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AML (Anti-Money Laundering)

  • RegTech
  • Location
  • Test Automation

CONTEXT

Iceland-based AML software provider leveraging AI to help banks combat financial crime and improve productivity by detecting money laundering and improving customer due diligence

Challenges

  • Managing complex domain-specific flows with limited documentation.
  • Gaining knowledge of GraphQL APIs for effective testing.
  • Applied BDD methodology to API test automation.
  • Implemented a Behavior-Driven Development (BDD) approach for UI test automation.

Solution

  • Developed 207 UI test scripts and 67 API test scripts using BDD with Cucumber and Karate for automation.
  • Automated filter operations on dashboard columns and generated test data using APIs.
  • Conducted defect management and reporting, saving 400+ hours per release.

Value Delivered

  • Identified 139 UI defects and 58 API defects, improving product quality.
  • Enhanced coordination with the technical team and ensured seamless test case execution and reporting.
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