kb/methodology/tie-breakers.md

Tie-Breaker Rubric — When Policies Score Equal

The scorecard's 0–100 grade collapses 6 sub-scores. Two policies can land at the same overall score with very different shapes. This document defines the objective tie-breakers the system applies when overall scores are within ±2 points, ordered by buyer impact.

The intent: never tell a buyer "these are equal" — always have a defensible objective reason one wins.

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Tier 1 — Insurer Quality (applies across portfolio)

These metrics belong to the insurer, not the policy. If two policies come from different insurers, these dominate.

#	Metric	Source	Tie-breaker rule
1	Claim Settlement Ratio (most recent FY)	IRDAI Annual Report	Higher wins. Cutoff: <90% disqualifies regardless of other strengths.
2	Complaints per 10,000 policies	IRDAI Grievance Statistics	Lower wins. The insurer's own published metric reveals operational quality.
3	Repudiation rate	IRDAI public data	Lower wins. A 5% point swing here matters more than a 5% swing in CSR.
4	Average claim turnaround time	Insurer's IRDAI filings	Faster wins. Cashless TAT ≤2h is the gold standard.

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Tier 2 — Network Quality

#	Metric	Tie-breaker rule
5	Cashless network density in user's city	More hospitals within 10km radius wins. Not raw count — geographic density.
6	Quality of top-3 hospitals in network	If both networks include AIIMS / Apollo / Manipal / Fortis flagship branches, equivalent. If one excludes top-tier, the other wins.
7	Network depth in tier-2/3 cities	For non-metro users, presence in town's biggest 2 hospitals is decisive.

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Tier 3 — Cost-vs-Cover Trade Quality

#	Metric	Tie-breaker rule
8	Price per ₹L of sum insured at user's age	Lower wins. Calculated from real premium quotes for matching profile.
9	NCB accrual pace + cap	Higher pace AND higher cap wins. E.g., 50%/year capped at 100% beats 25%/year capped at 50% for buyers who stay claim-free.
10	Restoration benefit liquidity	"Unlimited automatic restoration" beats "one-time per year" beats "available on full exhaustion only".
11	PED waiting reduction options	Some policies let you pay extra to drop PED waiting from 36→24 months. That option is itself valuable for diabetic / hypertensive buyers.

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Tier 4 — Customer Experience Signals

These come from outside the policy wording — Reddit + MouthShut + InsuranceDekho ratings.

#	Metric	Tie-breaker rule
12	Reddit sentiment skew (last 12 months)	"Mostly positive" beats "Mixed" beats "Mostly negative" claim-time stories.
13	MouthShut / PolicyBazaar star rating	Higher wins. Volume matters — a 4.6 over 500 reviews beats a 4.8 over 12 reviews.
14	Specific named-creator coverage on YouTube	If trusted creators (Ditto Insurance, Beshak, Subhanker Saha) have reviewed and rated positively, that's a tie-breaker.
15	Press: regulatory actions in last 24 months	Any IRDAI show-cause notice in last 24 months breaks the tie negative.

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Tier 5 — Specialised Match

Applies only when the user has a specific need flagged in their profile.

Profile flag	Tie-breaker
Maternity planned next 24 months	Policy with ≤24-month maternity wait wins.
Surgery planned within 12 months	Policy with no specific-disease wait for that condition wins.
AYUSH preference	Policy with explicit AYUSH coverage limits stated (vs "up to SI") wins.
Senior parents	Policy that allows porting in mid-term + has senior-specific rider wins.
Diabetic buyer	Policy with day-1 diabetes coverage option (e.g., HDFC Energy) wins for that buyer even if generic score lower.

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Application order

When the system needs to break a tie between two policies:

1. Walk through Tier 1 first — insurer quality is the most predictive single metric of claim experience.
2. If still tied (same insurer, two products), drop to Tier 2 (network).
3. Continue down the tiers.
4. If still tied after all 5 tiers, the tie is genuine — surface both and let the user pick on subjective preference (brand, ease of website, app reviews, etc.).

The "all-else-equal" framing is honest: in reality, two health policies rarely tie. Surfacing the tiered breakdown gives the buyer a defensible reason for the recommendation order.

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What we explicitly DON'T use as tie-breakers

• Brand recognition alone. "I've heard of HDFC ERGO" is not a tie-breaker.
• Commission rate to the broker / aggregator. The whole platform is built on not letting this influence ranking.
• Recency of policy launch. New ≠ better.
• Glossy marketing ("award-winning", "most trusted", etc.). Awards are often paid placements.

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Implementation contract

The tie-breaker logic lives at backend/scorecard.py::tie_break(policy_a, policy_b, profile) (TBD — to be implemented). It returns a structured comparison: {winner, reason_tier, reason_text, source}. The frontend renders this when two policies have grades within 2 points and the user has both selected for comparison.