Insurance 101

It was a couple of years ago, during my MBA curriculum that I came across this chart. And for obvious reasons, this didn’t catch my attention and came across as just being too obvious, just as obvious as those other tens of marginal utility graphs that we were exposed to in economics. But it was only when I joined my first stint in Life Insurance, did I understand the potent power of explanation of this simple chart. It represents the entire business model of a multi-trillion dollar global business of insurance.

Let me begin by briefly describing the supposed beginnings of modern insurance in the first place. It was a couple of centuries ago when the trade started flourishing that people realized the value of needing protection against ships capsizing in the seas or fires destroying goods in a warehouse. And it was obvious that such a loss was too big for a single individual/trader to bear, and thus trader cooperatives began charging for protection against such events, making a pay-out to any affected party of such risk events. And therein lies the basic principle of any insurance contract, life or non-life.

Read the above statement very carefully, specifically the highlighted words. As the events being covered started growing, insurance started getting more and more specialized. More legalese and more mathematics. And you can see why. To ensure the event being covered is specific, that value of impact is objectively verifiable and that the affected party is identifiable — very elaborate legal contracts started being put in place. At the same time, to combat the unpredictable and low-probability nature of such events, mathematics dictated the business model to sign up as many individuals as possible who are all exposed to the same event. This leads to the law of large numbers phenomenon, helping establish probability and certainty of insurance claim liabilities on a portfolio level.

But here’s the interesting part. Let’s say You have a policy worth ₹10000, for an event that has an annual probability of incidence of 1%. Simple math would put your probable value of the loss at ₹100, i.e. 1% of 10,0000. And hence perhaps the premium should be ₹100?

The insurance company, the central party in this business has its own cost. The cost of manpower to reach out and acquire new customers that make the business sustainable, the legal cost, the operating cost to adjudicate claims and make payments, and other human costs of those expensive mathematical experts, the actuaries. And hence they end up making marking that premium up by say 100%, to ₹200.

Purely mathematically speaking, this seems unfair, right? To pay ₹200 for an event with a probable value of the loss at ₹100. But that’s the financial/mathematical angle of it. As much maths is involved in the business of insurance, at the end of it, it’s still a retail product. Much like your soaps, cars or your phones. A phone costing ₹10000, probably has a bill of materials (BOM) cost of only ₹4000. The rest is required to pay up for assembly costs, logistics, distribution and that minuscule margin that phone manufacturers make. In a similar fashion, the mathematical probability of loss is like the Bill of Materials (BOM) of an insurance product. All other manpower and margin considerations jack up the cost of delivering the product (annual premiums) to a much higher number.

But this is where I find an insurance product to be far more beautiful in construct than any other retail product. Even when I offer you a phone for ₹10000, I need to sell you the very concept of the phone, the brand of the phone and its various features and benefits to justify why the value of the phone is much higher than the cost you are asked to pay up. In an insurance policy, especially one that is multi-year in nature, the chart referenced at the start of this post comes into play. Loss aversion is as basic a human instinct as the one to survive. In fact, the loss version stems very much from our instinct for survival. And hence, we always tend to overemphasize the value of avoiding loss, much more than what a mathematical probability of loss would dictate. And hence, we already value the construct of an insurance product. The shaded area under the graph is the value surplus that an insurance company already has to optimize all its various costs and extract its margin.

Mind you, I don’t mean to say that the brand of an insurance company or all its features have no value. The point I’m trying to make is that this is an industry whose product-market fit is as fundamental and established as the sun rising in the east. The nature of any industry, be it telecom, oil and gas or electronics, typically changes 1–2 times every century. On the other hand, insurance is one such industry whose products may be tinkered around with their features and benefits, but nonetheless have a shelf life equal to that of the existence of human societies.

Anyways, there are primarily 4 different cuts to look at any kind of insurance: life vs non-life and personal vs group.

Most of the above discussion above insurance applies primarily to the personal insurance segment. This is where all the loss aversion and law of number effects play out best in favour of the insurer and the insured as well. Will talk about group insurance in a follow-up post.

Personal Life Products:

Any personal life insurance product is effectively a tool to mitigate the financial impact of an unexpected length of life. Please pay attention to the choice of my words. Products here are meant to address the risk of a life cut short OR a life that extends beyond the expected life expectancy. Term life products cater mainly to the risk of a life cut short too soon, when your dependents may suffer financially. Annuity products cater to exactly the opposite risk. These products aim to provide a stream of cash till you live, thereby mitigating any risk of living a long life and running out of money to fund it.

For an individual, a term life product is the one that makes the most sense. It ticks all the boxes of “specific, unpredictable, low-probability but high-impact” to the fullest extent possible. Also, for an individual, it is the easiest to understand product (talking strictly about term insurance products) and financial most meaningful (tax benefits under 80c). Too much has been written all over the internet about various life products, ULIPs, Term, traditional and non-traditional already. I’ll rather not repeat the product aspect of this category further.

Personal Non-life Products:

Your car insurance, home insurance and health insurance are all examples of non-life products. In simple terms, covering any event risk, except the death of an individual, is termed under the non-life category. In my personal opinion, many of these products cover an event risk that could lead to financial stress, though not necessarily events that are low probability or high impact. Take the case of motor insurance that covers own-damage to the vehicle. ~20% of all policies end up filing a claim in any given year. The cost impact of damage that is covered ranges from 5k-30k or so. These aren’t the right use cases in the spirit of insurance. But sure, damage to the entire vehicle, be it theft or natural calamity, these are the events that hold up to the spirit of an insurable event. Home insurance that covers damage against fire and natural disasters is a similar example. These days celebrities are known to insure their body parts that may impact their on-screen persona, which in their case is the money-making asset. What a product in this category may end up looking like is completely up to the creativity of the insurer and the need of the customer.

I have only gone in brief the personal insurance products category, as a lot has been written on these from a perspective of product feature, insurer comparison or just the tax implications. I’ll follow up on this post with my personal understanding of the group life and non-life space. A lot of nuances here perhaps need to be understood better here that isn’t much documented in the world of personal finance.

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