Structured Address Data: Why Payments Firms Should Clean Client Addresses Now

Structured address data means a postal address split into defined fields, such as street, building number, town, postcode and country, rather than a free-text block. Payment messages are moving to structured addresses, and the Bank of England's forum summary of 4 November 2026 shows the change is close enough that readiness is now the issue. It applies to CHAPS and to cross-border payments sent through Swift.

What did the Bank of England say?

The Bank said that, following Swift's decision to delay its Standards Release 2026 over concerns about readiness for removing unstructured address fields, it also delayed the November 2026 RTGS Standards Release. To realise the benefits of structured addresses and avoid the same position in future, it wants early industry views on mandating structured addresses through the CHAPS rulebook before Swift and CHAPS formally retire unstructured fields.

Forum members supported exploring this further, noted the work already done to prepare, and pointed in particular to dependencies on customers completing creditor address fields.

The same forum discussed contingency arrangements for a Swift outage, where members highlighted the limits of manual processing and the benefits of automation. Clean, structured client data makes any automated fallback easier to run.

What does structured address data look like?

The example below is made up. It shows one address as free text, the way it often sits in client records, and then split into fields.

Illustrative address and field names only.

Field	Value
Free text	Flat 4, 12 Example Street, Exampletown EX1 2AB
Room or flat	Flat 4
Building number	12
Street name	Example Street
Town name	Exampletown
Postcode	EX1 2AB
Country	GB

Why does structured address data fall on operations teams?

• **Addresses come from clients.** They arrive at onboarding, often as free text, and are rarely revisited.
• **Gaps show up late.** A missing town or postcode only becomes a problem when a payment is rejected or delayed.
• **Fixes need the client.** Many corrections need a request to the client, which takes time.
• **Country is often missing.** A country left blank, written in full or misspelt needs mapping to a standard code.

How can workflow automation help clean address data?

The checking is routine, and it breaks into four steps.

• **Split what is clear.** Where an address has a clear building number, street, town and postcode, the agent proposes the fields.
• **Flag what is not.** Ambiguous or incomplete records go on a list for a person to review.
• **Draft the client request.** For records only the client can fix, the agent drafts the request, and a person approves it before it is sent.
• **Record the change.** Old value, new value, who approved it and when.

Our client onboarding files workflow checks documents and details against your checklist and drafts requests for anything missing, and a person approves every request before it goes to a client. Our article on CHAPS settlement hours covers another change from the same forum, and KYC onboarding automation covers onboarding checks.

Where should a payments firm start?

Run a count of client records with incomplete address fields and decide which need a client request. Our Workflow Automation London team can set up that check on your data in a 14-day Proof Run. This article summarises a Bank of England publication and is not advice.