Transaction Enrichment With Merchant Classification

Automate transaction enrichment to better understand your customers

This Solution Accelerator has two purposes. First, it shows how the lakehouse architecture enables banks and open banking aggregators to address the challenge of merchant classification. Second, it shows you how to use ML to enrich transaction data with contextual information — including store brand and category for downstream use cases, such as customer segmentation or fraud prevention.

  • Save days of dev time by labeling the initial source-of-truth data
  • Gain new customer insights from contextual information
  • Build hyper-personalized experiences with transaction data
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Transaction enrichment with merchant classification case study


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