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- Kara, Alper, et al.
(author)
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Achieving the United Nations' sustainable development goals through financial inclusion : A systematic literature review of access to finance across the globe
- 2021
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In: International Review of Financial Analysis. - : Elsevier. - 1057-5219 .- 1873-8079. ; 77
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Research review (peer-reviewed)abstract
- Access to credit may have a direct effect on achieving United Nations (UN) Sustainable Development Goals (SDGs) in ending poverty, improving health and education, and reducing inequality. In this paper, we systematically review the growing empirical evidence on whether individuals' demographic characteristics (such as gender and race) and socio-economic features (such as income and education) effect their ability in accessing credit. Our survey covers peer-reviewed articles providing empirical evidence, using quantitative and qualitative data, published between 2000 and 2020 (February). We find that having more education and/or being more financially literate increases households' and entrepreneurs' access to credit. Individuals with lower income and less wealth are less likely to obtain credit from the mainstream financial institutions. In emerging countries, women are more likely to be rejected and deprived from formal credit, and pay higher cost. Non-Whites, ethnic minorities, disabled people and immigrants are also more likely to be excluded from the formal credit markets. We find that abovementioned credit deprived segments of the society resort to fringe finance providers, such as pay-day lenders or pawnbrokers, with higher costs. These findings are remarkably similar across developed and developing countries. Finally, we provide direction for further research in achieving SDGs through financial inclusion and access to credit by highlighting various shortcomings of the existing literature and empirical evidence.
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| 2. |
- Tan, Hongwei, et al.
(author)
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Bioinspired multisensory neural network with crossmodal integration and recognition
- 2021
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In: Nature Communications. - : Nature Research. - 2041-1723. ; 12:1
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Journal article (peer-reviewed)abstract
- The integration and interaction of vision, touch, hearing, smell, and taste in the human multisensory neural network facilitate high-level cognitive functionalities, such as crossmodal integration, recognition, and imagination for accurate evaluation and comprehensive understanding of the multimodal world. Here, we report a bioinspired multisensory neural network that integrates artificial optic, afferent, auditory, and simulated olfactory and gustatory sensory nerves. With distributed multiple sensors and biomimetic hierarchical architectures, our system can not only sense, process, and memorize multimodal information, but also fuse multisensory data at hardware and software level. Using crossmodal learning, the system is capable of crossmodally recognizing and imagining multimodal information, such as visualizing alphabet letters upon handwritten input, recognizing multimodal visual/smell/taste information or imagining a never-seen picture when hearing its description. Our multisensory neural network provides a promising approach towards robotic sensing and perception. Human-like robotic sensing aims at extracting and processing complicated environmental information via multisensory integration and interaction. Tan et al. report an artificial spiking multisensory neural network that integrates five primary senses and mimics the crossmodal perception of biological brains.
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