Case Study 1: Automating the Annual Client Review Process
What an IFA could achieve by automating review administration
The opportunity
Annual client reviews are a core part of delivering an effective ongoing financial-advice service.
At the same time, the administration surrounding those reviews can consume hundreds of hours each year.
Review dates need to be monitored. Clients need to be contacted. Appointments need to be arranged. Updated information has to be collected and checked. Files need to be prepared for advisers. Meeting outcomes and follow-up actions then need to be recorded and tracked.
For many IFAs, these activities are spread across:
CRM records.
Spreadsheets.
Email inboxes.
Adviser calendars.
Personal task lists.
Shared folders.
Manual reminders.
If these processes are not connected, clients may be contacted late, information may be incomplete before meetings and advisers may spend valuable time checking whether files are ready.
Automating the annual-review journey could help an IFA create a more consistent client experience, improve visibility of ongoing-service delivery and release significant administrative capacity.
What could be improved?
A manual annual-review process may involve:
Exporting a list of clients due for review.
Checking the list against a separate spreadsheet.
Confirming client contact details.
Assigning reviews to advisers.
Sending review invitations manually.
Chasing clients who do not respond.
Arranging appointments through email.
Requesting updated financial and personal information.
Checking whether documents and information are complete.
Preparing the review file.
Recording meeting outcomes.
Creating follow-up tasks.
Monitoring outstanding actions.
Escalating overdue reviews manually.
Common challenges include:
Review dates being held in more than one place.
Clients being contacted later than intended.
Repeated manual chasing.
Missing information being identified shortly before meetings.
Advisers checking whether files are ready.
Inconsistent client communications.
Review preparation being dependent on individual employees.
Limited visibility of overdue reviews.
Follow-up actions being missed.
Difficulty monitoring whether ongoing services have been delivered.
Administrative capacity limiting future growth.
What could automation look like?
1. Annual review data assessment
Before automating the process, the existing review data could be assessed and client records grouped into categories such as:
Confirmed review date.
Estimated review date.
Missing review date.
Invalid contact details.
Duplicate client record.
Review already in progress.
Client not currently receiving an ongoing service.
Client requiring manual review.
Client with incomplete information.
Client requiring additional support.
This would help prevent poor-quality information from being carried into an automated workflow.
It would also show where data cleansing or manual investigation is required before client communications begin.
2. Annual review opportunity engine
The workflow could check the CRM every day and identify clients approaching their next annual review.
A possible review schedule could be:
90 days before review: early preparation.
60 days before review: initial client invitation.
45 days before review: first follow-up.
30 days before review: priority engagement.
14 days before review: adviser or administrator intervention.
Review overdue: escalation for manual action.
The exact timings could be adjusted to the firm’s service model.
Each client could be assigned a clear status such as:
Upcoming review.
Initial contact required.
Awaiting client response.
Appointment booked.
Information incomplete.
Ready for adviser.
Review completed.
Follow-up action outstanding.
Escalation required.
This could remove the need to maintain a separate review-tracking spreadsheet.
3. Personalised annual-review communications
Clients could receive communications appropriate to their stage in the review journey.
Messages could explain:
That their annual review is approaching.
The purpose of the review.
What information needs to be updated.
Which documents may be required.
How to complete a secure update form.
How to book an appointment.
What will happen next.
Who to contact if they need additional support.
The system could personalise communications using information already held in the CRM, such as:
Client name.
Adviser name.
Review date.
Service type.
Appointment options.
Relevant document requirements.
All communication wording would be approved by the firm.
4. Automated reminders and follow-up
Clients who do not respond could receive reminders automatically.
For example:
First reminder after seven days.
Second reminder after 14 days.
Administrator task after 21 days.
Adviser escalation after 30 days.
Compliance or management escalation if the review becomes overdue.
Every communication and follow-up task could be recorded automatically against the client record.
This would allow employees to focus on clients who actually require human intervention rather than repeatedly chasing every client manually.
5. Digital circumstances update
Clients could complete a secure digital form before their review.
Depending on the firm’s advice process, the form could collect updates relating to:
Contact details.
Employment status.
Income.
Expenditure.
Assets.
Liabilities.
Dependants.
Financial objectives.
Retirement plans.
Existing investments.
Pension arrangements.
Attitude to risk.
Capacity for loss.
Property ownership.
Health or vulnerability considerations.
Major changes in circumstances.
Future financial priorities.
The form could adapt according to the client’s previous answers.
For example, a client who reports a change in employment could receive additional questions relating to income and pension arrangements.
6. AI-assisted comparison and summarisation
AI could compare the latest client information with the previous review record.
It could highlight changes such as:
A revised retirement date.
A change in employment.
A new dependant.
A significant increase or reduction in income.
A major increase in expenditure.
A property purchase.
An inheritance.
A change in financial objectives.
A change in investment preferences.
A change in household circumstances.
Missing information.
Contradictory information.
The AI would not make a suitability decision or recommendation.
Its role would be to organise information and highlight areas requiring adviser attention.
7. Automated adviser preparation pack
Once the required information has been collected, the workflow could automatically prepare a structured review pack.
This could include:
Current client details.
Previous review information.
Previous objectives.
Material changes since the last review.
Existing products and investments.
Outstanding questions.
Previous recommendations.
Recent correspondence.
Documents supplied.
Missing information.
Suggested discussion points.
Actions requiring adviser attention.
The adviser could then receive a notification that the client file is ready for review.
This would create a more consistent preparation process across the firm.
8. Post-meeting action management
Following the annual review, meeting notes could be transcribed and summarised with appropriate client knowledge, consent and controls.
The workflow could identify:
Agreed client actions.
Adviser actions.
Administrator actions.
Target completion dates.
Documents still required.
Follow-up communications.
Additional advice requirements.
Possible referrals.
Future review dates.
Outstanding compliance tasks.
The adviser would review and approve the information before it was stored.
Tasks could then be automatically assigned to the relevant employee.
Annual review dashboard
Management could view:
Reviews approaching.
Reviews due this month.
Reviews completed.
Clients who have not responded.
Appointments booked.
Meetings with incomplete information.
Reviews awaiting adviser action.
Follow-up actions outstanding.
Overdue reviews.
Completion rates by adviser.
Reasons reviews have been delayed.
Clients requiring additional support.
Review volumes by month.
Records requiring manual attention.
This could provide a much clearer view of ongoing-service delivery across the firm.
What could be achieved?
Assume that an IFA has 600 ongoing-service clients requiring an annual review.
1. Without a structured automated process
If supporting administration takes approximately 135 minutes per review:
600 reviews × 2.25 hours = 1,350 hours per year
2. With a structured automated process
If automation reduces employee involvement to approximately 55 minutes per review:
600 reviews × 0.92 hours = approximately 550 hours per year
3. Potential annual capacity released
1,350 hours − 550 hours = 800 hours
At an illustrative employment cost of £30 per hour:
800 hours × £30 = £24,000 of annual administrative capacity
This does not necessarily mean £24,000 of direct cash savings.
The value could instead be realised through:
Avoided recruitment.
Reduced overtime.
Increased adviser capacity.
Faster review preparation.
More time for complex client work.
Improved client service.
Greater review consistency.
Improved management oversight.
Capacity to support additional ongoing-service clients.
4. Potential capacity impact
If 800 hours of administrative capacity were released each year, that is equivalent to approximately:
100 eight-hour working days
That capacity could potentially be redirected towards:
Client-facing work.
New-business activity.
Adviser support.
Compliance reviews.
Follow-up activity.
Complex client cases.
Business development.
Improving existing processes.
The strongest return may therefore come not only from reducing administration, but from allowing advisers and support teams to spend more time on higher-value activity.
Before and after
1. Annual review monitoring
Before: Employees manually check spreadsheets, CRM reports, calendars and personal reminders.
After: The system monitors upcoming annual-review dates every day and automatically places clients into the appropriate workflow.
2. Client contact
Before: Review invitations are prepared and sent manually.
After: Clients automatically enter a scheduled communication journey based on their review date.
3. Client messages
Before: Clients may receive generic or inconsistent review communications.
After: Clients receive approved, personalised communications based on their adviser, service and review stage.
4. Follow-up
Before: Employees manually create reminders and chase clients who have not responded.
After: The system automatically sends reminders and creates tasks only when human intervention is required.
5. Information collection
Before: Updated client information is collected through email, telephone calls and separate documents.
After: Clients complete a secure digital circumstances-update form before their review.
6. Change identification
Before: Advisers or administrators manually compare current information with the previous client record.
After: AI prepares a structured summary highlighting material changes, missing information and areas requiring discussion.
7. File preparation
Before: Review files are manually compiled from multiple systems, emails and documents.
After: The workflow automatically prepares a structured adviser review pack using the information already collected.
8. Appointment creation
Before: Appointments may require several emails or telephone calls to arrange.
After: Calendar booking, confirmations and reminders can be integrated into the review workflow.
9. Post-meeting actions
Before: Employees manually create and track actions after the client meeting.
After: Agreed actions can be identified, assigned and tracked through a connected workflow following adviser approval.
10. Review visibility
Before: Management relies on spreadsheets and individual updates to understand review progress.
After: A central dashboard displays upcoming, completed, delayed and overdue reviews in one place.
11. Ongoing-service evidence
Before: Demonstrating that services have been delivered may require checking multiple systems and records.
After: Communications, review activity, client responses and follow-up actions can be captured in a more consistent audit trail.
Controls that should remain in place
A controlled annual-review workflow could include:
Adviser approval of all regulated advice.
Human review of AI-generated summaries.
Approved communication templates.
Communication-preference checks.
Role-based system access.
Secure client authentication.
Audit logs.
Data-retention controls.
Validation of review dates.
Human review of uncertain client information.
Vulnerability escalation procedures.
Restrictions preventing AI from independently recommending financial products.
Monitoring of inaccurate or outdated records.
Regular testing of automated communications.
Quality checking of extracted or summarised information.
Clear responsibility for outstanding client actions.
Automation should support the annual-review and advice process.
It should not replace professional judgement.
The potential business impact
An automated annual-review workflow could help an IFA move from manually managing every step of the review process to managing exceptions.
Clients could be contacted earlier and receive a more consistent service.
Administrators could spend less time sending reminders, checking spreadsheets and assembling review files.
Advisers could receive better-prepared client information before meetings.
Management could gain a clearer view of upcoming reviews, overdue activity and ongoing-service delivery.
The firm could also create additional capacity without immediately increasing headcount.
The result could be:
More consistent annual reviews.
Faster client preparation.
Reduced administrative effort.
Better client communication.
Improved adviser productivity.
Stronger oversight of ongoing services.
Fewer missed follow-up actions.
Greater capacity for future growth.
A more scalable ongoing-service model.
Could your annual-review process be automated?
Neuranet helps IFAs and financial-advice firms assess their existing annual-review process, identify unnecessary manual activity and create automated review journeys around their current CRM and business processes.