How would you use Counterfactual Explanations in a real-world scenario to improve model transparency?
Instruction: A hypothetical model approves when s=0.02D-0.01I+0.4F is at most 0.5. Initially D=50, I=50 and F=1. D and I are amounts in thousands; F is a verified historical flag that cannot be changed. Feasible changes require 40<=D<=50 and 50<=I<=70. Determine whether changing only D or only I can reach approval, find a feasible combined change, and state what this explanation does not guarantee.
This is a simplified model-explanation exercise, not a real credit policy. The model and threshold remain fixed for the calculation. Use only feasible input changes and do not change the verified historical flag.
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The initial score is 0.0250 - 0.0150 + 0.4 = 0.9, so the model rejects it. With I fixed at 50, reaching 0.5 requires D<=30, outside the allowed range. With D fixed at 50, it requires I>=90, also outside the allowed range...