Abstract: The paper aims at examining the degree to which artificial neural networks are a suitable approach to aid risk management in the car financing industry. More specifically, we empirically compare a classic feedforward neural network to a recently proposed extreme learning machine. To that end, we employ a real-world credit data set from a leading car financing company in Poland is used to assess each classifier’s accuracy. To systematically study the suitability of the two methods, our study comprises multiple experimental factors including the type of the neural network, whether or not it is embedded into an ensemble learning framework, and strategies to mitigate class imbalance.

• Publication Date: 27-Sep-2015
• DOI: 10.15224/978-1-63248-071-2-25
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Abstract: To achieve a double digit growth, Bangladesh requires the right mix of human capital, policy and supportive bureaucratic structures to encourage entrepreneurship. Bangladesh must learn not only to develop and find global markets for its own industrial production, but look for it abroad and bring ideas back to be commoditized at home. The purpose of this article is to extract policy lessons from the SME development of China in the perspective of Bangladesh. The paper draws policy prescriptions to boost entrepreneurship through research, innovation, tax reform, market reform, education and training.

• Publication Date: 27-Sep-2015
• DOI: 10.15224/978-1-63248-071-2-26
• Views: 0
• Downloads: 0