How Insurance Commissions Actually Work in India

When you search for health insurance on PolicyBazaar, you get a list of recommended plans. They look authoritative. They have star ratings, expert badges, and "best value" labels. What they don't tell you — at least not prominently — is that the order of those recommendations is determined in part by how much the insurer is willing to pay PolicyBazaar for placing them there.

This is not a secret. It's how the entire industry works. But most Indian consumers don't understand the mechanics, which is exactly why it continues to work so well for the platforms.

Let's break down how the commission system actually operates.

The Basic Structure: How Insurance Commissions Flow

When you buy an insurance policy through an aggregator platform like PolicyBazaar or Coverfox, the insurer pays the platform a commission. That commission is a percentage of your first-year premium — and it varies significantly by product type.

The IRDAI (Insurance Regulatory and Development Authority of India) sets maximum commission limits for direct agents and brokers. But aggregators operate under a different regulatory category — they are licensed as Insurance Web Aggregators (IWAs) — and the rules governing their compensation have historically been less restrictive.

Why This Creates Biased Recommendations

The incentive problem is simple to understand once you see it. An aggregator gets paid more when a consumer buys a high-commission product. So the ranking algorithm — whatever its stated criteria — exists inside a business model that rewards showing you certain products over others.

This plays out in several concrete ways:

1. High-margin products appear first

Term insurance has the highest commission rate of any insurance category — sometimes 30–40% of the first-year premium. A 30-year-old buying a ₹1 Cr term plan might pay ₹8,000–10,000 a year. At a 35% commission, that's ₹2,800–3,500 to the platform on a single sale. Multiply that by millions of customers and you understand why term plans are aggressively promoted.

But not all term plans are equal. Some have better claim settlement ratios. Some have genuinely simpler exclusion clauses. Some have faster payout processes. The "featured" plan is rarely the one with the best consumer outcomes — it's often the one where the insurer has negotiated a higher placement fee.

2. Insurers bid for visibility

PolicyBazaar's advertising model isn't a secret. Insurers pay for premium placement — "sponsored" positions, featured badges, and top-of-page positioning. IRDAI acknowledged this in regulatory discussions, noting that platforms must clearly distinguish paid placements from organic recommendations. In practice, the distinction is frequently buried in footnotes.

3. Renewal commissions create stickiness incentives

On many products, aggregators earn a renewal commission in subsequent years — a smaller percentage, but compounding over millions of policies. This creates an incentive to keep customers on existing policies rather than recommend switching to genuinely better products when market conditions change.

"The problem isn't that aggregators make money. The problem is that their revenue model is structurally misaligned with consumer interests — and that misalignment is invisible to most users."

The Scale of the Problem

To understand how significant this is, consider the market context.

PolicyBazaar's parent company PB Fintech holds approximately 93.4% of the online insurance comparison market in India by search volume and transactional share. That near-monopoly means that for the vast majority of Indians who research insurance online, their first contact with policy information is through a platform with a structural commission-based revenue model.

The revenue from insurance distribution is largely commission-based. Hundreds of crores flows annually from insurers to the platform for customer acquisition. The consumer, buying what they believe is a neutral recommendation, is the product in this transaction — not the customer.

What IRDAI Is Doing About It

IRDAI has been increasingly aware of the commission bias problem. Several regulatory interventions are worth understanding.

Commission Cap Reviews

IRDAI has periodically reviewed commission structures for insurance intermediaries, including a significant consultation in 2023–24 that proposed standardising commission caps across distribution channels to reduce the distortion between what agents earn and what aggregators earn. The goal is to prevent insurers from offering higher commissions to aggregators in exchange for placement — a practice that distorts the market without technically violating any single rule.

Disclosure Requirements

IRDAI's web aggregator regulations require platforms to disclose that they earn commissions and to show consumers the commission percentage earned on each product they purchase. In practice, this disclosure is typically presented as a single line in the terms and conditions or a brief footnote at the checkout stage — after the customer has already been influenced by the comparison.

The Bima Sugam Initiative

IRDAI's most ambitious structural intervention is Bima Sugam — a government-backed insurance marketplace that would allow consumers to buy policies directly from insurers without intermediaries. If implemented fully, Bima Sugam would significantly reduce the commission layer. Predictably, incumbent aggregators have lobbied extensively against it or for its scope to be limited.

As of early 2026, Bima Sugam has been delayed multiple times. The political economy of disrupting a ₹3,000+ Cr revenue business with strong lobbying capacity is considerable.

What Consumers Should Actually Look For

Given this landscape, here's what an informed insurance buyer should keep in mind when using any comparison platform:

• Check the claim settlement ratio first. This is the single most important metric for any insurance product. It tells you what percentage of claims the insurer actually pays out. IRDAI publishes this data annually. A higher claim ratio is non-negotiable — no premium discount justifies buying from an insurer who denies 1 in 5 claims.
• Understand what "recommended" means. On commission-based platforms, a recommendation is marketing language, not an independent assessment. Look at the underlying data — premiums, coverage caps, sub-limits, waiting periods — and form your own view.
• Compare at least 3 insurers side by side. The best-looking single card in a list is usually not the best product. Force yourself to look at the alternatives. Sub-limits on room rent, per-disease caps, and specific exclusions are where most policies diverge meaningfully from each other.
• Read the exclusions, not just the benefits. Every insurer shows you the benefits prominently. Exclusions are buried. Pre-existing condition waiting periods (typically 2–4 years), maternity waiting periods, specific illness exclusions, and sub-limits on day-care procedures are where most claim rejections originate.
• Know whether the platform earns commission on your purchase. Most platforms are required to disclose this. If a platform earns 0 commission — like InsureScan — the incentive structure is different by design. That's worth knowing before you trust the comparison.

How InsureScan Is Different

InsureScan was built precisely because the commission problem isn't going to be solved by the incumbents who profit from it. We earn no commissions from insurers. We have no affiliate relationships. No insurer has paid us for placement or a better score.

Our scores are algorithmic: weighted on claim settlement ratio (the single most important factor), premium value for coverage, hospital network density, waiting period terms, and consumer complaint data from IRDAI's published reports.

The insurance industry in India is not going to reform itself. The commission system is too profitable, too entrenched, and too opaque for platforms with ₹3,000+ Cr in annual revenue to voluntarily dismantle. IRDAI is moving — but slowly, and against significant resistance.

In the meantime, the best thing a consumer can do is understand how the system works, look at the underlying data, and use tools that aren't financially incentivised to send them toward the wrong product.

That's what we're here for.

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