FilmPass & CoResearch & education
05 / HOW PAYMENT DATA WORKS

A ticket. A decision.
A possible data journey.

An unnamed, fictional example. Learn what is generated, what a business may be able to query, and which extra steps are needed for a CRM record.

Illustrative mechanism

One checkout. Different records.

One checkout. Different records.CHECKOUT → ORDER RECORD → DEVICE SIGNALS → TRACE THE LINKS. Collection, access and later use are separate questions.CHECKOUTORDER RECORDDEVICE SIGNALSTRACE THE LINKS
Collection, access and later use are separate questions.Explore this page →
On this page
How to read this explanation. The technical explanation describes how records can be linked and reused when the stated access, identifiers and integrations are present. The names, amounts and sample records are invented to demonstrate the mechanism. The examples do not reproduce private case records. Provider-specific field availability and each assumed step are identified separately.
Compare accountable use with a fictional commercial-misuse scenario →
Step 1 of 6
ILLUSTRATIVE EVENT

A customer buys a ticket.

A checkout can create an order and payment record. The demonstration uses invented identifiers and a £20 purchase.

ILLUSTRATIVE RECORD · NOT REAL CUSTOMER DATA
{"order":"order_demo_01","value":"GBP 20.00"}
The scenario identifies ticket events, payments and fraud checks as separate steps.

A route with purpose checks

This first animation requires the purpose check before presenting an authorised-use scenario. Software could still move data without that authority; the matching example below separates technical possibility from justified use.

Purpose and authority remain unresolved in the initial scenario.

Fraud prevention

Signals help assess whether a payment could be unauthorised or fraudulent. A risk score represents the system’s assessment of a transaction.

Reporting, including Sigma

An authorised business can query data available to its account. Only exposed fields can be selected; the available fields and account scope define the query.

A separate CRM integration

An export or integration can map selected fields into a receiving system. A reliable identifier enables matching. Suitable permissions and a justified purpose must be assessed separately.

A redemption can be a ticket-system event with no new payment. Neither a redemption nor a purchase automatically proves that fraud data reached a CRM. The example demonstrates a possible configured route.
What do the terms mean?
SME
A small or medium-sized enterprise.
CRM
Customer relationship management: a system for customer records and interactions.
Sigma
Stripe’s reporting product for querying available account data. It is not itself proof that information was sent to a CRM.
Matching identifier
A value, such as a customer ID, used to associate a record with the correct customer. Matching can fail or join the wrong person, so it must be checked.
Raw signals and derived results
A device observation is an input; a payment-risk assessment is a result derived from inputs. Access to a result does not establish access to every input.

Why transparency matters for SMEs and closed user groups →

Tracing a transfer through its records

  1. Which field was available to which account, at the relevant date?
  2. Which query or export selected it, and where is the export log?
  3. Which integration transmitted it, to which destination?
  4. How was it matched, and what did the receiving CRM actually store?
  5. What purpose, authority, notice and retention rule applied?

Technical sources

Official sources checked 6 October 2026. Current documentation may differ from historic versions.

Example reporting query

Illustrative query for account reporting. The fields available depend on the authorised account and schema. This example selects exposed payment fields.

SELECT id, customer_id, outcome_risk_level
FROM charges
ORDER BY created DESC
LIMIT 10;
ONE CUSTOMER JOURNEY / SEVERAL LINKED RECORDS

How context can follow a record.

The important question is which identifiers survive each step. A payment, its merchant metadata and a security assessment can concern the same transaction while remaining different records with different access rules.

1. Collection

A checkout may send payment details and trigger separate device or activity requests. Stripe documents periodic requests to m.stripe.com. Trace each request and its fields separately.

2. Merchant context

A merchant can attach custom metadata, such as an internal order reference, to supported objects. A tag can add context; it is not necessarily a unique person identifier. Metadata does not automatically copy to every related object.

3. Selected reporting

Sigma can query available account data and join customer and charge records. A selected export may retain a usable reference. The query uses exposed account fields; internal device and activity telemetry has its own collection and disclosure records.

Linking records does not require one network request. A single event can generate separate records that retain a common reference or a distinctive combination of attributes. In the teaching example, the linking information is deliberately retained so readers can see how a later system could reconnect the records. Collection and transfer records identify the fields available at each stage.

Collection and transfer records identify the fields available at each stage. A device identifier is not a company registration number or automatically a payment-account identifier. Establish the scope and meaning of each field before comparing it.

Stripe: advanced fraud detection ↗ · Stripe: metadata and copying rules ↗ · Stripe: transaction and customer joins ↗

INTERACTIVE EXAMPLE / INVENTED RECORDS

When can an exported record be linked to a person?

Try the matching conditions using merchant report fields and an invented contact lookup. The records in this control are invented.

Selected export

Invented payment reference and the selected matching field.

Receiving lookup

A lookup and account scope are assumptions that must be demonstrated.

Matching result

Matching capability and lawful authority are different questions. The demonstration can show a technically possible match even when the authority switch is off. A real match can be wrong; source identity, collisions and accuracy still need checking.

A pseudonymous or hashed identifier may remain linkable when another party has the necessary matching information. Merely removing a name does not guarantee anonymity. A common campaign tag alone usually identifies a group, not a unique person. Combinations of fields can create further identifiability risks, which this simplified example does not model.

ICO: pseudonymisation ↗ · ICO: indirect identification ↗

Follow the invoice and accounting trail →
TIMESTAMPS, PAYLOADS & RE-IDENTIFICATION

How a record can remain linkable after a name is removed.

This educational example demonstrates a possible matching mechanism using retained timestamps and identifiers.

Removing a name or replacing a card number does not automatically remove every way to recognise a person. Retained identifiers, order references or sufficiently distinctive attributes may permit a link if the recipient has the corresponding information.

A precise timestamp retained in two copies of an event can contribute to matching them. Combined with an order reference, amount or other distinguishing attributes and an available identity record, it may allow a person to be recognised after a name is removed. Time alone is not always unique; clock differences, retries and concurrent events must be handled. ICO: pseudonymisation and additional information ↗

Read the structure before drawing a link.

Check whether timestamps, identifiers and activity values belong to the same event. Separate arrays or columns are not automatically aligned. Record time zones, repeated events, missing values and the meaning of each identifier.

A device identifier, merchant account identifier and company registration number answer different questions. Establish their scope before using them to join records.

How an audit could trace a real transfer

A complete request capture could show fields sent together, destination and time. An export schema, executed query, matching recipient record and access log could then show which fields moved and how they were linked. A timestamp match alone does not supply that end-to-end evidence.

Stripe’s documentation describes periodic fraud-signal requests and states that advanced signals are used for fraud/security rather than advertising. Sigma’s documentation describes transactional reporting and CSV export of exposed account fields. Check the product configuration and documentation applicable to the event being examined.

Advanced fraud documentation ↗ · Sigma documentation ↗

Fictional teaching example

See what survives the removal of a name.

Checkout record
10:00:00.123
order_demo_17
Other record
10:00:00.123
identity unknown

The timestamp is a candidate link.

This control uses invented records to explore a transfer’s fields, purpose, authority, recipients and retention.