Too much or less? The effect of financial literacy on resident fraud victimization

Du, Wenhu; Chen, Min

doi:10.1016/j.chb.2023.107914

Cited by 9 publications

(4 citation statements)

References 96 publications

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“…According to the transfer hierarchy, it can be divided into instancebased transfer learning, feature-based transfer learning, model-based transfer learning, and relationbased transfer learning. Based on the transfer direction, it can be categorized as unidirectional transfer learning and bidirectional transfer learning (Du & Chen, 2023). Depending on the transfer purpose, it can be classified as inductive transfer learning, transductive transfer learning, and generalized transfer learning.…”

Section: Transfer Learningmentioning

confidence: 99%

Deep Learning-Powered Financial Product Recommendation System in Banks

Li,

Song

2024

Journal of Organizational and End User Computing

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With the rapid evolution of financial technology, the recommendation system for financial products, as a crucial technology to enhance user experience and reduce information search costs, is increasingly becoming the focus of the financial services sector. As market competition intensifies, the diversity of user demands, coupled with the continuous expansion of financial product types, has exposed limitations in traditional recommendation systems regarding accuracy and personalized services. Therefore, this study aims to explore the application of deep learning technology in the field of financial product recommendations, aiming to construct a more intelligent and precise financial product recommendation system. The metrics we focus on include precision, recall, and F1-score, comprehensively evaluating the effectiveness of the proposed methods. In terms of methodology, we first employ a Transformer model, leveraging its powerful self-attention mechanism to capture the complex relationships between user behavior sequences and financial product information.

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Section: Transfer Learningmentioning

confidence: 99%

Deep Learning-Powered Financial Product Recommendation System in Banks

Li,

Song

2024

Journal of Organizational and End User Computing

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“…This is owing to the development of financial markets that require households to make more complex financial decisions than ever [ 13 ]. Financial literacy enhances investors’ stock market participation [ 14 ], increases household demand for risky financial assets [ 15 ], improves the identification of fraud in risky decision-making [ 16 ], and promotes financial inclusion [ 17 ]. Additionally, an individual’s financial literacy, experiences, attitudes, and behaviors can contribute to their financial decision-making [ 18 ].…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

“…The growing importance of financial literacy is gaining prominence with the increasing interconnectedness of global economies and information accessibility. Although previous studies examined many effects of financial literacy [14][15][16][17], there is still a dearth of scholarly investigation of the correlation between financial literacy and stock returns, particularly within the Chinese stock market context. This study addresses the aforementioned research gap by uncovering a positive correlation between the prevalence of financial literacy and microhousehold stock returns.…”

Section: Financial Literacy Helps Improve Stock Returnsmentioning

confidence: 99%

Impact of financial literacy on household stock profit level in China

Luo,

Azam,

Wang

2023

PLoS ONE

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The popularization of financial literacy has become a global trend, with governments across the world expressing commitment to continuously enhancing the financial literacy of their citizens to improve the country’s overall financial well-being. However, there is a lack of research evaluating the actual effects of financial literacy on Chinese households. This study first investigated the micro impact of financial literacy on the household stock profit level using data from the 2019 China Household Finance Survey. As most existing studies use factor analysis to measure financial literacy from a single dimension of financial knowledge, our study additionally used the entropy method to construct a composite evaluation system of financial literacy from four dimensions: financial skills, knowledge, attitudes, and behaviors. The ordinary least squares model was utilized as the primary regression model to estimate the correlation, and the average financial literacy of other households in the same community was selected as an instrumental variable. Further instrumental variable regression analysis was conducted using the two-stage least squares method. Three robustness tests were performed to ensure the reliability of the research findings. The results demonstrate that financial literacy significantly enhances household stock profit levels. The mediation effect analysis indicates that financial literacy affects stock profit levels through financial information attention. Moreover, financial literacy has a more substantial promoting effect on stock profit levels for households with members working for state-owned enterprises and those living in first-tier cities. This study confirms the value of financial literacy; identifies important channels for residents to increase their property income; and provides important guidance for the government, educational organizations, and financial institutions. This also injects more vigor into market participation to improve the persistently sluggish Chinese stock market.

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“…Multimodal robots can interact with human users, through emotion recognition and expression, facial expression analysis, and speech synthesis and recognition. This enhances their ability to interact with people (Tang et al, 2023;Du & Chen, 2023).…”

Section: Introductionmentioning

confidence: 99%

Breaking Boundaries Between Linguistics and Artificial Intelligence

Wang,

Tie,

Jiang

et al. 2023

Journal of Organizational and End User Computing

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There is a wide connection between linguistics and artificial intelligence (AI), including the multimodal language matching. Multi-modal robots possess the capability to process various sensory modalities, including vision, auditory, language, and touch, offering extensive prospects for applications across various domains. Despite significant advancements in perception and interaction, the task of visual-language matching remains a challenging one for multi-modal robots. Existing methods often struggle to achieve accurate matching when dealing with complex multi-modal data, leading to potential misinterpretation or incomplete understanding of information. Additionally, the heterogeneity among different sensory modalities adds complexity to the matching process. To address these challenges, we propose an approach called vision-language matching with semantically aligned embeddings (VLMS), aimed at improving the visual-language matching performance of multi-modal robots.

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Too much or less? The effect of financial literacy on resident fraud victimization

Cited by 9 publications

References 96 publications

Deep Learning-Powered Financial Product Recommendation System in Banks

Deep Learning-Powered Financial Product Recommendation System in Banks

Impact of financial literacy on household stock profit level in China

Breaking Boundaries Between Linguistics and Artificial Intelligence

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