Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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The improvement of financial sector in Tanzania by the introduction of financial reforms was expected to improve the efficiency of the financial sector which includes lowering the Interest rate spread. Beyond the expectations of the reforms the interest rate spread is high with no sign of narrowing down. This study was set to analyse the determinants of Interest rate spread in Tanzania commercial banks focusing on the internal characteristics. Data from commercial banks incorporated before 2002 were extracted and analysed using SPSS 16 and regression model was established. The results indicate that operating costs, loan loss provisioning, and liquidity risk increases the interest rate spread. While factors of required reserve and non-interest income decrease the interest rate spread.
Edward Ntulo. 2018. \u201cDeterminants of Interest Rate Spreads in Commercial Banks– A Case of Tanzania\u201d. Global Journal of Management and Business Research - C: Finance GJMBR-C Volume 18 (GJMBR Volume 18 Issue C6): .
Crossref Journal DOI 10.17406/GJMBR
Print ISSN 0975-5853
e-ISSN 2249-4588
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Total Score: 101
Country: Tanzania
Subject: Global Journal of Management and Business Research - C: Finance
Authors: Edward Ntulo (PhD/Dr. count: 0)
View Count (all-time): 155
Total Views (Real + Logic): 2883
Total Downloads (simulated): 1505
Publish Date: 2018 11, Wed
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The improvement of financial sector in Tanzania by the introduction of financial reforms was expected to improve the efficiency of the financial sector which includes lowering the Interest rate spread. Beyond the expectations of the reforms the interest rate spread is high with no sign of narrowing down. This study was set to analyse the determinants of Interest rate spread in Tanzania commercial banks focusing on the internal characteristics. Data from commercial banks incorporated before 2002 were extracted and analysed using SPSS 16 and regression model was established. The results indicate that operating costs, loan loss provisioning, and liquidity risk increases the interest rate spread. While factors of required reserve and non-interest income decrease the interest rate spread.
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