The product is to offer microloans to consumers in emerging markets Kenya, Mexico, India

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Introduction:

The product is to offer microloans to consumers in emerging markets (Kenya, Mexico, India). Over that time period, the product has lent money to millions of satisfied customers. Some of the customers use the product regularly to help grow their businesses, others use it for more on-demand expenses. The company is in the process of defining an “Active Customer” metric that helps it understand the landscape of new customers, active customers, at-risk active customers and churned customers. This take-home challenge is to help the company define its Active Customer classification by reviewing sample historical data. 

Deliverable:

Using the sample data attached, please provide the following analysis using R-Studio:

●  A definition for an Active A customer at Tala, including the cutoff threshold for how long to consider a customer active

●  A summary of the Customer Retention Rate based on your recommended Active Customer definition

●  Any insight into what next steps the company should take to help predict when a customer is at risk of churning

●  Attach any code or documents you created to help you develop your recommendation and summary 

Data:

You are being provided a log of application and loan disbursement history for all customers who signed up in Q1 of 2017. Each row in this data set represents a loan application (loan_application_id) made by the customer (person_id) and includes information about the loan including:

●  Date of Application

●  Approval Decision of Application

●  Disbursement Date of Funds to Customer

●  Loan Amount Disbursed

●  Number of Repayments made toward the loan

●  Due Date

●  Flag Indicating if Loan is Currently Outstanding 

Analysis:

Please perform all analysis and visualizations in R-Studio.

Attachments:

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