Ernst & Young Case Study
The evaluation of interest expense and revenue in the case study were advised on analytical procedures discussed by IAPC (2001, pp. 92-94). In this respect, a regression analysis was performed to assess the association between prime rates and revenue and expense rates. Following the analysis, Martin could simplify the information in Exhibit 1 as follows (Excel sheet for calculations):
| Exhibit 1: | ||
| Particulars | Feb | April |
| Total Deposits | 729,368,000.00 | 742,473,000.00 |
| Average Interest rate | 4.34 | 3.87 |
| Total interest Expense | 31,641,624.92 | 28,743,914.10 |
The average interest rate is evaluated by assessing the variation in prime rates with real interest rates calculated from the monthly deposit values and corresponding interest value from Jan 1998 to September 2004. The coefficients obtained from the regression analysis are used to calculate the expected average rate for total deposits by solving the regression equation (y = k + βXi), using the provided prime rates for February and April. From the regression equation (see excel sheet), variability in prime rates is noted to explain 87.18 percent variability in the average interest rates. As such, Martin should take into consideration the unexplained variability when assessing whether the reported interest expense in the financial statement reflects a fair and true position of the entity.
The corresponding simplification of exhibit2 is as follows:
| Exhibit 2: | ||
| Particulars | Feb | April |
| Interest Revenue from loans | 708,294,000.00 | 710,320,000.00 |
| Interest rate | 4.51 | 4.05 |
| Interest from liquid investments | 31,914,133.98 | 28,758,193.10 |
| Interest from non-liquid investments | 55,554,358.10 | 659,394.20 |
| Total interest revenues | 87,468,492.08 | 29,417,587.30 |
The interest revenue from loans is also evaluated through the assessment of how variations in prime rates, are associated with calculated monthly interest rate (excel sheet), from the monthly values of loans and loan revenues recorded. The regression equation (excel sheet) indicates that variations in the prime rate explain 83.59 percent variations in monthly interest rates. As such, as in the case of expenses, Martin will need to consider the unexplained variations to determine whether a true and fair position is reflected in the total interest revenues indicated. Apart from this, Martin will need to consider interest revenue from non-liquid investments separately since variations in such were not associated with prime rate variations – they were not related to the bank’s loans whose interest rates are determined by changes in prime rate.
Reference
International Auditing Practices Committee (IAPC) (2001). International auditing practice statement (IAPS) 1006: Audits of the financial statements of banks. Retrieved from http://www.ifac.org/sites/default/files/downloads/b006-2010-iaasb-handbook-iaps-1006.pdf
Last Completed Projects
| topic title | academic level | Writer | delivered |
|---|