Data Integrity

Accounting data is rich and contextual, but is user-entered, and therefore potentially open to manipulation and fraud. Banking data lacks context and meaning, but comes directly from a trusted source or a third party, and is immutable. Our Data Integrity product automatically matches these data sources for you so you don't have to. Data Integrity matches bank accounts and transactions reported in an accounting package against bank accounts and transactions reported in banking sources.

In principle this validation can support many use cases, e.g. lending decision-making (perhaps lenders have more confidence in lending to businesses with highly accurate books), fraud detection, and invoice financing.

How do we match data?

Data Integrity is based on one-to-one mapping between a bank transaction in the banking source and a bank transaction in the accounting source. The matching logic uses a multi-step approach that incrementally releases the mapping restrictions. This ensures the maximum accuracy and trustworthiness of the provided match results.

The transaction data used to compare in the logic are:

  • Transaction amount
  • Currency
  • Clearing Date
  • Description
  • Account data

For non-textual comparisons, equal values are compared (within a certain threshold).
For textual comparisons, a combination of Jaro-Winkler similarity and Overlap coefficient (with thresholds) is used.

In the event where the company has bank accounts with different currencies, those transactions will be matched with an accounting source with the same currency. For these companies, the matching percentage will be less accurate. This is on our roadmap to fix.

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