Using the Beneish M-score Model to Detect Financial Statement Fraud in the Microfinance Industry in Ghana

Abstract

The paper sought to investigate the effect of corporate earnings manipulation on microfinance institutional failures in Ghana. The researchers employed a quantitative investigative technique to analyse data obtained from the Bank of Ghana (BOG) on microfinance companies covering eight-year intervals. Beneish M-scores model was used to analyse the sampled data. The study found a link between earnings manipulation and business failures in the Microfinance Sector of Ghana. It found the M-score model as an effective tool for uncovering early warning signs associated with corporate earnings management, thus, averting many negative repercussions related to the practice. The research findings are based on data obtained only from the microfinance industry of Ghana over an eight-year period. Reasons behind earnings manipulation could not be deduced from the research conclusions. A qualitative inquiry must be considered in future studies to explain the reasons for this phenomenon. Collecting and analysing data from more than one sector and across other geographical boundaries may enhance the applicability of the findings in other jurisdictions. This paper provides some recommendations that help early detection of fraud in the microfinance industry. The research focuses on a sector where data is very sensitive and confidential, hence, highly prone to fraud but hardly researched. It, therefore, adds to the scanty literature on fraud in this part of the economy.