dc.contributor.author | Taliani, Julius I | |
dc.date.accessioned | 2013-02-28T09:53:38Z | |
dc.date.issued | 2012 | |
dc.identifier.citation | MBA Thesis 2012 | en |
dc.identifier.uri | http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/12294 | |
dc.description | Thesis | en |
dc.description.abstract | The objectives of this study were to develop a discriminant model incorporating ratio
stability that can be used to predict financial distress in Commercial Banks in Kenya and
to identify critical financial ratios with significant predictive ability. The following ratios
were identified as significant. Net Profit / Sales, Net profit / total Assets, Current
Debt/Inventory and Total Debt/Total Assets. The findings provide evidence that the
stability of financial ratios has an impact on the ability of the firm to continue as a going
concern. Profitability ratios offer a reasonable measure of management effectiveness in
firm value creation, leverage / indebtedness ratios provide historical reasons for firm
failure while liquidity ratios constitute a measure of firms’ solvency.
An important observation is that none of the Activity and Turnover ratio was found to be
critical in predicting financial distress in commercial banks in Kenya failure prediction.
The model attained 70% and 100% correct classification in year 1 and in year 3
respectively. The findings are consistent with studies by Kiragu (1991), Kiege (1991) and
Dambolena and Khoury (1980) who concluded that profitability and leverage ratios were
crucial in predicting failure. The findings however differ with those of Altman’s (1968)
who concluded that efficiency and profitability ratios were most crucial and that liquidity
ratios were not significant.
The methodology utilized examined and justified the research design to be applied in the
study. It also stated the population of interest for the study and the sample to be used. The
data collection method that was used was provided. The data analysis technique to be
applied and the justification for its use is also given. The computer software for analyzing
the data was provided as well as what was used for presenting the findings. Finally, the
model derived checked and validated. | en |
dc.description.sponsorship | University of Nairobi | en |
dc.language.iso | en | en |
dc.subject | Finance, Commercial Banks, Kenya | en |
dc.title | Predicting Financial Distress in Commercial Banks in Kenya. | en |
dc.type | Thesis | en |
local.publisher | school of Business | en |