As the scenario of telecom network fraud intensifies, the development of anti-fraud models has become a focal point in financial technology, including banking sectors. Traditional anti-telecom fraud models, which primarily rely on expert rules and machine learning methodologies, are beset with limitations such as poor real-time performance and high false favourable rates, leading to biased predictive outcomes. This paper introduces a novel anti-fraud model: The Dynamic Quantification Anti-Fraud Model grounded in Real-time Transaction Flows to address these issues. This model combines multiple F-Beta features linearly, employs a DML (Double Machine Learning) framework for feature weight quantification, and conducts instantaneous risk assessments of account transactions. By dynamically adjusting feature weights based on historical single-feature false favourable rates and the branch’s anti-fraud tolerance capacity, it significantly improves model performance and the efficiency of fraud prevention. Using transaction detail data of implicated cards from a case bank spanning January to June 2023 as an example for modelling, the validation sample recall rate reached 0.506. Post-deployment, the model facilitated a 30-percentage point reduction in the proportion of implicated cards within six months at the bank, alongside a substantial drop in its ranking among peers concerning the number of fraud cases. This comprehensive improvement solidly validates the precision and efficacy of the proposed model.

This study investigates the influence of perceived external control and computer playfulness on behavioral intention to adopt mobile banking, with perceived ease of use (PEOU) as a mediator. Mobile banking adoption is driven by factors beyond basic usability, including security, personalization, and trust. While the Technology Acceptance Model (TAM) provides a foundation for understanding user acceptance, this research extends it by focusing on the roles of perceived external control (beliefs about external factors impacting banking outcomes) and computer playfulness (enjoyment derived from the user experience). Previous studies suggest that financial control significantly affects use intentions, with ease of navigation enhancing users' sense of control. Similarly, the enjoyment derived from mobile banking increases engagement and adoption. However, security and privacy concerns remain paramount. The Technology Acceptance Model's third version, TAM3, which incorporates social influence and external factors, acknowledges the complexity of technology adoption, but its focus on individual-level influences and complexity can be seen as limitations. Therefore, this study explores the importance of integrating additional constructs, such as trust and emotional responses, along with regulatory compliance, to develop a more comprehensive understanding of user behavior. This study examines the interplay of computer playfulness and perceived external control with mobile banking adoption, seeking to determine which factors have the most significant impact on user behavior. These insights are intended to help financial institutions optimize their mobile banking offerings through user-centric design and robust security measures to promote widespread adoption.

This study examines the roles of Perceived External Control (PEC) and Computer Playfulness (CP) in shaping users' Behavioral Intention (BI) to adopt mobile banking, alongside Perceived Ease of Use (PEOU) within the Technology Acceptance Model (TAM) (Mathew, Sulphey, & Prabhakaran, 2014). PEC refers to users' beliefs about their ability to control the mobile banking environment, which can lead to increased confidence and BI (Marpaung, Dewi, Grace, Sudirman, & Sugiat, 2021). CP is characterized by enjoyment and engagement, positively influencing users' attitudes and BI (Salah & Ayyash, 2024). The study highlights the significance of PEC and CP in enhancing PEOU, which explains 65% of the variance in BI. PEC allows users to feel in command, reducing anxiety and enhancing user confidence (Gu, Lee, & Suh, 2009). CP contributes to a more enjoyable interaction, encouraging exploration and usage (Zhang, Lu, & Kizildag, 2018). PEOU acts as a crucial mediator between PEC, CP, and BI, indicating that users who find mobile banking easy to use are more likely to adopt it (Obaid, 2021). The research emphasizes the importance of enhancing PEOU to boost user adoption rates in mobile banking services (Aldammagh, Abdeljawad, & Obaid, 2021). However, factors such as trust and perceived risk also play critical roles in user acceptance, suggesting a multifaceted approach is necessary (Illia, Ngniatedema, & Huang, 2015; Obaid, 2021). By integrating playful elements and enhancing users' perceptions of external control, banks can improve PEOU and user satisfaction, aligning with the TAM and emphasizing the importance of perceived enjoyment and control in fostering user engagement.

In today's digital landscape, mobile banking has become a core element of the financial sector, providing both convenience and greater accessibility for customers. Nevertheless, identifying the elements that truly drive user adoption and subsequent engagement remains a significant hurdle for banking institutions. This research sets out to investigate the nuanced aspects of how users adopt technology, focusing specifically on the context of Hangzhou City Commercial Bank. By exploring the lasting impact of factors such as perceived external control and an individual's computer playfulness, this study aims to deepen understanding regarding the intentions and actual behaviors demonstrated by those who use mobile banking services. Drawing upon the foundation of the Technology Acceptance Model 3 (TAM3), the research plan integrates perceived ease of use to act as a mediating variable, helping dissect the intricate connections between outside influences and a user's intention to behave in a certain way. The study employ a quantitative research framework, utilizing a structured questionnaire intended for distribution among customers of Hangzhou City Commercial Bank, with a target sample size of five hundred participants. Key steps in the methodology encompass a thorough literature review, the process of developing the survey instruments, gathering the necessary data, and conducting statistical analysis, primarily through structural equation modeling. Ultimately, this research endeavor intends to uncover the underlying motivators impacting user uptake, thereby offering valuable, actionable insights for the bank to refine and improve its mobile banking service offerings. The anticipated results stand to contribute meaningfully to both advancements in the theory behind technology acceptance models and practical recommendations for the financial sector aiming to boost user involvement and overall satisfaction. This document presents the foundational reasons, theoretical background, planned methods, and expected contributions of the upcoming study, welcoming further discussion and critique to refine and solidify the design of this research initiative.