Transaction Matching is a capability that automates manual and onerous cross-checking, or "tick-and-tie" processes used to ensure the completeness and accuracy of transactional accounting between systems of record.  It enables quick identification of transaction exceptions, allowing users to focus on corrective activities or evidencing of discrepancies. 

Transaction Matching, also referred to simply as Matching, is a capability used to sift through voluminous and disparate transactional data sets to find exceptions that account for imbalances between source systems. 

Transaction Matching enables users to craft matching rules using logical filters, create groupings based on similar transactional information, and compare multiple data fields to automatically match transactions.  This logic is business-user derived and does not require any software language or coding to configure.  Rules have a designated run order and can have varying levels of confidence or strictness.  Rules are easily maintained and updated over time as the transactional data changes.  Automating Transaction Matching will dramatically reduce the amount of time and effort needed to identify exceptions, allowing the consumer to focus on corrective activities or substantiating valid differences. 

Businesses use Transaction Matching to: 

  • Automate the comparison of transactional data between one or more source systems 
  • Identify missing or erroneous transactions 
  • Focus on exception management and investigation, reducing risk and improving financial data integrity 
  • Continually and proactively monitor transactions, eliminating rushed and hasty periodic reviews 

Transaction Matching facilitates several capabilities that manual processes cannot provide.  Users can review matched transactions in a fully personalized interface, add evidence in the form of comments and attachments, and approve matches as required. The same interface can show unmatched transactions, matches that contain amount discrepancies (variances), matches by confidence level, or every transaction in the data sets.  Sorting, filtering, and ordering are all available and easily configured per user requirements.  Users may create manual matches from the pool of unmatched transactions, provided the amounts are within business-established materiality limits.  Lastly, matched transactions, regardless of matching method, can be unmatched as necessary, placing the transactions back into the unmatched pool for reconsideration in subsequent matching rule processing.

To learn how to set up the Transaction Matching capability, refer to the implementation steps for matching.

The support and support match capabilites are not supported for new customers.