AI System for Reviewing Point-of-Sale Transaction Exceptions

The problem

Point-of-sale events, returns, discounts and authorisation records arrive from different systems and event logs, preventing the team from viewing each case on a single timeline.

As a result, source links may be lost while the reasoned transaction review queue is prepared, the case may be referred to the wrong team and the basis for a technical decision may remain unclear.

An incomplete workflow may overlook cancellations, large discounts or repeated returns, while an unsuitable workflow could misinterpret a legitimate transaction as employee misconduct.

What we set out to improve

• Time taken for the draft reasoned transaction review queue to be ready for specialist review
• Correct referral of records involving cancellations, large discounts or repeated returns to the appropriate specialist queue
• Record of suggestions corrected or rejected by the point-of-sale operations manager

How the system works

1. 01 Retrieve point-of-sale event, return, discount and authorisation record data from authorised sources
2. 02 Verify the source, timestamp and record identifier
3. 03 Add the context of the relevant asset, user, store, vehicle or content
4. 04 Prepare a draft reasoned transaction review queue
5. 05 Compare the draft with technical rules and authority limits
6. 06 Check for exceptions: cancellations, large discounts or repeated returns
7. 07 Obtain the point-of-sale operations manager's approval, correction or rejection
8. 08 Write the input, suggestion, change and final decision to the audit log

Methods we used

• Source- and time-traceable data extraction for point-of-sale events, returns, discounts and authorisation records
• Structured output that constrains the reasoned transaction review queue fields according to technical rules
• An exception gate that separates cancellations, large discounts or repeated returns from workflow processing
• An authorised queue that presents evidence and suggestions together for the point-of-sale operations manager
• Duplicate transaction checks and a rollback record to address the risk of interpreting a legitimate transaction as employee misconduct

Where people stay involved

Data and security

Only fields required for the task are processed from point-of-sale events, returns, discounts and authorisation records. Source-system permissions are preserved, and personal, technical and security-sensitive data is minimised before being provided to the model. Every read, suggestion, human change and target-system action is written to the audit log.

Who this suits

Frequently asked questions