About Revolut


improvement over industry standards within one year of Couchbase


saved with Couchbase


of fraudulent transactions caught


    • Fraudsters are evolving to beat traditional predetermined fraud detection rules
    • A mission-critical application required consistent high availability and high throughput for its rapidly growing customer base
    • On average, financial fraud costs institutions between 7-8 cents out of every $100


    • Sherlock’s high speed caching enabled machine learning algorithms to continually learn and update rules – catching 96% of fraudulent transactions
    • Sherlock evaluates transactions for signs of fraud in under 50 milliseconds for Revolut’s 12+ million customers
    • Within the first year in production with Couchbase, a 75% improvement over industry standards saved more than $3M
For our customers, the loss of $100 can mean the difference between a pleasant holiday and an experience filled with frustration and resentment. Couchbase has never failed us or our customers.

Dmitri Lihhatsov Financial Crime Product Owner, Revolut

Maccabai logo Use case

  • Fraud detection
  • User profile store
  • Digital communication
  • Caching

Maccabai logo Key features

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