GenAI in Finance Software Testing CT-FT Practice Questions (Page 2)

Questions 6–10

1. 6application · medium

   A QA team is using GenAI to generate test cases for a new payment gateway. The team wants to ensure that the test cases cover edge cases such as invalid card numbers, expired cards, and insufficient funds. What is the best way to use GenAI for this?

   • ALet the GenAI tool generate test cases without any input, as it can infer edge cases from the system.
   • BAsk the GenAI tool to generate test cases based on the code, not the business requirements.
   • CUse the GenAI tool to generate test cases and then run them without review to save time.
   • DProvide the GenAI tool with a list of edge case scenarios and have it generate test cases for each.
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2. 7application · medium

   A fintech company wants to use GenAI to generate test data for a new credit-scoring application. The data must include realistic customer profiles with varied income levels, credit histories, and geographic locations. Which approach best addresses the need for realistic data while managing the risk of introducing bias?

   • AUse the GenAI tool to generate synthetic data from scratch, then use a subset of the generated data for testing without further review.
   • BAsk the GenAI tool to generate data that matches the distribution of the training data, and rely on the tool's built-in fairness checks.
   • CGenerate synthetic data with GenAI, then have a domain expert review the data for realism and bias before using it in tests.
   • DUse only real historical customer data for testing, as synthetic data is never realistic enough for finance applications.
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4. 8application · medium

   A bank is planning to use GenAI to generate realistic network traffic patterns for performance testing of its online banking portal. What is a key consideration when using GenAI for this purpose?

   • AGenAI can generate traffic patterns that are indistinguishable from real user behavior, so no further tuning is needed.
   • BPerformance testing with GenAI eliminates the need for load testing tools.
   • CGenAI can help create diverse and realistic load scenarios, but the generated patterns must be validated against known production behavior.
   • DGenAI should only be used for functional testing, as it cannot be applied to performance testing.
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5. 9foundation · medium

   Which of the following is a challenge when using GenAI for finance testing?

   • AEnsuring the generated test cases align with regulatory requirements.
   • BGenAI requires no human oversight in finance testing.
   • CGenAI always produces unbiased test cases.
   • DGenAI cannot generate any test data for financial applications.
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6. 10foundation · medium

   What is a key risk of using GenAI in finance testing related to data privacy?

   • AGenAI may inadvertently include sensitive customer data in generated test data.
   • BGenAI is not subject to data protection regulations.
   • CGenAI eliminates the need for data anonymization in testing.
   • DGenAI always encrypts all test data, so there is no privacy risk.
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