Industry Use Case

Customer Profiling Using Statistical Analysis

This project focuses on building a strong foundation on the concept of Statistical analysis and Hypothesis Testing to classify each customer into either profitable or non-profitable buckets.

Banking Customer profiling using Statistical Analysis
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    Difficulty: Advanced

    Designed for those with a technical background or industry experience

  • Asset 1
    Duration: Approximately 3 hours

Course Overview

  • Making a statistical determination utilizing experimental data requires the application of the statistical approach known as hypothesis testing. To identify which statement is best supported by the sample data, hypothesis testing compares two statements about a population that are mutually exclusive.
  • The primary source of income for banks is interest earned on various loans. Grouping clients with similar characters allows banks to make better judgments of their current and potential customers. Profiling helps in recognizing the issuer’s decisions about whom to give banking facilities to and what should be the credit limit and increase customer base, create custom products, micro-target sales and improve customer experience through focused customer relationships.
  • Learn to gather data using statistical approaches, use analytical strategies, and create compelling strategies to profile customers.

What’s included

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Lifetime Access

Access this case study for life once completed

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Flexible Scheduling

Start learning online immediately, at your own pace

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Desktop Only

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Skills you will learn

Fundamentals of Data Science

Data Management

Data Visualization

Statistical Analysis

Feature Engineering

Data Transformation

Associated Learning Tracks

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