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Abstract
Internet of Things (IoT)–based financial systems leverage the capabilities of blockchain and artificial intelligence (AI) to enable seamless transactions and data exchange between devices. IoT‐based financial systems involve interconnected devices and services, such as payment terminals, wearables, and smart appliances, which collect, transmit, and process sensitive financial information. The study explores security methods incorporated in the financial systems designed using IoT and blockchain technologies to improve the background features. The study data were gathered from Complaint Data from the Consumer Financial Protection Bureau 2018–2022, and data‐based analysis is used in this study for detecting illegitimate interrupted transactions. Propensity Score Matching (PSM) is used for the robustness and endogeneity test; descriptive statistics is utilized in this study. Financial security systems are introduced to reduce the forging and breaching of intruders amid transactions. This study offers a novel contribution to the field of blockchain technology by furnishing a comprehensive analysis of the features of IoT‐based financial security systems from the perspective of the transaction, broadening the understanding of the feature focusing on financial security, and providing practical recommendations to address the features of IoT‐based financial security systems in blockchain technology. The study highlights how IoT devices can securely record and verify financial transactions by leveraging the blockchain's distributed ledger, preventing tampering or unauthorized access. The results of the study identify that the TS3 program relies on the transaction gaps between financial sessions, security requests between successive transactions, and sessions saved depending on the time delay. The study finds that sessions were analyzed for violations and fraud using information stored on the blockchain. The study suggests the design and building of devices and sensors in an IoT in financial security systems. Transparency should contribute to setting data privacy and safety problems in financial security systems.
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