Pet Insurance Ratings: What Stability Signals for 2026

AM Best doesn’t “affirm with stable outlook” because it’s feeling generous. It does it when an insurer has shown—on paper and in risk controls—that it can keep promises under stress.

That’s why the December 2025 update on Independence American Insurance Co. (IAIC), a major pet health insurer, matters beyond one carrier’s headline. AM Best removed IAIC’s ratings from “under review with developing implications” and affirmed an A- (Excellent) Financial Strength Rating with a stable outlook, after the company renegotiated its pet insurance quota share reinsurance and received an additional $125 million capital contribution from its parent in Q3 2025.

If you work in insurance, distribution, insurtech, or you’re a risk leader watching pet insurance growth, this is a real-time case study in how confidence gets rebuilt: capital, reinsurance structure, operating performance—and increasingly, AI-driven risk assessment that makes those levers more transparent and defensible.

What AM Best’s action actually signals (and why it’s timely)

Answer first: Removing a rating “under review” signals that the uncertainty driving the review has been addressed well enough for the agency to return to a normal monitoring posture.

In IAIC’s case, AM Best points to two specific actions that resolved the “developing implications” period:

• Reinsurance renegotiation and re-implementation of the pet insurance quota share contracts (effective July 1, 2025 for the re-implementation)
• A $125 million capital infusion from the parent company, Independence Pet Holdings, Inc.

That’s the mechanical story. The strategic story is bigger: pet insurance is scaling fast, and scaling fast breaks things. It stresses:

• Reserving discipline (especially with changing veterinary pricing)
• Underwriting consistency across acquisitions
• Reinsurance structures that can unintentionally spike net premium retention
• Regulatory scrutiny when growth outpaces control maturity

In December—when many carriers are locking 2026 plans and boards are asking “where are we exposed?”—a rating agency affirmation functions like a market signal. Not a guarantee, but a credible third-party read: this insurer’s balance sheet and risk governance cleared a high bar.

Reinsurance, capital, and BCAR: the “trust stack” behind the headline

Answer first: The rating reaffirmation hinges on the insurer’s ability to support growth with capital strength and a reinsurance structure that produces stable, explainable net risk.

AM Best called IAIC’s balance sheet “very strong,” highlighting liquidity, an investment portfolio that supports the assessment, and a lack of financial leverage (no debt in its structure). It also noted continued capital and surplus growth into Q3 2025.

Why BCAR matters in pet insurance

AM Best explicitly references Best’s Capital Adequacy Ratio (BCAR)—a key lens for how well capital covers the company’s risk profile. The RSS update notes:

• BCAR was strong at year-end 2024, but declined due to a refiling of 2024 annual statements to reflect a deposit account on reinsurance contracts effective Jan. 1, 2024.
• BCAR later improved to the “strongest level” after the re-implementation of reinsurance and the $125M contribution in Q3 2025.
• BCAR is projected to remain at the strongest level for 2025.

Here’s my take: for fast-growing pet carriers, BCAR volatility is a warning light. It doesn’t always mean “trouble,” but it does mean the insurer needs to explain—cleanly—how contract structure and accounting treatment influence net risk.

Where AI fits into reinsurance and capital planning

AI isn’t a replacement for actuarial work or rating agency models. But it’s becoming the practical glue that helps carriers keep their “trust stack” coherent across underwriting, claims, finance, and reinsurance.

In pet insurance, AI can support this by:

• Improving exposure clarity: entity-level views of breed, age, geography, coverage design, and channel mix—especially post-acquisition.
• Reducing volatility in net performance: earlier detection of claim severity drift by clinic network, region, or procedure category.
• Stress-testing reinsurance structures: simulation of net retention under different loss severity and inflation scenarios (more on inflation below).

When your reinsurance structure changes mid-year, you want to answer one question quickly: Did we just change our risk, or only our accounting and premium reporting? AI can make that analysis faster and more consistent.

Pet insurance growth is real—so are the operational risks

Answer first: Pet insurance is expanding through acquisitions and partnerships, and that growth creates integration risk that has to be actively managed.

AM Best points out that IAIC has grown premiums in each of the past five years, driven by acquisitions and organic growth. It also notes that reinsurance contracts caused a substantial increase in net premiums in 2024, with net premiums expected to decline slightly in 2025 after re-implementation of reinsurance agreements.

The company’s acquisition pace is notable:

• 2022: acquired Crum & Forster’s pet insurance business
• 2023: bought cat health insurer Felix
• 2024: acquired Pets Best

It also operates via partnerships and brands (including white-label and co-branded offerings), such as ASPCA, Figo (including Costco sales), Pets Plus Us (Canada), AKC Pet Insurance (via Pet Partners), and 24 Pet Watch.

Why partnerships and white-label products complicate risk

White-label distribution can grow premium fast. It can also dilute underwriting discipline if product configurations multiply without tight governance.

Common failure modes I’ve seen in fast-scaling insurance programs:

• Too many plan variants (limits, coinsurance, waiting periods) that confuse customers and complicate claims adjudication
• Inconsistent underwriting rules across channels
• Marketing promises that don’t match policy reality (a complaint and regulatory magnet)
• Claims leakage when documentation standards vary by channel or vendor

That’s not an argument against partnerships. It’s an argument for control systems that scale as fast as distribution.

AI’s practical role in acquisition integration

In the “AI in Insurance” series, we’ve talked about AI in underwriting and claims automation. Here’s the acquisition-specific twist: AI is most valuable when it helps you standardize decisions across legacy stacks.

For pet insurers integrating multiple books, AI can:

• Normalize medical coding and invoice line items across different claim systems
• Flag outlier claim patterns by provider or region (potential fraud or billing anomalies)
• Detect shifts in loss ratios by cohort (new business vs. renewal, legacy brand vs. acquired brand)
• Power customer communications that reduce avoidable disputes (better explanations, faster document requests)

The aim isn’t “more automation.” It’s more consistency—which is exactly what regulators and rating agencies reward.

Underwriting and claims: where AI builds transparency (not hype)

Answer first: AI improves pet insurance credibility when it produces decisions that are explainable, repeatable, and auditable—especially in underwriting and claims.

AM Best’s update mentions IAIC’s positive operating earnings in 2024 and through Q3 2025, with net income of $44.3 million through Q3 2025 driven by strong underwriting and investment gains.

Operationally, underwriting and claims are where pet insurance either earns long-term trust—or loses it quickly.

The real constraint in pet insurance: claims severity inflation

Veterinary costs have been rising due to higher labor costs, specialty care expansion, and more advanced diagnostics. Even when frequency is stable, severity can creep.

AI helps here in a very specific way: trend detection at a granularity humans can’t sustain manually.

Examples that matter:

• Procedure-level severity drift (e.g., imaging, orthopedic surgery, oncology)
• Region-level pricing shocks (a metro area where specialty clinics consolidated)
• Benefit design interactions (how deductibles and coinsurance change behavior)

When you catch these early, you can adjust pricing, tighten underwriting, renegotiate provider relationships (where applicable), and set reserve expectations before the problem shows up in annual statement lag.

Fraud detection that doesn’t punish honest customers

Fraud is part of every insurance line, and pet is no exception (altered invoices, duplicate billing, misrepresented pre-existing conditions). The trap is building controls so blunt that they slow down legitimate claims.

A better approach is a layered AI model:

1. Triage model to route claims by complexity and risk
2. Document understanding to read itemized invoices and vet notes consistently
3. Anomaly detection to surface unusual patterns (provider, customer, timing)
4. Human review reserved for the small percentage of claims that truly need it

That structure supports what rating agencies care about: reliable operations that can handle volume without degrading customer outcomes.

Snippet-worthy reality: In pet insurance, trust isn’t built by paying every claim instantly. It’s built by paying the right claims quickly—and explaining the hard ones clearly.

What this means for pet insurance innovation in 2026

Answer first: The next phase of pet insurance growth will reward carriers that can prove stability—through capital strength, disciplined reinsurance, and AI-enabled governance.

Rating agency actions like this one ripple outward. They influence:

• Reinsurance negotiating leverage
• Partnership conversations with affinity brands
• Distribution confidence (agents, brokers, embedded partners)
• Regulatory posture and market conduct risk

For 2026, I expect “innovation” in pet insurance to look less like flashy features and more like operational credibility:

• More rigorous model governance for AI in underwriting and claims (audit trails, bias checks, change logs)
• Clearer customer communication to reduce complaints and rescissions
• Product simplification where complexity isn’t paying for itself
• Tighter feedback loops between claims data and pricing updates

A quick checklist for insurance leaders evaluating AI in pet insurance

If you’re buying or building AI capabilities, ask these questions before you sign anything:

• Can we explain model outputs to a regulator, a rating agency, and a customer? If not, it’s a risk.
• Does the system support reinsurance reporting needs? Quota share structures demand clean, consistent data.
• How fast can we detect loss trend drift? Weekly is better than quarterly in a fast-moving line.
• What happens when we acquire a new book? If integration takes 12 months, your model insights will be stale.
• Can we measure impact with real numbers? Claim cycle time, leakage reduction, complaint rate, loss ratio stability.

What to do next if you’re building trust in a growing line

AM Best’s IAIC update is a reminder that stability isn’t a branding exercise. It’s engineering: reinsurance structure, capitalization, disciplined growth, and operations that don’t fall apart when volume spikes.

If you’re planning 2026 initiatives in pet insurance—or any specialty line that’s scaling—the most practical play is to treat AI as part of your risk control environment. Not a side project. That means connecting AI models to the metrics that rating agencies and regulators already care about: capital adequacy, underwriting consistency, claims integrity, and governance.

If you’re pressure-testing your roadmap, here’s the question I’d put on the agenda: Where would we lose rating confidence first—data quality, claims handling, reinsurance structure, or capital planning—and what AI-supported control closes that gap fastest?