Summary
What this article covers in 30 seconds
- A poll found 80% checked 0-10% of annual reviews for suitability.
- No-change files can be high risk when a client’s position has not changed for years.
- AI can flag cases, check evidence and support RAG-rated reviews.
- Suitability reviews can create collaborative insight when findings are evidence-based.
Suitability reviews are often treated as a routine compliance step during new business. Quieter cases can pose greater risk: annual reviews where the advice is that nothing should change.
The reality of no change reviews
During a webinar, attendees were asked how often they formally undertake a suitability assessment as part of a client’s annual review, even where the advice is no change.
- More than 10% of annual reviews are subject to a suitability check: 20%.
- 0-10% of annual reviews are subject to a suitability check: 80%.
- No annual reviews are suitability checked: 0%.
All surveyed firms understood the importance of reviewing ongoing advice.
Why they matter
David Boyhan, TCC’s Technical Director, said no-change reviews should not be ignored. From a risk perspective, these files can be high risk, particularly where a client’s position has not changed for a number of years.
The absence of a new product recommendation is often why the files are overlooked, but ongoing suitability still needs verification. The checks are straightforward in principle: confirm a meaningful annual review occurred, check that client objectives and needs remain aligned with the advice, and confirm that attitude to risk and capacity for loss remain appropriate.
Applying these checks consistently across large client bases is more difficult in practice.
How risk profiles shape review frequency
Products do not all carry the same risk. Drawdown accounts typically need more frequent scrutiny than ISAs. Clients who have not engaged for more than 12 months but are still paying fees also need file reviews to check they are benefiting from the services provided.
These nuances turn no-change reviews from routine paperwork into a compliance checkpoint.
Using AI to make it work
Neil Dethick, TCC’s Operations Director, described how AI is changing no-change review work in his managed services team. AI is not replacing human judgement; it is removing labour-intensive tasks.
It can flag cases that need attention, check for evidence of meaningful annual reviews and help reviewers RAG-rate files based on timeliness, documentation and client outcomes. The result is faster, more accurate assessment and clearer evidence of where processes work well and where improvement is needed.
Advisers receive targeted feedback without the combative back-and-forth that can accompany traditional compliance checks.
From burden to collaborative insight
Suitability reviews, whether for new business or ongoing advice, can provide valuable insight when handled well. Evidence-based feedback helps compliance teams and advisers work collaboratively. Patterns and trends become easier to identify, helping firms encourage positive behavioural change without adding extra costs.
This aligns with the FCA’s “show me don’t tell me” approach. Firms need to evidence good outcomes and a reasonable sampling process. Without this, FCA censure is a real risk.
No-change review clients can represent a large share of a wealth manager’s population, often exceeding new business clients. Ignoring them can increase compliance risk and future workload, so they should be treated as higher risk and built into business assurance models.
Bringing it to life
A free consultancy review was offered for ongoing services cases. The first five requests would receive a sample assessment of 100 client files to show current compliance standards and improvement actions, helping turn no-change reviews from a compliance obligation into a source of practical insight.
Frequently asked questions
Clients whose position has not changed for years may still need their ongoing suitability verified.
They should confirm a meaningful annual review occurred, check that objectives and needs still align with advice, and review attitude to risk and capacity for loss.
AI can flag cases, check evidence of meaningful reviews and help reviewers RAG-rate files by timeliness, documentation and outcomes.
It showed 20% checked more than 10% of annual reviews, 80% checked 0-10%, and 0% checked none.