2. - the solvency norms and their reform - Financial Management ...

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Dec 14, 2013 (3 years and 10 months ago)

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1

1
.
-

INTRODUCTION


One of the main reasons to reform the European s
olvency system

is to relate
company’s equity
capital

with market risk
.
However,
in this paper we propose that

the Solvency II methodology
is not
accurate enough
,

to evaluate

the amount of

r
esources needed, as it uses

the same or similar rules

for all
insurance
compa
nies, whatever their investment profile
s
, portfolio choice or organizational
form.

In this way, it

is important

to recogniz
e

that p
robably no other industry has such a diverse se
t
of corporate ownership structures as insurance. The industry, offers researchers a unique
environment within which to examine specific types of organizational firm on business behavior as
companies, usually, adopt one of two major types of own
ership stru
cture
-
the stock
or the mutual
form. Shareholders own stock companies, whereas mutual companies have no equity capital and
are nominally owned by their customers, the policyholders (Cummins and Weiss, 1991).


Few researchers believed several years ago, tha
t the organizational form was an important
determinant of firm financial structure, risk and performance. In the last two decades, there has
been nevertheless a considerable interest in the issue of why some financial firms separate the role
of customer an
d residual claimant, while others do not (Doherty 1991, Fama and Jensen 1983,
Hansmann 1985, Lamm
-
Tennant and Starks 1993, Mayers and Smith 1981, 1986, 1988, 1992;
O'Hara 1981, Smith and Stutzer 1990).


The costly contracting literature suggest, neverthele
ss, that business activity choices, such as the
selection of investment and financing strategies, seek to optimize the efficiency of internal
contracting between owners (stockholders), managers and customers (policyholders) in the firm,
and the capital str
ucture and investment strategies of stock and mutual insurers, therefore, might
differ: Since mutual policyholders own both the debt and the equity of the mutual, increasing the
value of the equity simply decreases the value of the policyholder stake, then
, the mutual form is
better suited to control the owner
-
policyholder incentive conflict (Smith and Stutzer, 1995). Differing
abilities of stock and mutual to efficiently control these incentive conflicts have significant
implications for the comparative ad
vantage of the two ownership structures in various insurance
activities. The nature of residual claimant of the equity holder payoffs gives stock companies a
relatively preference for risky investments. As a result, stock companies might have a greater
pre
ference for riskier asset portfolios.


T
he purpose of this study will be to examine empirically the solvency risk
of Spanish
insurance
companies from the assets and liabilities, reported in their balance sheets and how this risk
might depend of their orga
nizational form, size or business line. By focusing on the ratios and
determinants of balance
-
sheet structure of different kinds of insurance companies
-
stock and
mutual
-

the study could offer some important insights into the relationship between the
orga
nizational form of insurance companies and their financial structure, risk and profitability,
which could be pursued further in future research.


2

Data on the proportionate and absolute values of balance sheet items of insurance companies
were extracted fr
om a data base of the
275

insurance companies, registered

in Spain

in 2008
,
including both, life and non
-
life, joint stock and mutual insurance companies.


2
.
-

THE SOLVENCY NORMS AND THEIR REFORM


The insurance business is based on risk
-
taking by compani
es in exchange for
certain

income
s


primes
-

from

the agents who transferred
them
these risks. Like any business,
chasing
profitability
is the reason
of its existence. However, we must recognize that in addition to generating surpluses,
insurers need to e
nsure compliance with its commitments. It is therefore absolutely necessary to
have institutions strong enough to be able to
face
all possible contingencies that might arise from
their activity. For this reason, it is essential to analyze a key
aspect
such

as
their

solvency.
Although profitability and financial
stability

could look like
two
very different and antagonistic
qualities
,

it is essential to
have
the second
one before getting the
first. Th
erefore
,
the
regulatory
authorities have permanently
sought

to count with
adequate indicators and standards that enable
them
to check the strength of the companies.



In the European Union the issue of solvency is not new. In fact, the first regulations on the
subject date from 1973 y 1979
1
, which requires the

cre
ation of a capital cushion c
apable of
absorbing the results of unexpected change. Solvency rules were conceived as a common
minimum requirements for the entire EU, leaving full freedom for Member
Nations

to establish more
stringent criteria if they chose

d
o to so
.
All regulation relative to
Solvency was recently amended. It
is what has been called Solvency I. The changes have focused on the following aspects:



publication of two directives, one for life and another for non
-
life,
by

amending the solvency
marg
in requirements
2



emergence of a directive regulating the insurance business within financial conglomerates,
which is added to the 1998
directive
on insurance groups
3



Publication of the directive on reinsurance
4



directives that set requirements for the reor
ganization and bankruptcy of insurance
5




1


For non
-
life insurance,

Fir
st Council Directive 73/239/EEC of 24 July 1973 on the coordination of
laws, regulations and administrative provisions relating to the taking
-
up and pursuit of the business
of direct insurance other than life assurance
. For

life insurance
,
First Council Di
rective
79/267/EEC of 5 March 1979 on the coordination of laws, regulations and administrative
provisions relating to the taking up and pursuit of the business of direct life assurance

2


They are,
Directive 2002/13/EC of the European Parliament and of t
he Council of 5 March 2002
amending Council Directive 73/239/EEC as regards the solvency margin requirements for non
-
life
insurance undertakings
, and
Directive 2002/83/EC of the European Parliament and of the Council
of 5 November 2002 concerning life assu
rance
.

3


Directive 98/78/EC of the European Parliament and of the Council of 27 October 1998 on the
supplementary supervision of insurance undertakings in an insurance group

4


Directive 2005/68/EC of the European Parliament and of the Council of 16 Novem
ber 2005 on
reinsurance and amending Council Directives 73/239/EEC, 92/49/EEC as well as Directives
98/78/EC and 2002/83/EC
.


3


Since the beginning of this century, the European Commission has been working in the reform of
the level of the fixing system of the capital in the insurance companies. The objectives pursued are:

1)

protection of poli
cyholders

2)

establishment of a more commensurate capital
requirements
with the risks incurred

3)

establishment of principles, not rules


This reform
process did start

in 2003, when the Commission prepared an explanatory
6

note on the
design of the future system
of calculating the solvency capital. The system is intended to apply to
the insurance area the principles of Basel II in the banking field. Therefore, and as in such scheme,
the system is built around three pillars. Other key aspects of Solvency II are:


1)

s
olvency margins structured around two main capital figures
7
:

a)

One
, that we could call economic capital, which would be the amount associated with
the risk
-
bearing. This is what
is called

the Solvency Capital Requirement, SCR
-

b)

another one, that we could cal
l legal capital, which would be the minimum
required
amount
.
It is what is called the
Minimum Capital Requirement
-
MCR
-

2)

incorporation of international developments to promote a major convergence with
organizations as such as the IAIS, IAA and the IASB
8
, re
lated to the establishment of relative
procedure such as the level of the suitable capital.


The backbone of the new system is in the change of criteri
on

at the moment of calculating the
quantity of the capital of solvency,
because its role changes from es
tablishing the solvency capital
as
a function of the risk of subscription
-

pr
imes

-

to making it depend on the level of risk supported
in all and each one of the spheres in which the
insurance
activity
takes turn.


Ideally, the solvency capital requiremen
t should be:

a)

to
reduce the risk that an insurer is unable to meet payment of claims

b)

to
reduce the losses suffered by policyholders in the event that the company
goes
bankruptcy

c)

to provide
regulators an alert system that would allow them to intervene if th
e capital was
below certain levels

d)

to
promote confidence in the stability of the insurance industry






5


Directive 2001/24/EC of the European Parliament and of the Council of 4 April 2001 on the
reorganisation and winding up of credi
t institutions.

6


European
Commission
, Directive on the Internal Market (2003): "Concepción de un futuro sistema
de control cautelar en la UE.
Recomendaciones de los servicios de la Comisión".
MARKT/2509/03. Brussels, March 3, 2003.

7


Swiss Re (2006):
Solvency II: an integrated risk approach for European insurers
. Sigma nº 4/2006

8


These are the acronyms of the
International Association of Insurance Supervisors,

International
Actuarial Association

and the
International Accounting Standard Board
.


4


This process of change has finished with the pass of Directive 2009/138/CE (Solvency II Directive).
The whole scheme will be completed in the future with
the design of a mechanism for measuring
the solvency of the undertakings. This tool
it is foreseen
will be
able to assess the level of

resources in each company
, according to the amount risk undertaken.
In order to achieve this
target, CEIOPS has implement
ed four empirical studies, called QIS (Quanti
tative Impact Studies)
and we expect a fifth one by
2010.

The use of this analytical tool provides a huge advantage:
easiness

of use.

Whatever the company or its risk policy, in order to meet its level of capita
l
required according to the risks the company have assumed
, it will be enough to simply apply the
general model
. However, it has one big drawback: because t
he model is calibrated from
data
proceeding from
the
sector as a
who
le
,
it will
adequately represent

the average behavio
u
r of the
industry

and if the risk policy set up a profile different than the industry average, the model
will
calculate an overall amount of capital
that
have little or
mostly
nothing to do
with

the reality of that
company.


In short,
it seems clear that if from the sector analysis we could deduce that there are different
realities within it, then it could be affirmed that the use of a general model for assessing the
company’s solvency would not give the desired results with the new reg
ulations and that, in short, it
would be much better
the creation of
internal model
l
ing that captured the individuality of each
company
.




3.
-

TARGET AND DATA FOR THE ANALYSIS


As noted, the overall accuracy of the model would be further strengthened by
the existence of
behavio
u
rs not too different amongst other insurance companies. This work focuses in the area

of
Spanish insurers during 2008
-
most recent inf
ormation available by
February

20
10

-

and such work
seeks to finding out whether these companies p
resent the same risk profile, in which affirmative
case it would be
proven to be correct the use of the

global model
ling.


It is true that for the Solvency II calculations the whole balance is valuated at market prices, both
profit and loss. But to do it t
his way it would be needed not only to know
the kind of investment
each company has
made

and who
are its policyholders
but also aspects such as duration and
profitability of their investments, or the probability distribution of claims, associated costs and

the
expected
time for settlement
among

others.
Definitively, it would be necessary project towards the
future the predictable cash flows, and proceed to update them later.


However, publicly information available does not provide such data but only accoun
ting
-
P&L
issues, technical and nontechnical accounts, solvency margin and coverage of technical reserves.
Therefore, we have proceeded to analyze the behavio
u
r of firms and their risk position based on
ratios. As noted above, for the analysis we used the m
ost recent public information supplied by the

5

Directorate General of Insurance and Pension Funds, an agency under the Ministry of Finance,
concerning all operating entities in Spain

in 2008
. They were
296

insurers. However, we have only
analyzed informatio
n from entities that have complete information on all the selected ratios,
reducing the sample to
275

entities. The number of companies classified according to their legal
form is shown in Table 1



Table

1:
Number of insurance comp
anies according to their

institut
ional form,
2008

Organizational form

Number of companies

Percentag
e

Joint Stock Companies

(SA)




Direct insurance

192

69.9


Foreign Branches

2

0.7


Total

194

70.6

Mutual




Fix premium mutual

33

12.0


Social welfare entities (EPS
)

46

16.7


Total

79

28.7

Reinsurers

2

0.7

Total

275

100.0

Source: DGSFP


The ratios that were used are related to the assets, liabilities and income. Specifically, the
variables listed and the
names

with which they will appear in the analysis are sh
own in Table 2
:



Table 2: Ratios

Block

Ratio

Numerator

Denominator

Assets

R1

Return on financial investment

Financial Assets

R2

Total return before taxes (ROA)

Total assets

R3

Total investments

Total assets

Liabilities
&
Solvency

R4

Technical provis
ions

Total liabilities

R
5

Capital and reserves

Total liabilities

R
6

Total assets

Total debt

Insurance
P&L acc.

R7

Total gross indemnities (TGI)

Premium (Gross)

R8

TGI + Gross expenses

Premium (Gross)

R9

Net return (life/ non life)

Premium (Gross)

R10

Net return in Direct Insurance (DI)

Premium (Gross) in DI

Financial
income

R11

Total return after taxes (ROE)

Equity

R12

Premium (Gross)

Total Revenues (Gross)

Source: own elaboration


Some of these ratios are general to any company
-
for example,
R2 is ROA or

R11 is

ROE,
while others are specific to the insurance business
, such as
R
8

-
combined ratio
-
. In addition to
these ratios, are considered indicative of the size variables such as the volume of total assets and
number of employees.





6


4
.
-


ME
THODOLOGY AND RESULTS


The study has two distinct parts. In the first, the main objective is to investigate into the
underlying relationships between the ratios to try to identify a set of variables that explicitly allows
different
behaviours

between parse
d entities. To do this, we used factor analysis from which
we
have reached a number of significant axes that would
explain much of the variability of the sample.
From these
resulting
axes or factors
we started to proceed with
the second phase. In it, the i
nitial
ratios
have been replaced

by those factors achieving a reduction of dimension. With these data
we
have classified the sample into statistically homogeneous groups by cluster analysis.


The first phase of factor analysis is the confirmation of the ex
istence of interrelationships
between the ratios used. In fact, the matrix of correlations among them has plenty of
such
relationships
,
most of them

being statistically significant. Both the determinant of this matrix
(8.33∙10
-
7)
and the KMO statistic (0.7
34) have values that suggest the
opportunity to

use
a

factor
analysis. The
values

of the matrix above that exceed the unit are four,
obtaining, with all of them,
explanation for the
82% of the total variance, as stated in Table 3
.


Table

3:
Total Variance
explained


Total Variance explained

Components

Total

% of Variance

Cumulated %

1

4.646

38.717

38.717

2

2.347

19.556

58.273

3

1.525

12.709

70.983

4

1.252

10.435

81.418

Source: own elaboration


Because the obtained array of components did not make cle
ar the saturation of the ratios by the
factors, we decided to proceed to its rotation by using the method Varimax, obtaining the matrix
of rotated components set out in Table 4
:


Table

4: Matrix of rotated components


1

2

3

4

R1

-
0.089

0.325

0.329

0.393

R2

0.400

0.853

-
0.127

-
0.193

R3

-
0.087

0.073

0.016

0.802

R4

-
0.907

-
0.034

0.115

0.223

R5

0.974

0.072

-
0.113

-
0.116

R6

0.974

0.073

-
0.113

-
0.116

R7

-
0.135

-
0.092

0.883

0.089

R8

-
0.089

-
0.200

0.892

-
0.041

R9

0.476

0.538

-
0.408

-
0.365

R10

0.226

0.806

-
0.108

0.351

R11

-
0.312

0.891

-
0.069

-
0.105

R12

0.321

0.169

-
0.097

-
0.769

Source: own elaboration



7

It is important to notice

that the factor 1 produces the saturation of ratios 4, 5 and 6, which are
those concerning the financial structure and solvency

of companies. On the other side, factor 2
produces saturation on ratios
2, 9, 10 and 11

which are those
associated with measures of overall
performance
. Factor 3 saturated ratios
7 and 8

which

are

those related to technical results
.

Finally,
factor 4 satu
rates the remaining ratios, i
.
e
.
,
1, 3 a
nd 1
2
,

which

are

those reflecting the incidence of
financial activity.

Consequently, the information
related to

the ratios can be replaced by
these
new
four
variables

which

are not observed, but are latent in the ana
lyzed
structure
and formed from the
interactions among them. With them, we make the second part of the study, which is the use of
cluster analysis to obtain groups split statistically differentiated.
We would like to stress that
the
factors obtained are no
rmalized variables
.


Using the

new variables,
we have made two
types of cluster methods: hierarchical analysis
techniques and, once selected the number of possible groups to
take into consideration,
techniques
of non
-
hierarchical (or k means)
analy
sis
. For

the hierarchical method
it
was used as a
measure of
distance
the Euclidean squared:


Where
:

represents the distance between company
i

and

j

,


is the value of variable


to

i
company,



is the value of variable


to

j

company
.



After testing with different methods of
possible
grouping (nearest
and farther

neighbour,
relationship between
-
groups and intra
-
group,

medium a
nd method of Ward grouping
), the
clustering method chosen was
the
Ward

method
,
who hierarchically groups

elements to minimize a
given objective function, which in this case is the internal variation of the group
obtained. Once
analyzed

and taking it as a s
tarting point, several tests were conducted based on the same
technique with non
-
hierarchical clustering
using
algorithm average k for a number of groups
going
from

4
to

13. The choice of the number of groups was made using a F test
to obtain a
variability

reduction by
comparing the sum of squares within each group with


SCDG
-

with G groups with
the existing one if there were G+1 groups. The expression of the test is:



being
,
g

makes reference to the group
,
j

refer to the variable


in our case
j

goes from 1 to 4
-

and

i

makes reference to element

i

within each group
.
We have
followed Hartigan’s rule
(1975)
9

according to which, another Group has to be introduced if
F

is
bigger than 10.

The test results can be f
ound in Table 5.




9


Ha
rtigan, J.A. (1975):
Clustering Algorithms
. New York. Wiley


8


Table

5:
Number of groups selected


K
-

average algorithm groups

(G)


4

5

6

7

8

9

10

11

12

13

Factor 1

0.481

0.374

0.425

0.313

0.301

0.370

0.285

0.219

0.250

0.230

Factor 2

0.486

0.508

0.420

0.446

0.385

0.345

0.300

0.300

0.326

0.320

Fac
tor 3

0.545

0.496

0.394

0.361

0.339

0.288

0.299

0.273

0.264

0.274

Factor 4

0.781

0.445

0.444

0.450

0.429

0.401

0.363

0.369

0.298

0.289












TOTAL

2.293

1.823

1.684

1.571

1.454

1.404

1.248

1.161

1.137

1.114

n
-

G
-

1

271

270

269

268

267

266

265

26
4

263

262

F


70.828

23.288

20.367

22.519

10.512

34.249

20.854

6.618

6.472












SELECTED


NO

NO

NO

NO

NO

NO

YES

NO

NO

Source: own elaboration


Therefore the number of selected groups is
1
1
.


After obtaining and selecting the number of groups or r
isk profiles, ANOVA analysis is used to
study the significant differences between all the variables that have been involved in its formation.
For this, the null hypothesis of equality was contrasted among all averages of each of the groups,
as follows:



As can be seen

in T
able 6, all the variables for the formation of groups turn out to be
statistically significant to 5 %, which means the existence of groups that reflect different
situations

Table

6: ANOVA


Group

Error





Quadratic

mean

gl

Quadratic
mean

gl

F

Sig.

Factor 1

21.629

10

.219

264

98.933

.000

Factor 2

19.470

10

.300

264

64.814

.000

Factor 3

20.191

10

.273

264

73.939

.000

Factor 4

17.655

10

.369

264

47.832

.000

gl = freedom degrees and Sig. = p
-
value

Source: own elabo
ration



The number of entities for every group as well as the branches of activity in which it operates
and his association form are gathered
in Table

7
:







9


Table

7:
Number of companies in each group, business line and institutional form


Non life

Life

Both

J.S. Co

Mutua
l

EPS

Total

Group 1

20

0

2

16

4

2

0

Group 2

18

1

5

18

2

4

0

Group 3

1

15

9

12

1

12

0

Group 4

4

16

14

27

2

5

0

Group 5

18

4

12

31

3

0

0

Group 6

15

1

4

12

5

3

0

Group 7

28

0

6

25

6

1

2

Group 8

2

15

8

14

3

8

0

Group 9

22

1

1

22

2

0

0

Group 10

10

3

1

9

2

3

0

Group 11

10

5

4

8

3

8

0

Total

148

61

66

194

33

46

2

Source: Authors


Provided that the factors are normalized, the characteristics of each one from the groups it is
possible to classify them in table 8, where they have categ
orized depending on the average
value of the factor in each of the groups (if the average is lower than
-
1, he is catalogued like "
Very low ", if it is between
-
1 and
-
0,5, “Low", if it is between
-
0,5 and 0,5 is labelled like
"Neutral", if it is between 0,
5 and 1, as "High", and from 1 as "Very high ".


Table 8: Group

char
acteristics



Factor 1:

Solvency

Factor 2:

Loss ratio

Factor 3:

Financial
Activity

Factor 4:

Performance

Group 1

High

Low

High

Low

Group 2

Neutral

Very low

Low

Low

Group 3

Very low

Low

Very low

High

Group 4

Low

High

Very high

High

Group 5

Low

High

Low

Neutral

Group 6

Very high

High

High

High

Group 7

Neutral

Neutral

Neutral

Very low

Group 8

Low

Low

High

High

Group 9

High

High

Neutral

Low

Group 10

Very high

Very low

High

High

Group

11

Very high

Neutral

Very low

Very high

Source: own elaboration


In short, the analysis shows

that, considering the variables included in the analysis,

different
risk
profiles do exist among
the analyzed
insurance
companies
.









10

5
.
-

CONCLUSIONS AND
F
INAL REMARKS



Taking in consideration data
in
the
1
1

groups, it is not possible to conclude that all of t
hem
should have
an
equal
risk

profile. In t
his way, ther
e is a predominance
of
the
life

business in

Groups
3, 4
a
nd
8
. All of them have the common cha
racteristic of high

financial activity.
Not
surprisingly, among these groups are

the sub
sidiaries of the big financial g
roups.
T
here is a
predominance of non
-
life

business

in the remaining groups
. They present heterogeneous
characteristics, though they tak
e as a common

denominator the scanty importance of

f
inancial
activity, except in g
roup
5
.


In general terms, the worst averages

among insurance companies

appear in Group
2 and 3
,
whereas the best
results
are obtained in Group
6
, in which the business
that

predominate of
non
-
life, especially civil responsibility, fire, deceases and transport insurance. A good behaviour,
though worse tha
n that of the previous g
roup is given in Group
s

4 and 10

formed

by companies
that are mainly in

medical assistance.



In sh
ort,
the information
provided
seems to sho
w a heterogeneous reality in

the
insurance
Spanish sector, it

does not seem to be suitable
trying

to app
ly the same model
o
f risk
measurement for all of them
.
It is
necessary t
o remember that the aim behind Solvenc
y II,
is
trying

to obta
in the capital level that all and every company

should h
ave vis
-
à
-
vis risk
.
This aim
seems difficult to attain if the different

organizational forms and business lines,
are ignored
and
we apply a single

standard

model, which

tries to

measure

different realities

with the same rule
.



11

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