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Insurance Claims Analysis for SecondCars Company

Insurance Claims Analysis for SecondCars Company author
Amit Choudhary
Last updated at Tue Nov 15 2022
Insurance Claims Analysis for SecondCars Company blog cover

Problem Statement

Second Cars is one of the leading used car sales giants with a presence in North America and Europe region. It has a presence across 120 markets and primarily deals with buying and selling used cars. It sensed this business need early and has plans to integrate services like vehicle inspection, certification, insurance, and delivery. The tie-ups with leading insurance service providers, it has a history of insurance claims against the sold cars.

The company's next big task is to validate, clean, and integrate this data with its sales data. Some of the important business rules related to the business process:

  • Major Damage & Total loss cases need to be expedited. These are termed High visibility incidents.
  • All incidents where injury claims are highest among injury, vehicle, and property are called High response cases.
  • All incidents which are both High visibility and High response, need to be processed within 2 days of logging the claim. Any delay must be reported.
  • All incidents where the State of incidence is different from the State where the policy was issued are liable to delay (due to legal involvement from the 2 different states). The company wishes to minimize such cases where the States are different.
  • Second Cars wishes to track all car sales where the vehicle is not insured/does not have a history of insurance claims. Such sales need to be highlighted.‍

Congratulations.!! You are hired as a Data Analyst by Second Cars and the following are your responsibilities.

  1. Devise questions, metrics, and dimensions concerning the given problem statement
  2. Collect, clean, and process the data using SQL, Python
  3. Answer client questions through data wrangling in SQL, Python

Learning Objectives

  • Getting familiar is working with data models
  • Ingesting data from different sources
  • Domain-oriented analysis
  • Developing an understanding of the Insurance domain and its KPI
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