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High-Performance Banking Through Expert Testing

High-Performance Banking Through Expert Testing

digital banking, testing

In this case study, we explored the testing services Testhouse provided for an Islamic Core Banking Solution by a leading IT company in the Middle East. The solution utilizes AI, Machine Learning, and Big Data to enhance banking operations, transitioning from legacy systems to a more digital, fintech-enabled environment.

High-Performance Banking Through Expert Testing


  • System Integration Testing
  • User Acceptance Testing Support
  • Performance Testing
  • Security Testing

Problem Statement

  • Lack of structured approach to testing and risk mitigation
  • Inadequate infrastructure and expertise for load, stress, and endurance testing
  • Design and architecture flaws were discovered only in production, resulting in rework and customer dissatisfaction
  • Challenges in prioritizing regression test packs, leading to inefficient testing efforts and potential gaps in critical functionality
  • Insufficient security measures, raising concerns about potential vulnerabilities and data breaches
  • Lack of real-time visibility into testing progress and product quality for stakeholders


  • Designed a Risk-Based Testing Strategy by analysing the business risk and the functional/non-functional characteristics of the application
  • Leveraged the Inhouse Framework T-Perform to conduct load, stress, and endurance testing of the product covering 75+ key workflows
  • Rolling Performance Tests for every major code drop to identify the design and architecture flaws early in the life cycles
  • Classification of Regression Test Packs based on the business priority with clearly documented usage guidelines
  • Implemented SAST and DAST scans early in the development life cycle to identify security flaws
  • Implemented Real-Time Dashboards to provide real-time status on the product quality to stakeholders


  • 90% Schedule Adherence
  • 95% Business Risk Coverage
  • 99.99% Availability of Applications in Production
  • 20% Reduction in Cost of Quality