Determinants of business loan default in Ghana

The initiation, funding, servicing and monitoring of loans by financial intermediaries has been done without regard to some critical factors which could have averted the likelihood of default. The study aimed at measuring the extent that owner-specific, borrower-specific, loan and lender-specific characteristics could determine the probability of loan default. The study used logistic regression for 224 business customers of a bank in Ghana from its nation-wide branches. The study found that owner's extra income (ownership characteristics), multiple borrowing, diversion of loan purpose (borrower characteristics), loan price, loan purpose, loan age, repayment plan (loan characteristics) and underfunding (lender characteristics) significantly determined the probability of business loan default. The overall model predicted up to 78.5% of variations in the likelihood of default. The hierarchy of strong determinants given by their odd ratios were loan purpose (47.9 times), underfunding (19.2 times), diversion of loan purpose (11.7 times) multiple borrowing (9.4 times) and owner's extra income (8.2 times). The study can conclude that financial intermediaries should be wary of the credit granting process taking cognisance of ownership, borrower, loan and lender characteristics especially the significant predictors. Combining quantitative and qualitative variables as determinants of default could be considered in futureWe would like to acknowledge the anonymous bank (staff and customers) for responding to the questionnaires and providing vital information for this research. Again, we are grateful to Dr. Jordi Moreno Gené (Univ of Lleida, Spain), Kwame Oduro Amoako (Univ of Canterbury, New Zealand) and Ernest Yeboah Acheampong (Univ of Grenoble, France) for the peer review work they did before final submission

Deep adaptive anomaly detection using an active learning framework

Anomaly detection is the process of finding unusual events in a given dataset. Anomaly detection is often performed on datasets with a fixed set of predefined features. As a result of this, if the normal features bear a close resemblance to the anomalous features, most anomaly detection algorithms exhibit poor performance. This work seeks to answer the question, can we deform these features so as to make the anomalies standout and hence improve the anomaly detection outcome? We employ a Deep Learning and an Active Learning framework to learn features for anomaly detection. In Active Learning, an Oracle (usually a domain expert) labels a small amount of data over a series of training rounds. The deep neural network is trained after each round to incorporate the feedback from the Oracle into the model. Results on the MNIST, CIFAR-10 and Galaxy Zoo datasets show that our algorithm, Ahunt, significantly outperforms other anomaly detection algorithms used on a fixed, static, set of features. Ahunt can therefore overcome a poor choice of features that happen to be suboptimal for detecting anomalies in the data, learning more appropriate features. We also explore the role of the loss function and Active Learning query strategy, showing these are important, especially when there is a significant variation in the anomalies

Co-management and Traditional Fisheries: The Case of Fante Fishers in Elmina, Ghana

Co-management has widely been recognized as an alternative approach to addressing natural resource crises and diverse environmental concerns. In line with this, the Ghanaian fishery sector introduced co-management as an institutional approach to manage natural resources. However, studies still reiterate that, the traditional fishery sector is still in decline, which have affected the livelihood of communities that depends on the resource and resulted in Ghana becoming a net importer to meet the country’s fish requirements, which is likely to increase due to the growing population. The aim of this study therefore is to understand the factors contributing to the decline of the sector despite the adoption of co-management. Following a qualitative approach, the study involved Fante fishers in Elmina to understand how co-management have influenced traditional fishing. The study further seeks to identify constraints that impede the successful implementation of co-management. By exploring the economic, social and environmental impacts of co-management, divergent issues were raised from respondents. Research findings reveals that weak institutional framework, lack of active participation, empowerment and trust as the challenges that contributes to the underperformance of co-management. From discussions and analysis, general lessons and recommendations are drawn from the study

DEFORMATION-BASED EXCAVATION SUPPORT SYSTEM DESIGN METHOD

Development in urban areas around the world has steadily increased in recent years. This rapid development has not been matched by the ever decreasing open space commonly associated with urban centers. Vertical construction, thus, lends itself a very useful solution to this problem. Deep excavation is often required for urban construction. Unfortunately, the ground movements associated with deep excavation can result in damage to adjacent buildings. Thus, it is critically important to accurately predict the damage potential of nearby deep excavations and designing adequate support systems. A new design method is proposed, as an attempt, to address the problem. The method is semi-empirical and directly links excavation-induced distortions experienced by nearby buildings and the components of the excavation support system. Unlike, the traditional limit equilibrium approach, the method is driven by the distortions in adjacent buildings. It goes further to propose a preliminary cost chart to help designers during the design phase. The benefit is that initial cost is known real time and will help speed up making business decisions. A new design flowchart is proposed to guide the designer through a step-by-step procedure. The method is validated using 2D Plaxis (the finite element program) simulation. Though the nature of deep excavation is three-dimensional, a plane strain condition is valid when the length of the excavation is long. Hence, two-dimensional finite element simulation was considered appropriate for this effort. Five hypothetical cases were compared and the model performed very well. The lack of available literature on this approach made verification difficult. It is hoped that future case histories will be used to ascertain the veracity of the deformation-based design method

The Impact of Gas Flaring On Man and His Environment and the Way Out

The nature of flaring processes has created a severe impact on man and the environment. Massive environmental degradation as a result of flaring activities has led to fluctuations in climate as well as depletion of the vegetation cover through acid rain. Findings have been made on some harmful gases released into the atmosphere that have effects on the environment and also on man. In order to control these effects by ensuring a clean atmosphere and environment, a new flaring model (DanMat flaring model) has been suggested. The model uses smoldering mechanism to reduce the amount of heat released into the atmosphere during conventional flaring by 60%. It also uses scavengers to oxidize harmful gas produced during flaring activities into less harmful ones. With this model one can flare gas without polluting the environment since it reduces the emissions of harmful gases during flaring

Assessment, Student Learning and Classroom Practice: A Review

Assessment in its various forms has always been a central part of educational practice.  Evidence gleaned from the empirical literature suggests that assessment, especially high stakes external assessment has effect on how teachers teach and consequently, how students learn. Through focus group discussions, this paper draws upon the experiences of 12 tutors and 18 student-teachers in 3 colleges of education in Ghana. The findings show that although teachers are expected to nurture evaluative thinking skills in their pupils/students this is not reflected in the assessment and teaching and learning practices of student-teachers. This paper argues that for teachers to be effective in promoting the desired goals of the basic school curriculum, greater recognition must be accorded to the influence of assessment on teaching and learning, the understanding of which could arguably play an important role in introducing changes that will promote the cognitive processes and thinking skills desired in our schools and classrooms. Keywords: Assessment, teaching and learning, teacher training, classroom practic

Impact of Micro Credit on Rural Farming Activities: The Case of Farming Communities Within Sunyani Area

Most MFIs especially rural banks have performed creditably well in their operations and have contributed a lot towards agricultural development. The study seeks to investigate the impact of micro credit on farming activities but specifically to determine the impact of micro credit on labour employed, working capital, output and income of farmers and other forms of support rural banks give to farmers. A total of 103 farmers were randomly selected from farmer clients of a rural bank to respond to close-ended questions. Paired samples t-test was run to determine the differences and impact of the credit intervention on the four dependent variables. A modified Eta squared formula and paired samples correlation were used to determine the impact of the independent on the dependent variables.The result found significantly large effect of the micro credit intervention on the labour employed, working capital, output and income of farmers. All the dependent variables had increased during the period under study although all the increases cannot be attributed to the credit intervention only. Apart from the credit, other forms of support given to farmers include improved and subsidized farm inputs like fertilizer, seedlings and other inputs