Three records for one client
Search the back office for a client and you find three entries: one from when they first enquired, one created by a provider feed, and one a new administrator added last year without spotting the others. Plans are split across them. The review date is on one, the latest address on another.
Reports built from this data are unreliable. The ongoing service client count does not match the fee income. Mailings go to old addresses. Nobody trusts the numbers, so people keep their own spreadsheets, which makes it worse.
Every new member of staff learns the workarounds: which record to trust for addresses, which for plans, which custom field actually means the review month. That knowledge is never written down, and it leaves with them.
How back office data gets this way
Every back office system relies on people entering data consistently, and over years they do not. Feeds from providers create plans or even clients when they cannot match existing ones. Acquired client banks are imported in a hurry. Staff come and go, each with their own habits for naming and filing.
- Duplicate clients from enquiries, feeds and imports.
- Plans attached to the wrong client or to no client.
- Clients with no service level, adviser or review date recorded.
- Contact details updated in email but not in the system.
- Custom fields used differently by different people.
None of this is anyone's fault in particular. But without a deliberate clean-up and ongoing checks, it only accumulates.
Where bad data bites
| Data problem | Where it shows up |
|---|---|
| Duplicate clients | Reviews missed, split holdings, double contact |
| Orphaned plans | Valuations and income not linked to anyone |
| Missing service level | Client left out of review scheduling |
| Stale address or email | Letters and statements not received |
| Inconsistent fields | Reports that do not add up |
It also blocks every automation project the firm might want. Review scheduling, fee reconciliation and client portals all need clean data to work, and they expose the mess quickly when it is not.
Our clean-up method
- We take a read-only extract of your back office data through its API or export, so nothing changes during analysis.
- Checks run for likely duplicates using names, dates of birth, addresses and plan numbers, with a confidence level for each pair.
- Orphaned plans, clients missing required fields and inconsistent values are listed.
- Your team reviews proposed merges and fixes in a simple approval screen. Nothing is changed without a person agreeing.
- Approved changes are applied through the back office's own tools or API, in batches, with a log of every change.
- Ongoing checks then run weekly, flagging new duplicates, missing fields and feed-created plans for someone to resolve.
- We agree simple data entry rules with your team, and add validation where the system allows, so fewer problems are created.
Merging client records can be sensitive, particularly for joint clients and families. Those decisions stay with your staff. Our job is to find the candidates and make applying the decisions safe and traceable.
What your data looks like afterwards
One record per client, with plans in the right place and service levels and review dates set. Reports can be trusted, so the parallel spreadsheets can go. Future automation projects start on solid ground. And the weekly check stops the slow drift back to where you started.
Staff also stop working around the system. When the record they open is the only record, and it holds the right plans and dates, they update it rather than a side spreadsheet, which is what keeps it clean from then on.
Is your back office in this state?
- Searching for a client returns more than one record.
- Plans appear that are not linked to anyone.
- Your client counts do not agree with your fee income.
- Staff keep their own spreadsheets because they do not trust the system.
- You are about to automate something and worry about the data.