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Loan-Prediction-Based-on-Customer-Behavior

Introduction

An organization wants to predict who possible defaulters are for the consumer loans product. They have data about historic customer behavior based on what they have observed. Hence when they acquire new customers they want to predict who is riskier and who is not.

About Data

ID: Id of the user(All Unique)

Income: Income of the user

Age: Age of the user

Experience: Professional experience of the user in years

Profession: Profession of the user

Married/Single: Whether married or not

House_Ownership: Owned or rented or neither

Car_Ownership: Does the person own a car

STATE: State of residence

CITY: City of residence CURRENT_JOB_YRS: Years of experience in the current job

CURRENT_HOUSE_YRS: Number of years in the current residence

Risk_Flag: Defaulted on a loan(Target variable)

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