Home Insurance

Context

Data has always been at the heart of the insurance industry. What has changed in our current reality to create massive disruption is the amount of data generated daily and the speed at which machines can process the info and uncover insights. We can no longer characterize the insurance industry as a sloth when it comes to innovation and technology. Artificial intelligence (AI) and machine learning are transforming the insurance industry in a number of ways.

Source: https://goo.gl/KJrWLb

Content

This is a Home Insurance dataset including police's years between 2007 and 2012. Each police includes some significants characteristics of polices, building's characteristics, the zone, the privileges, the faults, some risk indicators and so on.

Acknowledgements

This is a Home Insurance dataset from the R class in the "Université de Technologie de Troyes (UTT), France" where i'm coursing a Big Data master. I was assigned this dataset to get insights using R and its machine learning tool Rattle.

Inspiration

With this publication I would like to help those who are starting in the "Data Sciencie World" like me and to get reviews from those who have a major expertise in the subject.

Variables Description

• QUOTE_DATE: Day where the quotation was made
• COVER_START: Beginning of the cover payment
• CLAIM3YEARS: 3 last years loss
• P1_EMP_STATUS: Client's professional status
• P1_PT_EMP_STATUS: Client's part-time professional status
• BUS_USE: Commercial use indicator
• CLERICAL: Administration office usage indicator
• AD_BUILDINGS: Building coverage - Self damage
• RISK_RATED_AREA_B: Geographical Classification of Risk - Building
• SUM_INSURED_BUILDINGS: Assured Sum - Building
• NCD_GRANTED_YEARS_B: Bonus Malus - Building
• AD_CONTENTS: Coverage of personal items - Self Damage
• RISK_RATED_AREA_C: Geographical Classification of Risk - Personal Objects
• SUM_INSURED_CONTENTS: Assured Sum - Personal Items
• NCD_GRANTED_YEARS_C: Malus Bonus - Personal Items
• CONTENTS_COVER: Coverage - Personal Objects indicator
• BUILDINGS_COVER: Cover - Building indicator
• SPEC_SUM_INSURED: Assured Sum - Valuable Personal Property
• SPEC_ITEM_PREM: Premium - Personal valuable items
• UNSPEC_HRP_PREM: Unknown
• P1_DOB: Date of birth of the client
• P1_MAR_STATUS: Marital status of the client
• P1_POLICY_REFUSED: Police Emission Denial Indicator
• P1_SEX: customer sex
• APPR_ALARM: Appropriate alarm
• APPR_LOCKS: Appropriate lock
• BEDROOMS: Number of bedrooms
• ROOF_CONSTRUCTION: Code of the type of construction of the roof
• WALL_CONSTRUCTION: Code of the type of wall construction
• FLOODING: House susceptible to floods
• LISTED: National Heritage Building
• MAX_DAYS_UNOCC: Number of days unoccupied
• NEIGH_WATCH: Vigils of proximity present
• OCC_STATUS: Occupancy status
• OWNERSHIP_TYPE: Type of membership
• PAYING_GUESTS: Presence of paying guests
• PROP_TYPE: Type of property
• SAFE_INSTALLED: Safe installs
• SEC_DISC_REQ: Reduction of premium for security
• SUBSIDENCE: Subsidence indicator (relative downwards motion of the surface )
• YEARBUILT: Year of construction
• CAMPAIGN_DESC: Description of the marketing campaign
• PAYMENT_METHOD: Method of payment
• PAYMENT_FREQUENCY: Frequency of payment
• LEGAL_ADDON_PRE_REN: Option "Legal Fees" included before 1st renewal
• LEGAL_ADDON_POST_REN: Option "Legal Fees" included after 1st renewal
• HOME_EM_ADDON_PRE_REN: "Emergencies" option included before 1st renewal
• HOME_EM_ADDON_POST_REN: Option "Emergencies" included after 1st renewal
• GARDEN_ADDON_PRE_REN: Option "Gardens" included before 1st renewal
• GARDEN_ADDON_POST_REN: Option "Gardens" included after 1st renewal
• KEYCARE_ADDON_PRE_REN: Option "Replacement of keys" included before 1st renewal
• KEYCARE_ADDON_POST_REN: Option "Replacement of keys" included after 1st renewal
• HP1_ADDON_PRE_REN: Option "HP1" included before 1st renewal
• HP1_ADDON_POST_REN: Option "HP1" included after 1st renewal
• HP2_ADDON_PRE_REN: Option "HP2" included before 1st renewal
• HP2_ADDON_POST_REN: Option "HP2" included afterrenewal
• HP3_ADDON_PRE_REN: Option "HP3" included before 1st renewal
• HP3_ADDON_POST_REN: Option "HP3" included after renewal
• MTA_FLAG: Mid-Term Adjustment indicator
• MTA_FAP: Bonus up to date of Adjustment
• MTA_APRP: Adjustment of the premium for Mid-Term Adjustmen
• MTA_DATE: Date of Mid-Term Adjustment
• LAST_ANN_PREM_GROSS: Premium - Total for the previous year
• POL_STATUS: Police status
• Police: Police number