Answer as many questions as you can
- You are making a Dashboard for the Claims team of ABC insurance company. ABC operates in Asian, Europe and Latin America. The Global Head for Claims wants to understand how claims are being handled across product lines and Geographies at a glance. You are tasked with the design and development of such a dashboard. Please list down your main considerations
- KPIs to include in the Dashboard
- Design of front end
- Below is a small dataset
- List factors that lead to higher loss amounts - State your hypotheses such that they can be tested using the data below
- Does having an attorney result in greater compensation for the claimant?
- Set up an EDA (a lit of hypotheses) to determine the role played by an attorney in claims settlement process
## CASENUM ATTORNEY CLMSEX MARITAL CLMINSUR SEATBELT CLMAGE LOSS
## 1 5 1 1 NA 2 1 50 34.940
## 2 13 2 2 2 1 1 28 10.892
## 3 66 2 1 2 2 1 5 0.330
## 4 71 1 1 1 2 2 32 11.037
## 5 96 2 1 4 2 1 30 0.138
## 6 97 1 2 1 2 1 35 0.309
## 7 120 1 1 2 2 1 19 3.538
## 8 136 1 2 2 2 1 34 4.882
## 9 152 2 2 2 2 1 61 0.874
## 10 155 2 1 2 2 1 NA 1.351
- Using the data below will you be able to test the following hypotheses? (Answer Yes/No)
- State X has a higher per capita claim amount than the national average
- Old people claim more in Auto insurance than Young people
- State X has more “higher than national average” claims than any other state
## STATE CLASS GENDER AGE PAID
## 1 STATE 14 C6 M 97 1134.44
## 2 STATE 15 C6 M 96 3761.24
## 3 STATE 15 C11 M 95 7842.31
## 4 STATE 15 F6 F 95 2384.67
## 5 STATE 15 F6 M 95 650.00
## 6 STATE 15 F6 M 95 391.12
## 7 STATE 15 C11 M 94 3775.83
## 8 STATE 10 C6 M 94 415.35
## 9 STATE 14 C11 M 93 2283.56
## 10 STATE 03 C11 M 93 665.48
- Take a look at the data below to understand the dataset. And answer the questions using your choice of language. The dataset will be provided to you.
- Do a quick analysis to validate the hypothesis - Rural customers are less valuable than other customers
- Do a quick analysis to validate the hypothesis - Education positively impacts the Lifetime value of a customer
- Looking at the dataset below write down 5 hypotheses as to what contribues towards making a high value customer
- Write R code to summarize the dataset into tables similar to the Location code, Average CLV table below for testing these hypothesis
- Which parametric or non parametric test will you use to test if Marital status has an impact on value of a customer
- Plot the variation of CLV for various insurance policy types
- Plot how many policies are expiring on each day for the month of January 2011
| Rural |
$XXXX |
| Suburban |
$YYYY |
| Urban |
$ZZZZ |
## Customer State Customer.Lifetime.Value Response Coverage Education
## 1 BU79786 Washington 2763.519 No Basic Bachelor
## 2 QZ44356 Arizona 6979.536 No Extended Bachelor
## 3 AI49188 Nevada 12887.432 No Premium Bachelor
## 4 WW63253 California 7645.862 No Basic Bachelor
## 5 HB64268 Washington 2813.693 No Basic Bachelor
## 6 OC83172 Oregon 8256.298 Yes Basic Bachelor
## Effective.To.Date EmploymentStatus Gender Income Location.Code
## 1 2/24/11 Employed F 56274 Suburban
## 2 1/31/11 Unemployed F 0 Suburban
## 3 2/19/11 Employed F 48767 Suburban
## 4 1/20/11 Unemployed M 0 Suburban
## 5 2/3/11 Employed M 43836 Rural
## 6 1/25/11 Employed F 62902 Rural
## Marital.Status Monthly.Premium.Auto Months.Since.Last.Claim
## 1 Married 69 32
## 2 Single 94 13
## 3 Married 108 18
## 4 Married 106 18
## 5 Single 73 12
## 6 Married 69 14
## Months.Since.Policy.Inception Number.of.Open.Complaints
## 1 5 0
## 2 42 0
## 3 38 0
## 4 65 0
## 5 44 0
## 6 94 0
## Number.of.Policies Policy.Type Policy Renew.Offer.Type
## 1 1 Corporate Auto Corporate L3 Offer1
## 2 8 Personal Auto Personal L3 Offer3
## 3 2 Personal Auto Personal L3 Offer1
## 4 7 Corporate Auto Corporate L2 Offer1
## 5 1 Personal Auto Personal L1 Offer1
## 6 2 Personal Auto Personal L3 Offer2
## Sales.Channel Total.Claim.Amount Vehicle.Class Vehicle.Size
## 1 Agent 384.8111 Two-Door Car Medsize
## 2 Agent 1131.4649 Four-Door Car Medsize
## 3 Agent 566.4722 Two-Door Car Medsize
## 4 Call Center 529.8813 SUV Medsize
## 5 Agent 138.1309 Four-Door Car Medsize
## 6 Web 159.3830 Two-Door Car Medsize
## 'data.frame': 9134 obs. of 24 variables:
## $ Customer : chr "BU79786" "QZ44356" "AI49188" "WW63253" ...
## $ State : chr "Washington" "Arizona" "Nevada" "California" ...
## $ Customer.Lifetime.Value : num 2764 6980 12887 7646 2814 ...
## $ Response : chr "No" "No" "No" "No" ...
## $ Coverage : chr "Basic" "Extended" "Premium" "Basic" ...
## $ Education : chr "Bachelor" "Bachelor" "Bachelor" "Bachelor" ...
## $ Effective.To.Date : chr "2/24/11" "1/31/11" "2/19/11" "1/20/11" ...
## $ EmploymentStatus : chr "Employed" "Unemployed" "Employed" "Unemployed" ...
## $ Gender : chr "F" "F" "F" "M" ...
## $ Income : int 56274 0 48767 0 43836 62902 55350 0 14072 28812 ...
## $ Location.Code : chr "Suburban" "Suburban" "Suburban" "Suburban" ...
## $ Marital.Status : chr "Married" "Single" "Married" "Married" ...
## $ Monthly.Premium.Auto : int 69 94 108 106 73 69 67 101 71 93 ...
## $ Months.Since.Last.Claim : int 32 13 18 18 12 14 0 0 13 17 ...
## $ Months.Since.Policy.Inception: int 5 42 38 65 44 94 13 68 3 7 ...
## $ Number.of.Open.Complaints : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Number.of.Policies : int 1 8 2 7 1 2 9 4 2 8 ...
## $ Policy.Type : chr "Corporate Auto" "Personal Auto" "Personal Auto" "Corporate Auto" ...
## $ Policy : chr "Corporate L3" "Personal L3" "Personal L3" "Corporate L2" ...
## $ Renew.Offer.Type : chr "Offer1" "Offer3" "Offer1" "Offer1" ...
## $ Sales.Channel : chr "Agent" "Agent" "Agent" "Call Center" ...
## $ Total.Claim.Amount : num 385 1131 566 530 138 ...
## $ Vehicle.Class : chr "Two-Door Car" "Four-Door Car" "Two-Door Car" "SUV" ...
## $ Vehicle.Size : chr "Medsize" "Medsize" "Medsize" "Medsize" ...