Download TI Day 3

New Paradigm for International
Insurance Comparison
With an Application to Comparison of Seven Insurance Markets
Presented By:
Stephen Packard
Director, Financial Services/Strategy and Operations
Deloitte Consulting, LLP
Copyright © 2008 Deloitte Development LLC. All rights reserved.
0
The strategic importance of assessing growth potential of insurance markets
There are many factors contributing to the strategic importance of accurately assessing market growth
potential. Those factors include:
• Making the right investment choices requires a comprehensive and
consistent framework to understand the current and future growth
opportunities in various geographic/geopolitical markets.
• Competitive environment and market conditions will increase the
damage caused by wrong bets
• Need to capitalize on international institutions involved in market
building
Copyright © 2008 Deloitte Development LLC. All rights reserved.
1
The Two Insurance Growth Models
The basis of the author’s thesis is a comparison between two “world insurance growth models”: The
Ordinary Growth Model and the Adjusted Growth Model. Each has its own application and comparisons
between them provide new insight.
Ordinary Growth Model
Observations from the Ordinary Growth Model
• Insurance penetration rises as GDP per capita rises, but different levels of GDP per capita accompany
different rates of increase for insurance penetration
• Low GDP per capita correlates with a slow rate of increase for Insurance Penetration
• Increasing GDP per capita leads to a high rate of increase for Insurance Penetration
• However, at the highest levels of GDP per Capita the rate of Insurance Penetration slows and
levels off
• Does not separate the economic factors and institutional factors influencing insurance growth
Adjusted Growth Model
Observations from the Adjusted Growth Model
• Separates country-specific institutional factors and economic factors influencing insurance growth
• More suited to structural analysis of the insurance industry. For instance, to compare the growth
structure of each country’s insurance industry
Comparing the Ordinary Growth Model and Adjusted Growth Model allows the observer to
separate the different impacts of economic factors and institutional factors on the development
of the insurance industry for an individual country
Copyright © 2008 Deloitte Development LLC. All rights reserved.
2
A New Method for Measurement
Each of the current methods for measurement of the insurance industry within a country are problematic in
that they do not provide for the effects of the relative stage of economic growth. A new method of
measurement is introduced to accommodate these differences
Method
Definition
Benefits
Challenges
Premium
Income
Method
Measures the total
premium income
Depicts the overall scale of the
insurance market in each country
Fails to take the population factor into
consideration
Insurance
Density
Method
The per capita premium
(Premium divided by
population)
Better reflects the true level of
insurance growth compared to the
premium income method
Only considers the development of the
insurance industry in isolation. Does
not take into account the relationship
between the insurance industry and the
economy
Insurance
Penetration
Method
Total premium divided
by GDP. An alternate
method is insurance
density/GDP per capita
Characterizes the relationship
between the insurance industry and
the broader economy
Does not consider the different stages
of economic development and thus
does not account for different insurance
penetration levels at each stage of
development
New
Method:
BRIP
Benchmark
Ratio of
Insurance
Penetration
The relationship
between the a country’s
insurance penetration
and the world’s
average penetration (at
an equivalent economic
level)
A measure of the relative
development of the country’s
insurance industry to the stage of
economic development
Copyright © 2008 Deloitte Development LLC. All rights reserved.
3
The Implications of BRIP Method
By measuring the relative development of a given country’s insurance industry in relation to its own stage
of economic development, the authors are able to gain insight into the specific factors driving industry
growth.
Table 3: Insurance Industry Raw Data of Seven Selected Countries in 2006
Market
U.S.
Japan
U.K.
China
India
Brazil
Russia
World
Average
GDP per
Premium
Insurance
capita
Income
density
(US$)
（US$) （million US$）
43,562
1,170,101
3,924
34,661
460,261
3,590
39,207
418,366
6,467
2,055
70,805
54
784
43,032
38
5,640
30,390
161
6,877
21,504
151
7,372
3,723,441†
555
Insurance
penetratio
n（％）
8.8
10.5
16.5
2.7
4.8
2.9
2.3
7.5
BRIP
1.31
1.57
2.56
1.30
2.49
1.12
0.88
1.13
Table 4: Rankings of Insurance Industry of Seven Countries in 2006
Market
U.S.
Japan
U.K.
China
India
Brazil
Russia
GDP per
capita
14
28
19
133
166
82
76
Premium
1
2
3
9
15
19
22
Copyright © 2008 Deloitte Development LLC. All rights reserved.
Insurance
density
6
9
1
70
76
49
52
If BRIP is equal to 1, the
country’s actual
penetration is equal to
the world average
penetration at that
country’s economic level
Insurance
penetration
14
7
1
47
31
44
56
4
BRIP
26
14
4
27
5
36
52
According to BRIP, the
rankings of insurance
industries of developed
countries descend
relative to rankings
under traditional
indicators, but rankings
of emerging countries
rise
The Implications of BRIP Method
By applying the BRIP Method and examining the ranking over time new conclusions are drawn compared to traditional
indicators.
Table 5: Ranking of BRIP of Seven Countries (1982 ~ 2006)
U.S.
Japan
U.K.
China
India
Brazil
Russia
Number of
Countries
1982
1987
9（17%） 8（15%）
8（15%） 5（9%）
11（21%） 7（13%）
53（100%） 49（89%）
36（68%） 33（60%）
48（91%） 50（91%）
-
1992
15（20%）
7（9%）
6（8%）
49（64%）
30（39%）
62（82%）
70（92%）
1997
20（22%）
8（9%）
7（8%）
54（59%）
39（42%）
48（52%）
59（64%）
2002
19（20%）
12（13%）
7（8%）
27（29%）
15（16%）
53（57%）
35（38%）
2006
26（30%）
14（16%）
4（5%）
27（31%）
5（6%）
36（41%）
52（60%）
53
76
92
93
87
55
During the past two
decades and more, the
rankings of BRIP for
developed countries
have both risen and
declined. However,
BRIP rankings for
emerging countries
have risen.
This suggests emerging countries’ growth potential has been larger than indicated by
traditional measures
Copyright © 2008 Deloitte Development LLC. All rights reserved.
5
Conclusions
In conclusion, the introduction of a new measurement model along with the insights presented by the
authors based on the Adjusted Growth Model and the trichotomy focuses new attention on the insurance
industry in emerging countries.
Author’s Conclusions
• Industry growth in emerging countries is driven largely by institutional factors while developed countries
growth is driven mostly by regular economic factors
• Introduction of the BRIP measurement indicates insurance growth levels in emerging countries is
understated by traditional measures while developed countries growth is overstated
Impacts for Business Leaders
• The need for top line growth will during soft market conditions will drive insurers towards other markets
• Understanding the drivers of insurance growth in emerging markets is critical to making good business
decisions
• Institutional growth in emerging markets should be monitored as it represents the greatest driver of
industry growth when GDP is low
• Looking beyond the traditional measures will give savvy leaders an edge and allow them to view
countries with low penetration rates in a new, more sophisticated way
Copyright © 2008 Deloitte Development LLC. All rights reserved.
6