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Deep learning in finance and banking: A literature review and classification
Jian Huang, Junyi Chai, Stella Cho
Front. Bus. Res. China. 2020, 14 (2): 121-144.
https://doi.org/10.1186/s11782-020-00082-6
Deep learning has been widely applied in computer vision, natural language processing, and audio-visual recognition. The overwhelming success of deep learning as a data processing technique has sparked the interest of the research community. Given the proliferation of Fintech in recent years, the use of deep learning in finance and banking services has become prevalent. However, a detailed survey of the applications of deep learning in finance and banking is lacking in the existing literature. This study surveys and analyzes the literature on the application of deep learning models in the key finance and banking domains to provide a systematic evaluation of the model preprocessing, input data, and model evaluation. Finally, we discuss three aspects that could affect the outcomes of financial deep learning models. This study provides academics and practitioners with insight and direction on the state-of-the-art of the application of deep learning models in finance and banking.
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Risk identification and prioritization in banking projects of payment service provider companies: an empirical study
Mohammad Khalilzadeh, Laleh Katoueizadeh, Edmundas Kazimieras Zavadskas
Front. Bus. Res. China. 2020, 14 (2): 145-171.
https://doi.org/10.1186/s11782-020-00083-5
Identifying risks and prioritizing is important for payment service provider (PSP) companies to get banking projects and gain more market share. However, studies regarding the identification of risks and causal relationships are insufficient in the Iranian PSP industry and the industry is unique because of its characteristics. In this study, 30 experts involved with PSP companies are employed as the research sample. Eleven key risks and Forty-six sub-risks are also identified. Subsequently, the fuzzy decision-making trial and evaluation laboratory technique is applied to determine the effective and affected risks and the severity of their effects on each other. Finally, all risks are ranked. Due to the internal interrelationships of the main risks, the weight of each risk is calculated via the fuzzy analytic network process. As the second-level risks have no significant interrelationships, they are ranked via the fuzzy analytical hierarchy process. Moreover, the best-worst method is used to ensure that the obtained rankings are reliable. This study identifies the risks affecting the loss of banking projects and determines the impacts of these risks on each. A sensitivity analysis is then conducted on the weights of the criteria, and the results are compared.
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Does reputation of sponsors matter in IPO? Evidence from Hong Kong
Wilson H. S. Tong, Michael B. T. Wong
Front. Bus. Res. China. 2020, 14 (2): 172-195.
https://doi.org/10.1186/s11782-020-00081-7
Contrary to other markets where underwriters perform a combined role of underwriting and sponsoring in an Initial Public Offering (IPO), IPO issuers in Hong Kong must appoint at least one sponsor in addition to the underwriters. The splitting of the single role of underwriters into two separate ones offers an ideal setting to disentangle the effects of the two roles and to examine which of the two roles—sponsor or underwriter—is more important in explaining IPO underpricing and initial volatility in the Hong Kong equity market. Interestingly, our findings provide supportive evidence that the sponsor reputation does matter in an IPO and it is even more significant than the underwriter reputation in explaining the IPO underpricing phenomenon. Given the recent high-tech fervor, our research goes deeper to examine specifically the role of sponsors on high-tech firms, with results indicating that the reliance on sponsors is higher for traditional issuers than for technology firms. We further discover that sponsors and underwriters are playing substitution roles rather than complementary roles. In order to examine the regulatory policy impact, our research also compares the role of IPO sponsors before and after the launch of the new sponsor regulatory regime in 2013. The empirical findings lend support to our argument that after the launch of the new regulations, public awareness of sponsors is raised, respect towards more reputable sponsor increases, and thus, the role of sponsors becomes more important than before.
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6 articles
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