Analyzing Fraudulent Claims in Insurance

Insurance
case study

Business Impacts

Fraud Claims Analytics

Billions of Dollars in Cost Savings

Customer Key Facts

  • Location : North America
  • Industry : Insurance

Problem Context

Fraudulent claims can cost companies billions of dollars per year. Building a dashboard on Looker can help insurance agencies improve the fraud detection process for future claims.

 

Challenges

 

  • Obtaining claims data in .CSV format
  • Pulling data into Google’s BigQuery and process the raw files
  • Bringing data to Looker from BigQuery and visualizing multiple metrics
  • Collecting labeled insurance claims data from open sources
  • Determining key characteristics that lead to a fraudulent claim
  • Creation of customized fields to generate relevant insights

Technologies Used

Cloud Storage

Cloud Storage

Google's BigQuery

Google's BigQuery

Looker

Looker

Building a Looker Dashboard for Insurers to Detect Fraudulent Claims

Solution

The customer is one of the largest provider of supplemental insurance in the United States, providing financial protection to more than 50 million people worldwide. They wanted to determine the probability of a claim being fraudulent based on historical data and understand the interrelationship between different dimensions in claims. Quantiphi built a dashboard on Looker that provides data visualization techniques and insight generation to help the customer better detect fraudulent claims.

Result

  • Insights are derived from historical data, while also highlighting the characteristics of fraudulent claims
  • Determines key relationships between features and helps create a solid foundation for machine learning
  • Improved fraud prevention and detection process for future claims

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