out.
What we have shipped
Counted, not estimated
50+
tax strategies checked per client profile inside IRS Escape Plan
<30 min
to produce a personalized strategy report, document-verified
22
production systems shipped, across fintech, trading and financial documents
The wealth management work we take
Advisor tools and client-facing platforms where custodian data, documents and real-time markets meet.
Custodian data integration
Pulling balances, positions and transactions from a custodian API and reconciling them against your own record, so the advisor is never working from a stale export.
Document intelligence on tax and financial paperwork
Reading 1040s, K-1s and 1099s, then checking the extraction against the arithmetic rather than trusting a confidence score. IRS Escape Plan runs this exact pattern for high earners.
Real-time alerting with a human approval gate
Trading CoPilot turns TradingView webhooks into a message the trader approves before a broker connection executes anything. Wealth platforms need the same discipline: an agent that proposes, a person who confirms.
Long-horizon projection tools
Calculators built to show their assumptions beside the output number. A 15-to-20-year projection only earns trust if a client can see what drives it.
Client-facing portals
A portal that matches the fee the client pays. Role-based views for the advisor and the client, built on the same underlying record so nobody works from two versions of the truth.
- Custodian pullBalances and positions, read not re-entered.
- Document intake1040, K-1, 1099 uploaded or scanned.
- ExtractionFields read, then checked against the maths.
- Strategy engineRules run against the client's actual profile.
- DisclosureAny claim or projection is labelled as one.
- Client reportAssumptions shown beside the number.
The failure point is almost never the model. It is a confident number with no visible assumption behind it, handed to a client who has to defend it to their own accountant.
A marketing claim inside the software is still a marketing claim
The SEC's Marketing Rule covers any communication that offers an advisory service. Software the advisor shows a prospect counts too. A projected return, a hypothetical chart, or a testimonial inside the app follows the same rules as a printed brochure.
Teams building the software rarely think of a chart as a marketing communication. The disclosure ends up as a design afterthought instead of a requirement decided before the screen is built.
We treat every projection and every hypothetical inside the product as a labelled claim from the first wireframe. The assumptions sit next to the number, not buried in a footer nobody reads.
- Decide which numbers are hypothetical before the screen is designed, not after compliance flags it.
- Attach the assumption to the number, on the same screen, not in a linked disclosure.
- Log what a client saw and when, since a projection changes as inputs change.
Financial documents and real-time money decisions we have built
A calculator against a system an advisor can defend
| Criterion | The usual build | How we build |
|---|---|---|
| Client data | Re-entered by hand from a statement. | Pulled from the custodian API and reconciled. |
| Document reading | Extraction trusted at whatever confidence score it returns. | Extraction checked against the underlying arithmetic. |
| Projections | A number on a chart. | The number with its assumptions shown beside it. |
| Automated actions | Executed as soon as the model decides. | Proposed, then approved by a person before anything moves. |
| Marketing claims | Decided by whoever built the screen. | Labelled and logged from the first design pass. |
What these builds run on
Application
Data
Integrations
AI
Questions wealth management teams ask us first
01Can you build on top of our custodian's API?
Yes, that is usually the starting point. Schwab and Fidelity both expose account data through an API. The build reads it directly, instead of asking a client to re-enter what the custodian already has. Matching that feed against your own record is the part that takes care.
02How do you keep AI-generated projections compliant with the Marketing Rule?
Every hypothetical or projected figure gets labelled as one, with its assumptions on the same screen. That gets decided before the interface is designed, not patched in afterward. Anything shown to a prospect is treated as a marketing communication, because under the rule it is one.
03Can AI read our clients' tax documents accurately?
Yes, provided the extraction is checked rather than trusted. IRS Escape Plan reads 1040s, K-1s and 1099s and verifies the figures against the arithmetic. A misread number becomes a flagged exception, not a wrong plan handed to a client.
04Should trades or rebalancing ever execute automatically?
Only with a human approval step in front of anything that moves money. Trading CoPilot sends the proposed action to the trader and waits for a yes before it reaches the broker. The same pattern fits automated rebalancing.
05How much does a wealth management platform cost to build?
The main drivers are how many custodian integrations you need and how much of the plan is document-driven. How heavily compliance reviews client-facing screens matters too. Scoping calls are free. Where we need to read an existing codebase to answer honestly, we run a paid two-week diagnostic and you keep the findings either way.
Go deeper
- Fintech software development →The ledger and payment engineering underneath any financial product.
- IRS Escape Plan →Document-verified tax strategy, built and shipped.
- Trading CoPilot →Real-time alerts with a human approval gate before execution.
- Predictive analytics →Forecasts tied to a decision, checked against what actually happened.
