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| The Shift Toward AI-Enabled Credit Card Platforms |
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The credit card industry is undergoing a profound transformation as digital payments become more intelligent, secure, and touchless. Generative AI is reshaping how credit card issuers operate, introducing automation, prediction, and intelligent validation across the QE lifecycle to enable faster rollout of new products into the market.
Core QE capabilities enabled by AI include:
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Robust test data generation
reflecting real-world credit card usage patterns |
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Self-healing automation
for UI, API, and workflow testing |
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Fraud simulation testing
to validate fraud detection readiness |
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Predictive quality analytics
using defect data, logs, API responses, and performance metrics |
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PCI DSS security validation
to support compliance and auditability |
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| These advancements establish AI as a force multiplier in credit card Quality Engineering, strengthening speed, intelligence, and reliability in testing. |
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| Powering Strategic AI Adoption to Accelerate the QE Lifecycle |
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As a strategic partner with NatWest, Infosys delivers advanced automation through AI-based solutions and Agentic AI frameworks across various LOBs. Teams have identified opportunities to implement AI models and tools that accelerate the QE lifecycle.
Leveraging AI with RPA UiPath solution gave us the required impetus to get the novel
‘Credit Card Builder’ product faster into the market, leading to quicker onboarding of customers for the bank.
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| Our Objectives: |
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Streamlining the QE lifecycle by leveraging
AI-driven automation to reduce manual effort |
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Accelerating testing cycles by shift left approach to meet the
Go-live timelines |
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Creating a scalable framework that can be reused for future testing requirements |
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Eliminating operational bottlenecks for bringing testing efficiencies |
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| CHALLENGES |
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| Testing credit card systems presented significant obstacles: |
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| No domain-specific test cases generated in the client in-house tool |
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Effort-intensive automated script creation for E2E testing |
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Vendor lock-in for client-side application |
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Manual effort required in Selenium to Playwright code conversion |
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| SOLUTION |
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| Automated Test Life Cycle (ATLC) with CRAG & Web Voyager |
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| We implemented a comprehensive solution that addresses each challenge: |
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| RESULTS |
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| Our solution delivered significant improvements across key metrics: |
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By combining innovation with execution, we've set a new benchmark for automated testing in financial systems.
Thank You and Best Regards,
<Sign off details go here>
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Copyright © 2026 Infosys Limited
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