Detection of fraud in financial statements using Beneish ratios for companies listed at Nairobi Securities Exchange

Abstract

Purpose: To determine and analyze financial statement fraud amongst Nairobi securities exchange listed companies.

Methodology: The research design that was used in this study was descriptive research design in collecting the data from the respondents. Descriptive research is a fact-finding approach generating a cross sectional study of the present situation. The population of this study will consist of all firms listed at the NSE. There are 62 companies listed at the NSE and this study will seek to determine earnings manipulation and fraudulent financial reports using the Beneish M- Score for these companies. The study will adopt a census for the companies listed at the NSE as at 31st December 2018

Findings: The study found out that the 8 varibales used by beneish capture all possible pain points for earnings managers. Thus by evaluating them and subjecting them to the formula a reliable Z -score of earnings manipulation existence is developed, also named M-score by its developer Messod Beneish. The probability is thus obtained  from the Z-score tables. The 8 Variables  studied are generally classified as  manipulation signals  and motivation signals. Manipulation signals as stated by Mcleavy (2013) are the days sales in receivables index DSRI ,asset quality index AQI ,depreciation index, DEPI  and total accruals to total assets ,TATA. Whereas motivational signals are gross margin index  GMI, sales growth index SGI, selling, general, and administrative index SGA and leverage index LEVI. From  the M-scores ,the companies that were likely manipulators all had peculiarities in their financials as measured by the variables at more than one year over the period of study.

Implications: The M-score cannot identify with full certainty whether a firm is a manipulator however at the -2.22 cut-off ,read from the cumulative normal table this z-score gives a probability of 0.0132, a firm has a probability of 0.986 to be classified innocent. 74 times the chances of being labeled a manipulator .

Value: The findings could be of use to policymakers as well as academics as a literature source as they seek to build watertight methods of discovery. Furthermore, policy-making institutions and accounting regulators such as Institute of Certified Public Accountants (ICPAK) can also benefit from the findings of the study by determining whether to come up with the decision of developing more rules to advance the quality of financial information reported by companies. Other intended beneficiaries are institutional and retail investors while analyzing the financial performance of a firm should holistically consider both financial, non-financial performance and the cash position specifically training their antennae to detect fraud presented as truth.