DOI: 10.2308/jfar-2021-027 ISSN:

A Case Study Using Data Analytics to Detect Hail Damage Insurance Claim Fraud

Christine Cheng, Chih-Chen Lee
  • General Medicine
  • Cell Biology
  • Developmental Biology
  • Embryology
  • Anatomy

ABSTRACT

Employers require that accounting students think critically and use data analytics tools to gain valuable insights for forensic, tax, auditing, and advisory services. This case provides students with a hands-on learning experience using data analytics and encourages critical thinking. Students are tasked with using Alteryx and Tableau to prepare and analyze a fictitious storm dataset and insurance claims dataset to identify claims that may be suspicious. They create visualizations and spreadsheets that support their recommendation for further analysis. The learning objectives are: (1) develop student knowledge and ability to conduct data preparation through the “Extract, Transform, and Load” (ETL) process; (2) expand student knowledge of data analytics and fraud investigation; (3) provide students with practice in fraud investigation skills, including critical thinking and problem solving; (4) develop skills specific to data analytics and data visualization in accounting; and (5) develop effective oral and written communication skills.

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