Concur Support & User Guides

12 November 2025 | 9:12 am

Impact as Reported: Customers using the American Express GL1025 file for credit card transaction feeds may have experienced issues with incorrect transaction labeling for transactions posted on or before September 2. Affected users may see payment transactions displayed to employees either with no vendor name or with an "unknown" vendor, while certain fee types may be incorrectly classified as cash advances. Root cause: The credit card vendor for the impacted customers sent incorrect transaction data to SAP Concur. SAP Concur engineering worked with the vendor to identify the impacted data set and apply the necessary corrections. Please refer to your support case for any additional information on individual impact. If you continue to have issues please create a support case. Corrective Actions: Code was written to identify and fix the incorrect data. A tool was developed that can now be used to more readily fix data on request.

12 November 2025 | 2:26 am

Impact as Reported: New Concur Travel bookings dropped up to 50 % below expected level for 31 minutes in the US2 Data Center. Affected users may have experienced latency, no response, or errors when attempting to perform travel searches or complete travel bookings. Root cause: An application tier supporting travel related workflows experienced performance degradation, resulting in intermittent time outs that impacted users ability to search or book. The Incident Response Team identified an issue with the service infrastructure configuration allocating insufficient memory to process increased load, causing application nodes to fail life checks and be taken out of service, reducing the available processing capacity. Service was restored by increasing the affected application tier capacity. Corrective Actions: The following corrective and preventive actions were identified: Increase the application tier baseline capacity Increase the memory allocated to the tier nodes Review service dependencies and remove unnecessary checks Review auto-scaling configurations for the impacted service to improve scale up parameters to better respond to load changes.