Explainability is where ML deals in banking, insurance and healthcare live or die. What SHAP actually computes, the per-decision worked example reviewers expect, and the trap of reading it as causality.
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A regulated customer asks: 'Why did the model deny this application?' Explain SHAP and how you'd deploy explainability.
Explainability is where ML deals in banking, insurance and healthcare live or die. What SHAP actually computes, the per-decision worked example reviewers expect, and the trap of reading it as causality.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
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