Research on Multidimensional Trust Evaluation Mechanism of FinTech Based on Blockchain

Song, Ying; Sun, Chaohao; Peng, Yun; Zeng, Yanjun; Sun, Baolin

doi:10.1109/access.2022.3177275

Cited by 13 publications

(10 citation statements)

References 34 publications

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“…Blockchain offers decentralised peer-to-peer financial transaction security; however, security and privacy remain problems. Since public blockchain access may compromise financial transaction data privacy, blockchain growth depends on security, privacy, and secrecy [31].…”

Section: Privacymentioning

confidence: 99%

“…Lack of technological innovation and countryspecific legislation have hampered technology adoption [64]. The trust mechanism must be improved to support FinTech development as current financial regulation approaches cannot [31]. Regulation helps enterprises to adapt IT and business processes for Green IT adoption and influences regulatory changes owing to disruptive technologies [21].…”

Section: Regulationmentioning

confidence: 99%

“…Figure 3 also shows some prominent factors mentioned in the selected articles that could impact the trust for the adoption. Factors like the quality of the system [19,55,71], design [19,62], immutability [21,52], familiarity [63,65], experience [29][30][31], and awareness [33,62] of the technology, along with others, are factors that could potentially help to strengthen factors such as security, privacy, transparency, and regulation to enhance the trust for the blockchain adoption in digital payment systems.…”

Section: Other Factors Influencing Trustmentioning

confidence: 99%

“…Although trust and acceptance are widely acknowledged as crucial, the prevailing literature considers them separately in technology adoption studies. Trust is looked at from a psychological perspective and considered a subjective belief [29] that is based on confidence [3], past experiences [30,31], and evidence [29]. At the same time, acceptance is more of a behavioural intention to use the technology [32,33].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Factors Affecting Trust and Acceptance for Blockchain Adoption in Digital Payment Systems: A Systematic Review

Norbu,

Park,

Wong

et al. 2024

Future Internet

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Blockchain technology has become significant for financial sectors, especially digital payment systems, offering enhanced security, transparency, and efficiency. However, there is limited research on the factors influencing user trust in and acceptance of blockchain adoption in digital payment systems. This systematic review provides insight into the key factors impacting consumers’ perceptions and behaviours towards embracing blockchain technology. A total of 1859 studies were collected, with 48 meeting the criteria for comprehensive analysis. The results showed that security, privacy, transparency, and regulation are the most significant factors influencing trust for blockchain adoption. The most influential factors identified in the Unified Theory of Acceptance and Use of Technology (UTAUT) model include performance expectancy, effort expectancy, social influence, and facilitating conditions. Incorporating a trust and acceptance model could be a viable approach to tackling obstacles and ensuring the successful integration of blockchain technology into digital payment systems. Understanding these factors is crucial for creating a favourable atmosphere for adopting blockchain technology in digital payments. User-perspective research on blockchain adoption in digital payment systems is still insufficient, and this aspect still requires further investigation. Blockchain adoption in digital payment systems has not been sufficiently conducted from the user’s perspective, and there is a scope for it to be carried out. This review aims to shed light on the factors of trust in and acceptance of blockchain adoption in digital payment systems so that the full potential of blockchain technology can be realised. Understanding these factors and their intricate connections is imperative in fostering a conducive environment for the widespread acceptance of blockchain technology in digital payments.

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Section: Privacymentioning

confidence: 99%

Section: Regulationmentioning

confidence: 99%

Section: Other Factors Influencing Trustmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Factors Affecting Trust and Acceptance for Blockchain Adoption in Digital Payment Systems: A Systematic Review

Norbu,

Park,

Wong

et al. 2024

Future Internet

View full text Add to dashboard Cite

show abstract

“…With people's attention to the demand for wealth enhancement, commercial banks, fund companies, asset management companies, and other financial institutions have launched artificial intelligence personalized recommendation services. In the near future, the customized recommendation system of financial services will definitely become an important tool for residents' asset allocation [8][9].…”

Section: Introductionmentioning

confidence: 99%

Application of AI technology in personalized recommendation system for financial services

Yue

2024

Applied Mathematics and Nonlinear Sciences

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How to quickly and accurately retrieve the products that users are interested in from a huge amount of financial products has become a business pain point that financial institutions must solve. In this study, an interpretable EPRSA model for personalized financial service recommendations based on self-attention mechanisms is proposed by combining an LSTM model and an LDA topic model with AI technology support. A customized recommendation system for financial services is constructed by introducing the Nginx server into the Flask framework, and the design of the database and personalized recommendation module is interpreted. For the financial service personalized recommendation system proposed in this paper, its recommendation performance and system performance are tested, and the stock financial products are selected as the recommendation objects to explore its recommendation effect. It is found that the DNCG index of personalized recommendation of financial products of the EPRSA model is improved by 40.18%, the average response time of the system when the number of concurrent users is 1,000 is 1.96 s. The average quality of the personalized recommendation of the collection of stocks reaches 0.153. The customized recommendation of financial services using AI technology can select financial products based on the investor’s preference, help investors better understand the product returns, and improve the service quality of the financial industry.

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GT-NRSM: efficient and scalable sharding consensus mechanism for consortium blockchain

Shen

Yu³

et al. 2023

J Supercomput

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Blockchain is an innovative application of distributed storage, consensus mechanism, cryptographic algorithm and other computer technologies. As the underlying architecture of blockchain, consensus mechanism is the key to realize service-oriented applications of blockchain in terms of its security, efficiency and scalability optimization. In some high complexity consensus mechanism such as Practical Byzantine Fault Tolerance (PBFT), throughput is severely reduced as the number of nodes increases, and even in low complexity algorithms such as Raft, the load on leader is severely affected as the network size increases, which affecting consensus efficiency. To solve these problems, in this paper, we propose a node reliable shard model based on guarantee tree (GT-NRSM) that achieves high scalability while ensuring a certain degree of decentralization and security based on consortium blockchain. Firstly, we design a guarantee mechanism to represent the trust relationship between nodes, and then we design a reliable node selection strategy based on the guarantee mechanism to evaluate the node guarantee results and consensus behavior, determine the node trust status, and identify Article Title malicious nodes and select a list of trusted leaders. Secondly, we propose a Dual-Leaders supervision mechanism, where deputy detects the heartbeat of leader while the deputy activity is detected by consensus nodes. Finally, we use guarantee mechanism and reliable node selection strategy to design a network partitioning method to achieve high concurrent consensus for multiple partitions and greatly improve the consensus efficiency. Subsequent experiments show that the throughput of the proposed algorithm improves by 48% over Raft and is much higher than PBFT, which has higher throughput and lower consensus latency.

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Research on Multidimensional Trust Evaluation Mechanism of FinTech Based on Blockchain

Cited by 13 publications

References 34 publications

Factors Affecting Trust and Acceptance for Blockchain Adoption in Digital Payment Systems: A Systematic Review

Factors Affecting Trust and Acceptance for Blockchain Adoption in Digital Payment Systems: A Systematic Review

Application of AI technology in personalized recommendation system for financial services

GT-NRSM: efficient and scalable sharding consensus mechanism for consortium blockchain

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