Storm Path - Identifying Fraudulent Insurance Claims

For the final project in my Risk and Insurance class, my team and I analyzed insurance claims to identify potential fraudulent activity related to a major storm. Using the storm’s factual path data and all submitted insurance claims, we employed tools such as Microsoft Excel and ChatGPT to filter and analyze the data, compare claims to the storm’s trajectory, and create a detailed "storm path map."

Furthermore, we used Excel to calculate three key ratios to evaluate the cost of each claim relative to the reported damage, helping us identify large discrepancies. Additionally, we utilized pivot tables to compare the average cost of claims handled by different adjusters and roofing companies, further uncovering patterns and anomalies.

The project concluded with a comprehensive write-up and presentation, where we highlighted our top three suspect insurance claims and identified patterns in the data that warranted further investigation. Working with real-world data from an actual storm and comparing our findings with graduate students tackling the same challenge was a unique and rewarding experience—especially as our thorough analysis earned us the top grade in the class.