Published 13 May 2026· via Google Cloud Customer Stories· Customer story
Snowdrop: AI-assisted merchant reconciliation using Vertex AI + BigQuery
Snowdrop Solutions Ltd. · Finance · United Kingdom
+40%
accuracy
As reported by the source; not independently verified.
Summary
Snowdrop Solutions Ltd. is a financial services transaction enrichment company that helps banks and payment providers clarify merchant information in transaction data where trade names vary by region and business.
The company migrated its merchant reconciliation platform to Google Cloud to improve scalability, deploy faster in new regions, and support more accurate end-customer merchant information at larger transaction volumes.
The problem
- 01Merchant names in bank and transaction data often differ from the names customers recognize, making reconciliation and enrichment difficult at scale.
- 02Snowdrop needed to expand into new regions and onboard high-volume clients without long manual research and ingestion cycles.
- 03The company also needed a platform that could scale reliably across geographies while improving match accuracy.
What they built
- 01Snowdrop uses Google Places API and Google Maps Platform to gather localized merchant information and combines it with manually scraped website data for enrichment.
- 02It stores unstructured data in Cloud Storage and uses BigQuery as its data warehouse for scalable processing across regions.
- 03Vertex AI is integrated with Snowdrop's Merchant Reconciliation System (MRS) API to automate background research, add validation checkpoints, and improve merchant match accuracy.
- 04Google Kubernetes Engine and Cloud Service Mesh support scalable, lower-burden deployment and operations across regions.
- 05The article says Snowdrop is also planning to use Gemini for Google Cloud and AlloyDB for additional language handling, embeddings, and data processing capabilities.
Reported results
- 01Snowdrop reported a 40% improvement in data accuracy.
- 02Manual regional onboarding dropped from 90 days to a couple of weeks.
- 03Merchant-to-transaction match rate increased by up to 15%.
- 04Transaction processing scaled from 198 million per month to more than 2.1 billion per month.
- 05The company says it now has 100,500x more merchants in its system than before migration.
- Improved merchant match accuracy
- Expanded into new regions faster
- Accelerated regional onboarding
- Scaled transaction processing capacity
Source
How this deployment compares
Computed from the library · data 10 Nov 2026This is the only Snowdrop Solutions Ltd. deployment in the library. Its reported 40% increase is within the typical range (median 40% across 50 figures).
Snowdrop Solutions Ltd. in the library
The only Snowdrop Solutions Ltd. deployment in the library
Too recent to judgeFollow-through is judged once a record is 1 year old; this one is 6 months old.
Results against peers
40% increase is within the typical range
Across 50 quality & accuracy figures (all industries), the median increase is 40%; the middle half falls between 22% and 96%.
This recordMiddle half of peers
- Customer experience50 figures, all industries · middle half 20%–90%28%median increase
- Revenue & growth67 figures, all industries · middle half 15%–150%40%median increase
- Time & speed36 figures, Finance · middle half 39%–75%57%median reduction
Peer figures are as reported by their sources; percentage claims only.
How we checked this record
Evidence tier: supported
A credible source with a named customer, but not the organization's own account.
- Named organization
- Snowdrop Solutions Ltd.
- Who published the source
- The organization itself
- Deployment status
- Scaled Production (confidence 95%)
- Quantified result
- The source reports at least one figure
- Summary checked against source
- 5 / 5 agreement
Last re-checked 13 Jun 2026.