Methodology · v1.1

The Insu Score

A 0–100 ranking of Australian pet insurance products, with the formula on the table.

Most pet insurance "best of 2026" lists don't tell you how they're ranked. We do — formula, weights, sources, worked example. If you disagree with a weighting, the page tells you exactly which lever to pull. If we change the formula, the version below moves and the change is logged.

J By Jarrod, Editor · Reviewed May 2026

The four components, in detail

Coverage depth — 45%

The single biggest weighting, because the cheapest policy is irrelevant if it doesn't pay your claim. We score eight features from the current Product Disclosure Statement (PDS) of each insurer:

Feature	Weight (of 45%)
Annual benefit limit — the maximum payout per policy year	8
Reimbursement % — percentage of vet bills paid (e.g. 80%, 85%, 90%)	8
Excess flexibility — range of excess options offered, including $0	5
Dental cover — included, optional add-on, or excluded	5
Behavioural / alternative therapy cover	5
Routine care add-on availability (vaccinations, desexing, dental scaling)	5
Bilateral condition flexibility — does pre-existing on one side exclude the other?	5
Pre-existing condition treatment — temporary vs permanent exclusion, review-after-symptom-free period	4

Source: PDS as published on the insurer's site, last reviewed quarterly. Each insurer's review page shows the date its PDS was last read.

Affordability — 30%

The premium for a benchmark scenario, percentile-ranked across all insurers in the comparison set. The benchmark scenario for v1.0 is:

• 3-year-old male desexed Labrador, no pre-existing conditions, postcode 2000 (Sydney CBD)
• $15,000 annual benefit, 80% reimbursement, $200 excess

The cheapest insurer for this benchmark scores 30/30 on this component. The most expensive scores 0/30. Everyone else scales linearly between.

The benchmark is deliberately specific. We also compute and publish per-page percentiles for two secondary scenarios — an older dog (10-year-old Cavoodle, postcode 3000) and a cat (5-year-old domestic shorthair, postcode 4000) — but only the Labrador scenario feeds the headline Insu Score. Why one benchmark, not an average →

Trust signals — 15%

Five binary or scaled inputs about the insurer behind the brand:

• APRA-authorised underwriter (binary: yes/no — all the brands on this site pass, but we publish the underwriter name) — 3 of 15
• AFCA member (binary, by law all insurers are — we surface the AFCA membership number) — 2 of 15
• Years the brand has been operating in Australia (scaled: 0/5 if <2 years, 5/5 if 10+ years) — 5 of 15
• Underwriter stability (scaled: 5/5 if no underwriter change in the last 5 years, 2/5 if one change, 0/5 if multiple changes) — 3 of 15
• AFCA complaint rate (underwriter-level) — total complaints attributed to the brand's underwriter in the most recent AFCA Datacube release. Brands sharing an underwriter receive the same score on this sub-component. Why underwriter-level, not brand-level →

Customer experience — 10%

Two public review aggregations, equally weighted within the 10%:

• ProductReview.com.au — average star rating × log-scaled review count (so 4.2 stars across 800 reviews beats 4.5 stars across 12)
• Trustpilot — same calculation

If an insurer has fewer than 50 total reviews across both platforms, this component is set to "insufficient data" and the brand's overall Insu Score is shown with an asterisk.

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A worked example: Bow Wow Meow

Here's how the v1.0 score is calculated for one Tier-A brand. Numbers below are placeholders pending the first full data pass — we publish this page now so the formula is on record before the first review goes live.

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What this score doesn't tell you

The honest list of limits, because every methodology has them:

• Pet-specific loss ratios aren't in APRA data. APRA's quarterly general-insurance statistics don't break out pet insurance as its own class of business — pet sits inside "Other accident" or "Other direct" alongside several other product types. So a per-insurer "claims paid as % of premiums collected" number is not obtainable from APRA for pet specifically. We surface the APRA-authorisation status of each underwriter, but not a per-product loss ratio. If APRA changes its reporting structure to expose pet, we'll add a 5–10% weighting for it.
• AFCA data is at the underwriter level, not the brand level. AFCA publishes complaints by firm via an interactive Power BI dashboard at data.afca.org.au — there's no bulk CSV, and the per-brand pet insurance breakdown isn't published in any extractable format. What is public: total complaints per underwriting agency. For example, PetSure recorded 195 complaints in FY24-25; Auto & General recorded 3,032 (across all their general insurance products, not just pet). Our score uses these underwriter-level numbers — so brands sharing an underwriter (e.g. Bow Wow Meow + Bupa + Medibank, all PetSure) get the same value on this sub-component. Brand-level discrimination would be ideal but the data doesn't exist publicly.
• Premiums change. Insurers can adjust pricing quarterly. The affordability score uses the most recently scraped premium data; the date of that scrape is shown on each insurer's review page. We re-scrape on a quarterly cadence.
• The Insu Score is one signal, not a recommendation. It cannot account for your specific pet's breed-related risks, your financial situation, your appetite for excess vs premium tradeoff, or your relationship with your vet. General advice only — read the relevant PDS before purchasing.

Why one benchmark, not an average across many

An average across multiple pet profiles obscures the differences that matter. Insurer A might be cheapest for a young Labrador in Sydney but the most expensive for an older Cavoodle in regional Victoria. Averaging hides that. We pick one benchmark for the headline score, publish two secondary scenarios on each review page so you can see how rankings shift, and let you run your own scenario via the premium estimator (launching with the first review-page batch).

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Affiliate independence

Insu earns commissions from some insurers when readers click through and buy a policy. We disclose affiliate relationships on every page that contains an affiliate link, and we publish the full list at /about/.

The Insu Score is calculated independently of affiliate status. To prove it: once the first 15 review pages are live, this section will show a table of "Top 5 scoring brands" alongside a "Brands we have affiliate relationships with" list. If the two are heavily correlated, the score isn't worth its claim of independence. If they're not, we've earned the trust signal. Either way, you'll see the comparison openly.

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Version history

Future version notes (v1.1, v1.2…) will be appended above as we revise the formula. Score changes attributable to formula changes vs. data changes will be flagged.

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Disagree with a weighting?

The formula is opinionated. Some readers will weight affordability higher, others will care less about routine care, others will weight customer experience much more heavily.

If you disagree, this page tells you exactly which lever to pull. We're not hiding the weights, and we're open to challenges. Email hello@insu.au with what you'd weight differently and why — if multiple readers raise the same point with a real argument, the version history above will move.