Project 2 The Furniture Fire Case Presented by Group Roots Case History In 1992, an accidental fire destroyed a furniture warehouse in Tampa, FL. Upon these findings, the furniture company made a claim to their insurance company for demand of lost profits. In doing so, the furniture company submitted a profit calculation, or the GPF, of the burned inventory. Determining Factors Because there were no sales receipts and the prices were unknown, the furniture company used 253 random invoices pulled from the 3005 total invoices from 1991 to calculate the average GPF.

These invoices were then separated into 2 groups. One consisting of 134 samples and the other one had 119 samples. The GPF calculated for the 134 group was 50. 5%. The 119 group GPF was 51. 0%. The average GPF for the two was 50. 8%. Because the average GPF for this type of business is typically 48%, the insurance company contested this while the furniture company maintained that the samples were completely random. To put this in terms we can all understand, we must know that 1% is equal to $16,000.

In essence, the furniture company is claiming a loss of $812,800 while the insurance company thinks the maximum value of this case is $768,000. The difference being $44,800 in favor of the furniture company. Because of this dispute, a lawsuit was filed. During the discovery phase of the lawsuit, when both side submit all of the information they have to each other, the insurance company hired an independent CPA firm to calculate the GPF. Although we did not get those results, we had enough information given to us to determine if the furniture company had committed some type of fraud.

Assignment Our assignment for this project is to determine if there was fraudulent activity on the part of the furniture company. To determine fraud, we had to find the probability that a standard normal random variable exceeded the GPF samples given to us. So we used the following formula: 134 Random Samples P (z > 50. 6) = 50. 6– 48. 901 13. 8291 / v134 = 1. 699 1. 195 = 1. 422 = 0. 4222 – 0. 5 = 0. 0778 Mean = 48. 901 Standard Deviation= 13. 8291% Sample Size = 134 Table for Normal Distribution = 1. 22 119 Random Samples P (z > 51. 0) = 51. 0– 48. 901 13. 8291 / v119 = 2. 099 1. 268 = 1. 655 = 0. 4505 – 0. 5 = 0. 0495 Mean = 48. 901 Standard Deviation= 13. 8291% Sample Size = 119 Table for Normal Distribution = 1. 655 Mean for both random samples is 0. 00385 or 0. 3%. What does the 0. 3% mean to us? It means that the GPF numbers submitted to the insurance company had a 0. 3% chance of being accurate. In other words, we contend that the likelihood of fraud in part of the furniture company is evident.