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Insurance Churn Prediction: Weekend Hackathon #2

The second edition of the weekend hackathon series is here and this time we challenge data scientists to predict the customer churn-out for an Insurance company in MachineHack’s Insurance Churn Prediction: Weekend Hackathon #2.

The challenge will start on April 24th Friday at 6pm IST.

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Problem Statement & Description

Insurance companies around the world operate in a very competitive environment. With various aspects of data collected from millions of customers, it is painstakingly hard to analyze and understand the reason for a customer’s decision to switch to a different insurance provider.

For an industry where customer acquisition and retention are equally important, and the former being a more expensive process, insurance companies rely on data to understand customer behaviour to prevent retention. Thus knowing whether a customer is possibly going to switch beforehand gives Insurance companies an opportunity to come up with strategies to prevent it from actually happening.

Given are 16 distinguishing factors that can help in understanding the customer churn, your objective as a data scientist is to build a Machine Learning model that can predict whether the insurance company will lose a customer or not using these factors.

You are provided with 16 anonymized factors (feature_0 to feature 15) that influence the churn of customers in the insurance industry

Data Description

The unzipped folder will have the following files.

  • Train.csv – 33908 observations.
  • Test.csv – 11303 observations.
  • Sample Submission – Sample format for the submission.

Target Variable: labels

Train.csv

Test.csv

Sample_Submission.xlsx

Bounties

The top 3 competitors will receive a cool AIM goodie bag.

Rules

  1. One account per participant. Submissions from multiple accounts will lead to disqualification
  2. Participants can submit any number of times for this hackathon
  3. All registered participants are eligible to participate in the hackathon
  4. This competition does not count towards our overall ranking points
  5. You will not be able to submit once you click the “Complete Hackathon” button. You may ignore this feature
  6. We ask that you respect the spirit of the competition and do not cheat
  7. This hackathon will expire on 27th April Monday at 7am IST

Evaluation

The leaderboard is evaluated using F1 Score for the participant’s submission.

More Great AIM Stories

Amal Nair
A Computer Science Engineer turned Data Scientist who is passionate about AI and all related technologies. Contact: amal.nair@analyticsindiamag.com

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