STATEMENT TO HOLDINGS
Example allocation · Review the extracted holdings before analysis.
Automating investment proposal generation starts with the client statement, but it should not end with data extraction.
With Investipal, advisor teams can move from client statement intake to proposal-ready recommendations in under 10 minutes, with support for 50+ custodian statement formats and 99%+ extraction accuracy for structured statement data.
The real value comes when the statement data flows into portfolio analysis, proposal generation, IPS documentation, onboarding, and follow-up tasks without the team rebuilding the same record in separate systems.
If you are comparing proposal software vendors, start with our investment proposal software guide. This article focuses on the narrower statement-to-proposal workflow.
TL;DR
- Statement scanning removes the first bottleneck: manual holdings entry.
- Investipal supports 50+ custodian statement formats and 99%+ extraction accuracy for structured statement data.
- Proposal automation needs clean data flow from statement intake to analysis and recommendations.
- Advisors should review extracted data and control the final recommendation.
- The strongest workflow connects statement scanning, proposal generation, IPS, onboarding, and Alpha.
Step 1: Upload the client statement
Most proposal delays begin when a prospect sends a brokerage statement and someone has to turn it into usable portfolio data.
Investipal's automated statement scanner supports 50+ custodian statement formats and 99%+ extraction accuracy for structured statement data. It helps extract holdings and account-level information from statement files so the advisor can review the structured data instead of typing it from scratch.
This matters because the proposal will only be as useful as the data underneath it.
Step 2: Review and structure the portfolio
Before building the recommendation, compare the imported holdings with the source statement and confirm which accounts belong in the analysis. A correctly extracted position can still lead to a misleading comparison if it belongs to the wrong household or comes from a different reporting date.
Use the following checks as an advisor review process. They describe what to verify, not a promise that every check happens automatically.
| Check | What to compare with the source |
|---|---|
| Statement date | Confirm the reporting period and note any accounts with different dates |
| Account and household | Check that each included account belongs to the intended client or household |
| Holding identity | Review the security name and identifier; resolve unclear or unmatched positions |
| Quantity and value | Compare units and reported position values, keeping price dates in mind |
| Cash and totals | Check how cash is represented and reconcile totals using the same reporting basis |
| Duplicate records | Look for an account or position included more than once through overlapping uploads |
Investigate differences before changing the data. A statement total and an analysis total may use different dates or include different items. Work out what each total represents rather than adjusting a holding just to make the numbers match.
Keep uncertain holdings separate from proposed replacements
If a security is unclear, return to the statement or obtain clarification before treating it as a confirmed holding. A missing identifier should not become a guessed security in the recommendation.
Similarly, keep the client's actual holdings distinct from the investments you propose. If an existing holding is being used as a proxy for a proposed exposure during a transition, make that relationship explicit in the analysis. Do not relabel the original holding as the proposed security.
For example, a client holding VOO still holds VOO when a proposed allocation uses SPY. A proxy decision can inform what to retain during the transition; it does not change the source record.
Resolve the review before moving into analysis
Confirm the accounts, holdings, and reporting dates you will use. Record any outstanding questions and resolve material differences before comparing the current portfolio with a recommendation.
This makes the next step more useful: the advisor can explain the proposed changes against a current portfolio that has been checked, rather than spending the proposal meeting untangling the inputs.
Step 3: Run comparative portfolio analysis
The next step is to compare the current portfolio with the proposed recommendation.
Useful analysis can include:
- current vs. proposed allocation
- concentration and exposure
- risk and performance context
- fee and cost considerations
- transition considerations
- recommendation rationale
The client should be able to see why the recommendation is being made, not just what the proposed allocation is.
Step 4: Generate the proposal
With the statement data and analysis in place, proposal generation can turn the workflow into a branded, client-ready proposal.
The proposal should include a clear explanation of:
- the client's current situation
- the recommended portfolio
- the reason for the change
- the expected client benefit
- the next steps
AI can help draft the narrative, but the advisor should control the final recommendation and client-facing language.
Step 5: Create supporting documentation
Proposal work often triggers documentation work.
Advisory teams may need to support the recommendation with an investment policy statement, internal rationale, or related review steps. When the same data powers the proposal and the supporting documentation, the team avoids copying details between tools.
Step 6: Move from proposal to onboarding
When the prospect is ready to move forward, the workflow should continue into client onboarding.
The statement, analysis, risk inputs, and proposal context should not be abandoned after the PDF is generated. They should help the team prepare the client record, required steps, documents, and follow-up work.
Step 7: Use Alpha for follow-up
The last step is execution.
Alpha, Investipal's in-app AI assistant, can help teams create tasks, answer workflow questions, and keep proposal follow-up from getting buried in email or chat.
That is important because an automated proposal still needs an owner, a next step, and a clear path into the client relationship.
What to avoid
Avoid proposal workflows where:
- statement data is extracted but not connected to analysis
- analysis has to be copied into a separate proposal tool
- IPS documentation is created from scratch
- onboarding restarts data collection
- follow-up tasks live outside the advisor workflow
Each handoff adds time and increases the chance that something gets missed.
See the statement-to-proposal workflow
Investipal is built to connect statement intake, analysis, proposals, IPS, onboarding, and follow-up in one advisory workflow.
Explore Automated Statement Scanner, review Proposal Generation, start a free trial, or book a demo to see the workflow end to end.
FAQ
How do advisors automate investment proposal generation from a client statement?
Advisors can automate the workflow by using statement scanning to extract holdings, reviewing the structured portfolio data, running analysis, generating a branded proposal, preparing IPS documentation, and carrying the same client context into onboarding.
Is statement scanning enough to automate proposals?
No. Statement scanning is the intake layer. To automate proposal generation meaningfully, the extracted holdings need to connect to portfolio analysis, recommendation rationale, proposal output, compliance documentation, and follow-up tasks.
How does Investipal support statement-to-proposal workflows?
Investipal connects automated statement scanning, portfolio analysis, proposal generation, IPS, onboarding, and Alpha so teams can move from client data to client-ready next steps in one workflow.
How fast can Investipal turn a client statement into a proposal-ready workflow?
Investipal helps advisor teams move from client statement intake to proposal-ready recommendations in under 10 minutes, with support for 50+ custodian statement formats and 99%+ extraction accuracy for structured statement data.
