How Wigan Financial Advisors Can Use AI to Create Personalised Client Summaries
You're a financial advisor based in Standish, seeing twelve clients a week for annual reviews. After each meeting, you need to produce a personalised summary: what was discussed, the client's current position, recommended actions, and a suitability rationale. Each one takes between forty-five minutes and an hour to write. That's ten to twelve hours a week, every week, spent on admin that doesn't bring in revenue. AI won't replace that work entirely, but it can cut that time by more than half.
The Problem With Annual Review Documents
The annual review summary is one of the most time-consuming pieces of writing in financial planning. It needs to be personalised, readable, FCA-compliant in its rationale, and accurate to the specific client's situation. No two documents should look the same.
The challenge is that the content varies but the structure doesn't. You're always covering the same categories: objectives, current position, changes since last review, recommendations, risk assessment. Once you know how AI fits into that structure, you can use it to do the heavy drafting and focus your time on accuracy and compliance.
Using ChatGPT to Draft From Meeting Notes
The most practical workflow is this: take rough notes during your client meeting, then feed those notes into ChatGPT with a clear prompt asking it to produce a structured summary.
A prompt might look like: "Based on these meeting notes, write a personalised annual review summary for a client who is 58, approaching retirement, with a moderate risk profile and a pension pot currently valued at £210,000. Cover their objectives, current position, actions agreed, and a brief suitability rationale. Use plain English."
ChatGPT will produce a draft in seconds. It won't be perfect — it may miss nuance, misorder priorities, or use generic phrasing you'd want to change. But it gives you a complete structure to edit rather than a blank page to fill. For most advisors, editing takes fifteen to twenty minutes. That's a significant improvement on writing from scratch.
Making Reports Readable for Clients
One of the most common complaints clients have about financial review documents is that they're difficult to understand. Pages of technical language, unexplained acronyms, and dense paragraphs leave people confused about what they're actually supposed to do.
AI is particularly good at translating complex information into plain English. Once you've produced a draft, you can ask ChatGPT to simplify a specific section: "Rewrite this paragraph about pension drawdown options in plain English for someone who has no financial background." The result is usually much clearer, and clients are more likely to engage with a document they can actually read.
Personalised Action Points
Generic action points — "review protection needs", "consider pension contributions" — are easy to spot and feel lazy. A well-drafted summary should have specific, personalised recommendations tied to that client's situation.
This is where giving the AI enough detail matters. The more specific your meeting notes, the more specific the output. "Client mentioned that her husband recently retired and they are considering downsizing from their Leigh home within three years" gives the AI enough to produce targeted action points around cash flow planning, pension withdrawal timing, and property sale proceeds.
Proofreading and Compliance Checking With AI
Once you have a draft, you can use Claude or ChatGPT to do an initial proofread. Ask it to check for inconsistencies, unclear phrasing, or sections that could confuse a client. This isn't a compliance check — it's a readability check.
The compliance review must be done by a qualified human. The FCA is clear that AI-generated content used in regulated advice must be reviewed by a competent person before it goes to a client. AI speeds up the drafting; you are still responsible for the accuracy and suitability of everything in the document. Never send an AI-drafted report to a client without reading it in full yourself.
The Time Saving in Practice
A financial advisor who was spending ten hours a week writing client summaries and review reports can realistically reduce that to four or five hours with a consistent AI workflow. Over a year, that's 250 to 300 hours saved — time that can go into seeing more clients, business development, or simply not working evenings.
The key is building the workflow properly from the start: a consistent note-taking format that gives the AI enough detail to work from, a reliable prompt that produces the structure you need, and a clear review process before anything goes out.