IRDAI proposes ban on insurers gating premium details behind personal-data requests

In a consultation proposal, IRDAI has asked insurers and distributors to show product features, premiums and quality information before collecting personal data. The draft also seeks standard disclosures, dark-pattern tracking and commission disclosure for policies above Rs 50 crore.

— Source publishedThu, 24 Sept, 2026, 12:42 IST·First seen Thu, 24 Sept, 2026, 14:17 IST·Source Medianama

What happened

IRDAI proposes banning insurance websites and distributors from requiring personal data before displaying product features, premiums and quality information.

Key facts

  • Rs 50 crore

Why this matters

Insurers and aggregators may seek partnerships or acquisitions in disclosure-tech, consent management and journey-analytics capabilities as dark-pattern monitoring and commission transparency requirements tighten.

What to watch

  • Publication of the final IRDAI regulation, implementation dates and whether the proposal applies equally to insurers, web aggregators, corporate agents, POSPs and embedded distributors.
  • IRDAI clarification on whether displayed premiums may be ranges or must be personalized quotes before personal-data collection.
  • Definition and required methodology for product-quality, claims, grievance and service disclosures.
  • Specific dark-pattern taxonomy, monitoring requirements, reporting cadence and penalties.
  • Industry consultation submissions from life, health and general insurers, aggregators and insurtech firms.
  • Early redesigns by major digital insurers or aggregators, especially removal of mobile-number gates before quote results.
  • Any enforcement actions or consumer complaints involving deceptive insurance lead capture and unsolicited sales calls.
  • Map every web, app, aggregator, call-center and embedded-insurance journey to identify points where phone number, email, DOB or KYC data are collected before premium visibility.
  • Build quote-first product pages with clearly separated indicative and final premiums, coverage limits, exclusions, riders, claim-service metrics and policy suitability disclosures.
  • Review lead-generation economics and revise attribution models for lower pre-consent data capture, higher contextual-media spend and potentially reduced remarketing reach.
  • Create standardized disclosure templates and machine-readable product data feeds for distributors, aggregators and bank/retail partners.
  • Audit UI patterns for forced registration, pre-ticked consents, misleading urgency, hidden exclusions and other dark-pattern risks; maintain evidence trails for compliance.
  • For large-ticket policies, prepare commission-disclosure workflows, intermediary contracts and sales-force scripts ahead of any Rs 50 crore threshold requirement.