Keeping every client review on time, in a business built on trust
A view of reviews due, completed and overdue by adviser, with the funds those clients hold, so the practice can rebalance workload before reviews lapse.
Key numbers on the dashboardAnnual client reviews · Year to September 2026
- Reviews due this year202Across 5 advisers
- CompletedFlagged75%Target 90%
- Clients overdueFlagged50Up from 18 a year ago
- Funds under adviceA$412MOverdue clients hold A$38M
The problem
An advice practice had reviews falling behind, and found out from compliance checks rather than from its own reporting. Advisers spent hours building review packs by hand.
What the numbers say
Overdue reviews have almost tripled in 12 months. The two advisers furthest behind carry the most complex clients.
How FDX uses it
- 01Connect the data
We connect the CRM and the platform data into one model, refreshed daily.
- 02Draft, then approve
AI drafts review packs and file notes from approved records. Advisers own every recommendation.
- 03Keep it private
Client names, account numbers and balances are masked before any AI model sees them, and client data is not used for training.
Next steps it points to
Review packs. AI prepares each review pack from approved client records. The adviser checks every figure and recommendation.
Capacity. Move 10 of Adviser C's reviews to a paraplanner led meeting this quarter.
Compliance. Draft file notes after each meeting for the adviser to edit and sign.
ExampleExample case study with illustrative sample data. Not a real client or real results.
Next exampleEngineeringStopping scope creep from quietly eating the fee
The dashboard is one part of the work.
It gives the team one trusted view of the numbers. The bigger gain is AI working from that same data to draft the follow ups, with a person approving every step.
When AI drafts from your data, personal details are masked before the model sees them. Onshore hosting is available, and your data is not used for training.