The Annual Review End-to-End: Where the Time Actually Goes in an Intelliflo Firm
The question nobody asks precisely enough
“How long does an annual review take?” is a question most IFAs have an answer to. The answer is usually something like “about three to four hours” or “it varies” or — most honestly — “I haven’t actually measured it.”
The problem with the question is that it bundles together six or seven distinct stages, each with its own time cost and its own failure mode. When you disaggregate them, the picture looks quite different from the summary figure.
I’ve been mapping this for my own firm and for a number of other Intelliflo practices. What follows is a stage-by-stage account of where the time actually goes in a standard annual review — and where automation does and doesn’t make sense.
The numbers are from real workflows. They won’t match your firm exactly, but they should be close enough to be useful for identifying where your own process is leaking time.
Stage 1: Pre-meeting data pull
What it involves: Pulling the current portfolio valuation from the platform, finding last year’s fact find in Intelliflo, reviewing the previous suitability letter, checking for any events flagged in IO since the last review (bereavements, address changes, new accounts), and pulling the most recent charges disclosure.
Typical time: 40–70 minutes.
Where it slows down: The main friction is that this data lives in multiple places and none of them talk to each other automatically. Platform valuations are pulled by logging into each provider portal separately, or via a third-party aggregator if the firm has one set up. The previous fact find is in Intelliflo but may be partially complete or have stale fields. The previous suitability letter is usually in a document store — IO, OneDrive, a network drive — and isn’t searchable by content.
The result is that pre-meeting prep involves 20–30 minutes of what is essentially data retrieval before any thinking has happened.
What automation can do here: This is the stage with the clearest automation case. If Intelliflo holds clean, complete client data and connects to a platform data feed, a pre-meeting pack can be assembled automatically — current values, previous fact find responses, flagged events, charges summary — and dropped into a structured template before the adviser touches it. The adviser’s job becomes reviewing and annotating, not collecting.
The precondition is data quality. If the Intelliflo record is incomplete or the platform data feed isn’t set up, there’s nothing to automate yet. Fixing the data is the unglamorous prerequisite.
Stage 2: The review meeting itself
What it involves: The client conversation — updating circumstances, reviewing performance, discussing recommendations, confirming ongoing suitability.
Typical time: 45–60 minutes for a standard client. Longer for complex circumstances, shorter for straightforward reviews.
Where it slows down: The meeting itself rarely slows down from an operational perspective. The friction is in the capture — specifically, the notes taken during the meeting and how structured they are for what comes next.
Advisers who take unstructured notes (narrative paragraphs, bullet points across multiple pages) create downstream work for themselves or their paraplanner. The meeting was efficient; the write-up will take longer than it needs to because the inputs aren’t in a usable format.
What automation can do here: Meeting transcription tools (Otter, Fireflies, Fathom and others) handle the capture side. This is a solved problem for most firms that want it — the tools work well enough and consent protocols are well-established.
The more important question is whether the transcript or the meeting notes are structured in a way that feeds cleanly into the next stages. A transcript is not a fact find update. A voice note is not a file note. The value of capturing the meeting well is entirely determined by what happens to that capture afterwards.
Stage 3: Fact find update in Intelliflo
What it involves: Updating the client record in IO with any changes that came out of the meeting — employment changes, new dependants, change of address, updated expenditure, revised objectives, vulnerability flags, change in risk profile.
Typical time: 15–30 minutes.
Where it slows down: This step is almost entirely manual for most firms. The adviser or admin staff member reads back through meeting notes, identifies the changes, and enters them field by field into Intelliflo. If the meeting notes aren’t structured — which they often aren’t — this involves interpretation as well as data entry.
The specific Intelliflo pain point: the IO fact find module is comprehensive but not fast to navigate. Updating five or six fields across different sections takes longer than it should, particularly if the firm hasn’t customised the module to match their standard fact find structure.
What automation can do here: This is the step most firms haven’t thought about automating, and often the one with the most straightforward case. If meeting notes are captured in a structured format — even a simple template with named fields — those fields can be mapped to Intelliflo’s API and written back to the client record automatically. No re-keying. No interpretation step.
The barrier is usually that Intelliflo’s API requires some setup work and the data mapping needs to be firm-specific. It’s not a plug-and-play integration for most systems. But it’s also not as complex as it sounds — it’s a mapping exercise, not novel engineering.
Stage 4: Post-meeting file note
What it involves: The written record of what was discussed in the meeting, what was recommended, and what was agreed — the file note that would stand up to a compliance review or FCA scrutiny.
Typical time: 20–45 minutes.
Where it slows down: File notes are inconsistent across firms and often across advisers within a firm. The standard varies. Some advisers write thorough, structured notes immediately after the meeting; others write cursory notes and fill in the detail later from memory. Some firms have a template; many don’t.
The Consumer Duty dimension adds pressure here. A file note that says “annual review conducted, recommendations discussed, client happy” no longer passes scrutiny. The note needs to evidence ongoing suitability, good outcomes, and — where relevant — vulnerability consideration. That evidencing doesn’t need to be long, but it does need to be there, in a consistent format, for every client.
What automation can do here: A structured meeting note template, populated during or immediately after the meeting, generates most of the file note content without additional drafting. If the template includes the Consumer Duty evidence fields — one question about ongoing suitability confirmation, one field for vulnerability assessment, one for any material change in circumstances — the evidencing is produced as part of the meeting capture, not as a separate step.
This is the structural change that separates firms handling Consumer Duty well from firms bolting evidence onto the process retrospectively. The content required is roughly the same. The difference is where in the process it’s captured.
Stage 5: Suitability letter draft
What it involves: The formal suitability letter or report — recommendations rationale, charges disclosure, risk profiling outcome, Consumer Duty elements.
Typical time: 1.5–4 hours, depending on complexity and how much of the preceding stages have been completed well.
Where it slows down: This step gets most of the attention in conversations about AI and advice efficiency, but in well-structured firms it’s often not the biggest time cost. The letter is genuinely time-consuming when the preceding stages were done poorly — when the fact find is incomplete, the meeting notes are unstructured, and the risk profile output isn’t easily extractable.
When Stages 1–4 have been done well, the letter becomes closer to an assembly job than a writing job. The rationale structure is standard, the client circumstances are documented, the recommendation is clear. The variance in time from firm to firm is often explained more by the quality of the upstream data than by the skill of the person writing.
What automation can do here: A first-draft suitability letter can be generated from structured meeting notes, Intelliflo data, and a CIP-aligned template. The draft handles the standard structure, the charges disclosure numbers, and the risk profiling narrative. The adviser or paraplanner reviews, amends for the specific client circumstances, and approves.
The key word is “first-draft”. The AI isn’t deciding what to recommend or why. It’s assembling a structured document from the information that already exists. The review step — the one that requires professional judgement — stays human.
The time reduction is significant but depends entirely on the quality of the inputs. A suitability letter drafted from structured, complete data can be reviewed and approved in 20–40 minutes. The same letter drafted from scratch from unstructured notes still takes hours.
Stage 6: Intelliflo update on completion
What it involves: Updating Intelliflo with the outcomes of the review — implemented recommendations, updated fund holdings, new review date, any changes to the ongoing service package, filing the completed documents.
Typical time: 15–25 minutes.
Where it slows down: This is a pure admin step and in most firms it’s done manually by admin staff. The agreed actions from the meeting need to be entered into IO, the documents need to be filed against the client record, and the review date needs to be set. Each of these is a separate action in IO.
The inefficiency is particularly visible in firms where advisers hand off to admin staff for this step — the handoff itself takes time (briefing, checking back, correcting errors) and the admin staff member is duplicating information that has already been captured elsewhere in the process.
What automation can do here: If the agreed actions are recorded in a structured format at the time of agreement — which they should be as part of the file note — they can be written to Intelliflo automatically on approval. Review date set. Holdings updated. Documents filed. The admin step becomes a review step rather than a data entry step.
What the full picture looks like
Aggregating across all six stages for a standard annual review at a firm that hasn’t automated anything:
| Stage | Manual time |
|---|---|
| Pre-meeting data pull | 40–70 mins |
| Meeting | 45–60 mins |
| Fact find update in IO | 15–30 mins |
| File note | 20–45 mins |
| Suitability letter draft | 90–240 mins |
| Intelliflo update | 15–25 mins |
| Total | 225–470 mins (3.75–7.8 hours) |
NextWealth’s 2025 benchmarking puts the industry average at 4.8 hours. That sits in the middle of this range, which suggests the benchmarking is consistent with what firms are reporting in practice.
With automation applied to Stages 1, 3, 4, 5, and 6 — the data retrieval, the IO writes, the file note structure, the first-draft letter, and the completion update — the picture looks like this:
| Stage | With automation |
|---|---|
| Pre-meeting data pull | 5–10 mins (review pre-populated pack) |
| Meeting | 45–60 mins (unchanged) |
| Fact find update in IO | 5 mins (review auto-written fields) |
| File note | 5–10 mins (review structured template) |
| Suitability letter draft | 20–40 mins (review and amend first draft) |
| Intelliflo update | 5 mins (review auto-filed completion) |
| Total | 85–130 mins (1.4–2.2 hours) |
The meeting time doesn’t change — nor should it. The advice conversation is the point. Everything around it is a candidate for automation.
The preconditions that most firms skip
Before any of this automation is viable, three things need to be true:
1. Intelliflo data quality. The automation in Stages 1 and 3 depends on IO holding complete, accurate client data. If the record has stale fact find data, missing fields, or inconsistent formatting across clients, the automation pulls bad data and produces bad outputs. A data audit before automation setup is not optional — it’s the foundation.
2. Documented process. A workflow that exists primarily in the adviser’s head cannot be automated. The steps need to be written down, agreed across the firm, and consistently followed. This is unglamorous but it’s often the most valuable output of the early stages of an automation project — the process documentation alone tends to surface inefficiencies that firms didn’t know they had.
3. A defined CIP and template. The suitability letter automation in Stage 5 depends on having a clear, documented CIP and a letter template that reflects it. If different advisers use different templates or the CIP isn’t written down in a form that can be encoded into a prompt, the first-draft output will be generic rather than firm-specific.
None of these are obstacles to automation in the long run. They’re stages of readiness, and working through them has standalone value independent of any technology investment.
What this means for Intelliflo firms specifically
The annual review automation case is stronger for Intelliflo firms than for firms on some other back-office systems, for two reasons.
First, Intelliflo’s API is well-documented and relatively accessible. The data writes in Stage 3 and Stage 6 are technically feasible without bespoke middleware — they require configuration, not novel engineering.
Second, most of the firm’s client data already lives in IO. The pre-meeting pack in Stage 1 can be populated almost entirely from IO data plus a platform data feed. The information is there — it just needs something to assemble it.
The gap Intelliflo doesn’t close is the integration between IO and the other tools in the advice stack — the meeting capture tool, the cashflow modeller, the risk profiler, the research platform. Each of those sits outside IO and requires a connection. Building those connections, and mapping the data flows between them, is where the real automation work lies.
That’s the layer IFAgent builds. If you want to understand what that would look like for your specific firm and stack, the 30-minute discovery call is the fastest way to find out.
Stage timings based on workflow mapping across Intelliflo advice firms in 2025–2026. Industry benchmark: NextWealth Financial Advice Business Benchmarks Report, October 2025 (263 respondents).