Anthony Burpitt offers a tour through two ‘real world' techniques that are used by insurers to reduce ‘headline' premiums.
The first technique known as ‘preferred lives’ or ‘cherry picking’ is probably the most discussed in the industry. It refers to when an insurer places their lowest premium in an industry portal price comparison table. As the applicant goes through the sales process, ‘loadings’ are often added to reflect their current state of health, which increases the original low premium quoted for all but the most healthy of applicants.
Assuming that only 80% of an advisers protection applicants get the insurers’ cheapest ‘headline rate’, and that the 20% of applicants excluded are 25% more likely to die than the 80% already accepted, insurers could reduce their ‘headline rate’ (written through an IFA) by around 5%.
Why might an insurer not want to use this strategy? One answer is the experience it offers to applicants and intermediaries compared with their expectations. The sudden increase in price after underwriting could result in the applicant choosing not to proceed. It is true that an applicant applying direct might incorrectly think that they would have been given an increase from all insurers and carry on with their application. In some cases, the increase might be so small that it is not enough to put the applicant off buying. An experienced protection-savvy IFA might however get fed up with using certain insurers if harsh loadings continually result in lost business.
The more accurate the age definition at quotation, the more competitive the premiums can be – so age next month gives cheaper rates than age next birthday. For example, there have been some assumptions made in the averages used but it is enough to explain the theory:
Take two applicants A and B who both wish to take out term assurance. Applicant A is aged 30 years and 1 day. Applicant B is aged 30 years and 364 days. Given that they are a year apart, Applicant B has around a 10% greater chance of dying than Applicant A.
Now take two insurers X and Y. Insurer X uses age next birthday. Both applicants are aged 31 next birthday and so both pay the same rate. The insurer knows that the average age of all applicants aged 31 next birthday is 30.5 years old, so both A and B pay a rate based on age 30.5.
Insurer Y uses age next month. Applicant A pays the premium for 30 years and 1 month. Applicant B pays the premium for 30 years and 12 months, or 31.
Applicant A will chose insurer Y and Applicant B will choose insurer X.
Insurer X assumed that their age 31 next birthday rates would have been purchased by young as well as old 30-year-olds. But in fact, they will now only get old 30-year-olds. So they have to raise their rates because the average age is not going to be 30.5 but 30.75.
This effect then works in a cycle. The older the lives the insurer gets, the more they have to increase their rates, the youngest applicants will therefore go elsewhere, so the insurer may get even older lives and so on.
To put this into numbers, if a 30-year and 1-day-old male applied with an age next month insurer and an age next birthday insurer, the price difference might be something in the region of 8%. But for a 30-year and 364-day-old male, the difference will be almost zero.
Pros and cons
Why might an insurer not want to use this strategy? Firstly, it increases the number of rates they have to calculate and hold, although with modern technology this is a minor issue. Some distributors have told Munich Re that one of the biggest reasons for policies being cancelled from inception is where the applicant goes through a birthday while the policy is in the process of going on risk. This is more likely if the insurer in question has a narrower age definition. However, customers and advisers can mitigate this by choosing insurers that guarantee their quote for a certain period of time.
While this is theoretical, practice in the real world is not as clear-cut. Due to other price differentiators and some applicants who are not so savvy or price driven, the ‘age next birthday’ insurers will always attract some young and some old 30-year-olds. Therefore, the price differentials that can be achieved tend to be a little more dampened than the figures quoted in the theory.
These are just two techniques or ‘tricks’ of the trade. There are many more...
Anthony Burpitt is strategy and research consultant at Munich Re UK Life
