Insurance fraud data

A compliance team is concerned about fraud detection accuracy as well as the key drivers that cause fraudulence in the automotive industry.

You can use this data to demonstrate how to use the utilities in the Minitab Solution Center.

Worksheet column Description
claim_number The claim identifier
age_of_driver Age of the driver
gender Gender of the driver: M or F
marital_status Marriage status of the driver: 0 or 1
safety_rating Safety rating: 2 - 100
annual_income Annual income of the driver
high_education Education status of the driver: 0 or 1
address_change Address change status of the driver: 0 or 1
property_status Does the driver own or rent
zip_code ZIP code
claim_date The date the claim was made
claim_day_of_week The day of the week the claim was made
accident_site The location of the accident: highway, local, parking lot
past_num_of_claims Total number of previous claims
witness_present Was a witness present: 0 or 1
liab_prct The liability percentage: 0 - 100
channel How claim was initiated: broker, phone, online
police_report Was a police report filed: 0 or 1
age_of_vehicle Age, in years, of the vehicle: 0 -14
vehicle_category The type of vehicle: compact, large, medium
vehicle_price The price of the vehicle
vehicle_color The color of the vehicle
total_claim Total claim amount in dollars
injury_claim Injury claim amount in dollars
policy deductible The amount in dollars of the policy deductible
annual premium The annual policy premium
days open Number of days claim is open
form defects Number of errors on form: 0 to 13
fraud reported Whether fraud was reported: Y or N

Download insurance_fraud_data.csv