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‘Reverse engineering’ motor insurance · Reverse-engineering process 1 Determine the price...
Transcript of ‘Reverse engineering’ motor insurance · Reverse-engineering process 1 Determine the price...
Competitive positioning study
‘Reverse engineering’ motor insurance
Contents
An introduction to reverse engineering
Example: MTPL competitive positioning of company A
Reverse-engineering process
Determine the price determinant variables for each of the competitors 1
Understand how each price determinant variable individually affects the final price2
Understand the interactions between variables3
Create a pricing calculator that emulates the tariff for each competitor4
Test and refine the pricing calculators to ensure a high degree of accuracy5
Steps to reverse-engineer a tariffNo.
The pricing calculators can be used to analyse the (price) competitiveness of the company in anysegment of the market through a simulation of the insurance market…
The methodology consists of generating a large number of profiles and simulating the prices and discounts of all competitors on each profile
Profile generation Statistical comparisonPrice simulation Statistical analysis
Generation of 13.000 profiles distributed according to the characteristics of the market, whilst maintaining appropriate constraints (eg. on age and driving experience)
Simulation of the premiums charged by each competitor to each profile, using the reverse-engineered models of the tariffs of competitors, as well that of the company, and applying appropriate discounts
Statistical comparison of the overall distribution of premiums, segment analysis by use of different variables and scenario analysis
The simulation uses representative profiles thus providing a precise view of the market, as well as full transparency of the price competitiveness of each market segment tested
Contents
An introduction to reverse engineering
Example MTPL competitive positioning company A
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Comparing base prices for company A
Average MTPL priceEUR
MedianEUR
Spread 2
EUR
706
721-2%
B
A
743
721+3%
C
A
+22%
D 883
A 721
1134
1176
1134
862
1134
1325
655
626
655
699
655
821
% of profiles where A price is… Percent
12 12 18 18 15 25
40 27 16 9 4 4
39 23 17 10 6 5
cheaper expensiveA
9.549
6.552
10.346
> 20%>10 - 20%-10% – 0 – 10%>10 – 20%> -20%
1 Calculated MTPL prices on a simulated portfolio of 13.000 profiles; no discounts applied2 Distance between 2,5%-97,5% percentile to reduce outlier bias
Sample size used
|
Average MTPL priceEUR
MedianEUR
494
613-19%
B
A
D 662
A 613+8%
964
824
964
689
964
994
557
438
557
559
557
616
% of profiles where Allianz price is… Percent
4 4 7 11 15 60
27 27 21 11 7 6
18 19 21 16 11 14
cheaper expensiveA
Sample size used
> 20%>10 - 20%-10% – 0 – 10%>10 – 20%> -20%
30% B15% A 25% D20% C
1 Calculated MTPL prices on a simulated portfolio of 13.000 profiles; standard discounts applied2 Distance between 2,5%-97,5% percentile to reduce outlier bias
However, when standard discounts are applied, pricing strength of company A against all competitors is significantly weakened 1
Spread 2
EUR
9.549
6.552
10.346
595
613-3%
C
A
Discount applied:
|
Competitive positioning of company A is improved when we increase the discountrate against that of competitors, particularly against C and D 1
Average MTPL priceEUR
MedianEUR
494
576-14%
B
A
595
576+3%
C
A
+15%
D 662
A 576
907
824
907
689
907
994
438
524
559
524
616
524
% of profiles where Allianz price is… Percent
6 6 10 14 16 48
40 27 16 9 4 4
27 22 20 14 8 9
cheaper expensiveA
Sample size used
> 20%>10 - 20%-10% – 0 – 10%>10 – 20%> -20%
30% B20% A 25% D20% C
Spread 2
EUR
9.549
6.552
10.346
1 Calculated MTPL prices on a simulated portfolio of 13.000 profiles; extra A discount and standard competitor discounts2 Distance between 2,5%-97,5% percentile to reduce outlier bias
Discount applied:
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Scenario analysis shows changes in cheapest offer applying (1) no discount for all competitors, (2) A15% discount, (3) A 20% discount
D
9%C10%
B
47%
A34%
D
12%C
7%
B
68%
A
13%
D
10%C7%
B65%
A
19%
30% B20% C 15% A 25% D 30% B20% C 20% A 25% D
1 2 3
1.212824
7.884
2.2851.437877
8.335
1.5561.0931.244
5.765
4.103
-451
+729
+2.570
-2.547
CBADCBA C
-225
BAD D
# number of profiles with cheapest price
No discount scenario A average discount level scenario Allianz 20% level discount scenario
0% B0% C 0% A 0% D
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A “Staggered discount model” allows A to optimize its spending on discounts and still have the cheapest offer for the same customer profiles
# of profiles where A has the cheapest price
472
340
530
729
959
30%
3.244
1.333
3.244
25%
2.285
4.577
20%
2.285
1.556
15%
1.556
1.026
10%
1.026
686
5%
686
472214
0%
472
Discount level of A
Results of discount sensitivity analysis
Step 1: With a flat discount of 0% A still offers the
cheapest price for 472 profiles
Step 2: Increasing the flat discount to 5% A offers 214
profiles more as the cheapest price. Conclusion: 214
profiles needs to have a discount between 0% and 5%
Step 3: Perform Step 2 increasing the flat discount level
to 30%.
ConclusionApplying staggered discount model allows A to save
money without losing customers1
“Staggered” discount model:
0%: 472 profiles 0% - 5%: 214 profiles
5-10%: 340 profiles 10-15%: 530 profiles
20-25%: 729 profiles 25-30%: 959 profiles
30%: 1.333 profiles
10.564 Total number of profiles with A offer
1 Assumption is that A value proposition allows convergence of prices close to competitors
“Generation Y” driver31 years old, Fiat Punto, 51kW
“Middle-aged” driver40 years old, Golf VII, 81kW
“Old timer” driver51 years old, BMW 5, 115kW
A’s tariff is cheapest byNumber of postal codes
A’s tariff is cheapest byNumber of postal codes
A’s tariff is cheapest byNumber of postal codes
475401224
> 10 - 20%> 10% > 20%
13
136174
> 10 - 20% > 20%> 10%
211
62
> 10 - 20%> 10% > 20%
A B C D
A’s price competitiveness is varied across different profiles; the average price for the “Generation Y” driver can be raised whilst still retaining the customer
On the whole, A could lower its postal code coefficients in the North and increasethem in the South to increase competitiveness
Postal coefficients versus CPostal coefficients versus B
In the North, A coefficients could be raised. Whilst in the South, A should lower postal zonecoefficients to become more competitive against C and D
Postal coefficients versus D
> 20%>10 - 20%-10% – 0 – 10%>10 – 20%> -20%
cheaper expensiveA
Current A‘s postal code zoning for TPL tariff 1