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CLUSTERING
Presented by : Ashish
Ranjan
Vaibhav Jain
Objective of the Study
O Maximize the company profits by

segmenting the business according to the
markets where the claim/coverage ratio is
least.
O To estimate the claim/coverage ratio for
each clusters & focus on the income
group having highest income with least
product penetration.
Data Variables Explained
O Claim Id
O Incident Date
O Claim Type : 1. Wind/Hail 2. Water Damage

3. Fire/Smoke 4.Contamination
5. Theft/Vandalism
O
O
O
O
O

Policy Id
Coverage
Income
Town size
Others Variables
Data Snapshot
Data Snapshot
Rapid Miner
K-Means Clustering
Clustering Analysis
Attributes

cluster_0

cluster_1

cluster_2

cluster_3

cluster_4

Claim Amount

32.13595628

646.7065116

429.937594

67.60462253

124.0138065

Coverage

136.2993755

1453.186047

588.8721805

402.1022067

1021.9

Income

46.86104606

199.0813953

109.7518797

83.51800232

134.5645161

Members

2562

86

133

861

310

CLAIM/COVERAGE(
%)

23.57747874

44.50266455

73.01034219

16.8127957

12.13561077

The claim/coverage % is highest for Cluster 2 i.e. 73% and the
members contributing towards the same are also less. But the
average income of the members are significantly high.
Clustering Analysis
Types of Claims
cluster

1

2

3

4

5

Grand Total

cluster_0

630

389

589

227

727

2562

cluster_1

10

6

46

19

5

86

86

47

cluster_2

133

cluster_3

228

130

163

70

270

861

cluster_4

95

52

35

15

113

310

Grand Total

963

577

919

378

1115

3952

Cluster 2 contains only claim types 3 (Fire) & 4
(Contamination). Hence, company should focus on
increasing their portfolio bucket by offering other insurance
coverage's i.e. 1 (Wind/Hail), 2 (Water Damage) & 5 (Theft)
.
Clustering Analysis
700
T
600
O
W 500
N 400
S
I
Z
E

1
2

300

3

200

4

100

5

0
cluster_0

cluster_1

cluster_2

cluster_3

cluster_4

CLUSTER TYPE

Cluster

>2.5 L (1)

50TH2.499L(2)

10TH49.99TH(3)

2.5TH9.999TH(4)

<2.5TH(5)

Grand Total

cluster_0

668

623

518

435

318

2562

cluster_1

20

21

17

18

10

86

cluster_2

30

28

25

33

17

133

cluster_3

219

208

165

178

91

861

cluster_4

85

70

56

67

32

310

Grand Total

1022

950

781

731

468

3952
Recommendations
O On the basis of analysis, we recommend

to the company to concentrate on Cluster
2 markets(towns) where the average
income is high & penetration of different
types of insurance products are less.
O Overall, by reduction in claim/coverage
ratio & increased customer base will
contribute towards higher profitability for
the company.
THANK YOU

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Clustering Model - Insurance Claims