Technology and AI interview questions for insurance roles
89 questions from core to advanced: concepts, calculations, whiteboard diagrams, SQL, scenarios and behavioural. Answer out loud first, then reveal the model answer and example. Mark each one practised when you can answer it without looking.
Practised 0 of 89
Where can GenAI add value in insurance today?
- Customer service agents for quotes, renewals, claim status.
- Document extraction for claims and underwriting.
- Copilots for agents and underwriters; summarising medical records.
- Always with guardrails, human review for decisions, and DPDP-compliant data use.
What core systems do insurers run?
- Policy admin (Guidewire, Duck Creek, Majesco, TCS BaNCS), rating engine, claims, billing.
- Distribution portals and APIs, CRM, data warehouse.
- Trend: cloud PAS, low-code product configuration, microservices.
How would you control bias and errors in an AI underwriting model?
- Define permitted features; exclude protected attributes and proxies.
- Explainability for every decision; monitoring of approval rates by segment.
- Human override and appeal path; periodic validation with actuarial and compliance teams.
Design a motor quote API for aggregators. What goes in it?
- Request: registration number or make/model/variant, city, registration date, previous policy and NCB, claim history, cover choice, add-ons.
- Response: quote ID, validity, IDV range, premium lines (OD, TP, CPA, add-ons, GST), and any referral reasons.
- Errors: invalid vehicle, TP still active (for comprehensive), break-in needing inspection.
- Non-functional: response time, idempotency, versioning, consent and logging.