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- Title
A Case Study Using Data Analytics to Detect Hail Damage Insurance Claim Fraud.
- Authors
Cheng, Christine; Lee, Chih-Chen
- 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.
- Subjects
INSURANCE crimes; INSURANCE claims; DAMAGE claims; FRAUD investigation; DATA analytics; CRITICAL thinking; FRAUD
- Publication
Journal of Forensic Accounting Research, 2023, Vol 8, Issue 1, p287
- ISSN
2380-2138
- Publication type
Article
- DOI
10.2308/JFAR-2021-027