Hasil untuk "Banking"

A. Haldane, R. May

Arnoud Boot, A. Thakor

A. Alalwan, Yogesh Kumar Dwivedi, Nripendra P. Rana et al.

Purpose – The purpose of this paper is to propose and examine a conceptual model that best explains the key factors influencing Jordanian customers ' intention to adopt mobile banking (MB). Design/methodology/approach – The proposed conceptual model was based on the Technology Acceptance Model (TAM). This was extended by adding perceived risk and self-efficacy as an external factors. Structural equation modelling (SEM) was conducted to analyse the data collected from the field survey questionnaires administered to a convenience sample of Jordanian banking customers. Findings – The results showed that behavioural intention is significantly influenced by perceived usefulness, perceived ease of use, and perceived risk. Research limitations/implications – Practical and theoretical implications for both Jordanian banks and researchers in the MB context are also discussed in the concluding section. Originality/value – MB-related issues are yet to be examined empirically in the Jordanian context. This submission has attempted to fill this gap by empirically examining some of the important factors influencing the adoption of MB from the Jordanian customers’ perspective.

M. Amin

Shkelqim Sherifi

New technologies, such as blockchain, are designed to address various system weaknesses, particularly those related to security. Blockchain can enhance numerous aspects of traditional banking systems by transforming them into digital, immutable, secure, and anonymous ledger. This paper proposes a new banking application ALBank, which is based on blockchain and smart contract technologies. Its functionality relies on invoking functions within smart contracts deployed on the Ethereum blockchain. This approach enables decentralization and enhances both security and trust. In this context, the paper first presents a critical analysis of existing research on blockchain and traditional banking systems, with a focus on their respective challenges. It then examines the Know Your Customer (KYC) process and its various models. Finally, it introduces the design and development of ALBank, a decentralized banking application built on the Ethereum blockchain using smart contracts. The results show that the integration of blockchain and smart contracts effectively addresses key issues in traditional banking systems, including centralization, inefficiency, and security vulnerabilities by storing critical data on a decentralized, immutable ledger, managing processes autonomously, and making transactions transparent to all users.

Subhrojyoti Mukherjee, Manoranjan Mohanty

Fake images in selfie banking are increasingly becoming a threat. Previously, it was just Photoshop, but now deep learning technologies enable us to create highly realistic fake identities, which fraudsters exploit to bypass biometric systems such as facial recognition in online banking. This paper explores the use of an already established forensic recognition system, previously used for picture camera localization, in deepfake detection.

João B. G. de Brito, Rodrigo Heldt, Cleo S. Silveira et al.

The emergence of Open Banking represents a significant shift in financial data management, influencing financial institutions' market dynamics and marketing strategies. This increased competition creates opportunities and challenges, as institutions manage data inflow to improve products and services while mitigating data outflow that could aid competitors. This study introduces a framework to predict customers' propensity to share data via Open Banking and interprets this behavior through Explanatory Model Analysis (EMA). Using data from a large Brazilian financial institution with approximately 3.2 million customers, a hybrid data balancing strategy incorporating ADASYN and NEARMISS techniques was employed to address the infrequency of data sharing and enhance the training of XGBoost models. These models accurately predicted customer data sharing, achieving 91.39% accuracy for inflow and 91.53% for outflow. The EMA phase combined the Shapley Additive Explanations (SHAP) method with the Classification and Regression Tree (CART) technique, revealing the most influential features on customer decisions. Key features included the number of transactions and purchases in mobile channels, interactions within these channels, and credit-related features, particularly credit card usage across the national banking system. These results highlight the critical role of mobile engagement and credit in driving customer data-sharing behaviors, providing financial institutions with strategic insights to enhance competitiveness and innovation in the Open Banking environment.

Haibo Wang, Takeshi Tsuyuguchi

Major bank mergers and acquisitions (M&A) transform the financial market structure, but their valuation and spillover effects remain open to question. This study examines the market reaction to two M&A events: the 2005 creation of Mitsubishi UFJ Financial Group following the Financial Big Bang in Japan, and the 2018 merger involving Resona Holdings after the global financial crisis. The multi-method analysis in this research combines several distinct methods to explore these M&A events. An event study using the market model, the capital asset pricing model (CAPM), and the Fama-French three-factor model is implemented to estimate cumulative abnormal returns (CAR) for valuation purposes. Vector autoregression (VAR) models are used to test for Granger causality and map dynamic effects using impulse response functions (IRFs) to investigate spillovers. Propensity score matching (PSM) helps provide a causal estimate of the average treatment effect on the treated (ATT). The analysis detected a significant positive market reaction to the mergers. The findings also suggest the presence of prolonged positive spillovers to other banks, which may indicate a synergistic effect among Japanese banks. Combining these methods provides a unique perspective on M&A events in the Japanese banking sector, offering valuable insights for investors, managers, and regulators concerned with market efficiency and systemic stability

A. Botta, E. Caverzasi, D. Tori

We propose a simple short-run Post-Keynesian model in which the key aspects of shadow banking, namely securitization and the production of structured finance instruments, are explicitly formalized. To the best of our knowledge, this is the first attempt to broaden purely real-side Post-Keynesian models and their traditional focus on shareholder-value orientation, the financialization of non-financial firms, and the profit-led vs. wage-led dichotomy. We rather put emphasis on the role of financial institutions and rentier-friendly environment in determining the predominance of specific growth and distribution regimes. First, we illustrate the macroeconomic rationale of shadow banking practices. We show how, before the 2007–08 crisis, securitization and shadow banking allowed for an increase in profitability for the whole financial sector, while apparently keeping leverage under control. Second, we define a variety of shadow-banking-led regimes in terms of economic activity, productive capital accumulation, and income distribution.

M. Shareef, A. Baabdullah, S. Dutta et al.

Abstract Many seminal studies have explored consumers’ attitude and perception to adopt mobile banking as a general and unique service channel. However, no empirical studies have so far addressed consumers’ intentions to select mobile banking service delivery channel from behavioral, technological, social, cultural, and organizational perspectives for the three distinct stages like static, interaction, and transaction service. This quantitative study investigates consumers’ behavioral intentions to adopt mobile banking at the three distinct service stages. It is designed to examine this behavioral pattern based on the theoretical concept of GAM model. In this regard, an extensive empirical study was conducted among mobile banking service receivers in Bangladesh. The results reveal that driving factors of consumers’ behavioral intentions to adopt mobile banking at the static, interaction, and transaction service phases are significantly different, providing important theoretical and practical contributions.

Manon Arcand, Sandrine PromTep, Isabelle Brun et al.

M. Jakšič, Matej Marinč

Hossein Hassani, Xu Huang, E. Silva

Blockchain is disrupting the banking industry and contributing to the increased big data in banking. However, there exists a gap in research and development into blockchain-ed big data in banking f...

X. Vives

Jamil Hammoud, Rima M. Bizri, Ibrahim El Baba

The purpose of this study was to examine the relationship between the dimensions of E-Banking service quality and customer satisfaction to determine which dimension can potentially have the strongest influence on customer satisfaction. Data were gathered using a survey instrument, which was distributed among bank clients in the Lebanese banking sector. The data were statistically analyzed using structural equation modeling with SPSS and Amos (20). The findings show that reliability, efficiency, and ease of use; responsiveness and communication; and security and privacy all have a significant impact on customer satisfaction, with reliability being the dimension with the strongest impact. E-Banking has become one of the essential banking services that can, if properly implemented, increase customer satisfaction, and give banks a competitive advantage. Knowing the relative importance of service quality dimensions can help the banking industry focus on what satisfies customers the most.

Jerchern Lin

The purpose of the article. Managed portfolios are subject to tail risks, which can be either index level (systematic) or fund-specific. Examples of fund-specific extreme events include those due to big bets or fraud. This paper studies the two components in relation to compensation structure in managed portfolios. Methodology. A novel methodology is developed to decompose return skewness and kurtosis into various systematic and idiosyncratic components and applied it to the returns of different fund types to assess the significance of these sources. In addition, a simple model generates fund-specific tail risk and its asymmetric dependence on the market, and makes predictions for where such risks should be concentrated. The model predicts that systematic tail risks increase with an increased weight on systematic returns in compensation and idiosyncratic tail risks increase with the degree of convexity in contracts. Results of the research. The model predictions are supported with empirical results. Hedge funds are subject to higher idiosyncratic tail risks and Exchange Traded Funds exhibit higher systematic tail risks. In skewness and kurtosis decompositions, the results indicate that coskewness is an important source for fund skewness, but fund kurtosis is driven by cokurtosis, as well as volatility comovement and residual kurtosis, with the importance of these components varying across fund types. Investors are subject to different sources of skewness and fat tail risks through delegated investments. Volatility based tail risk hedging is not effective for all fund styles and types.

Muhamad Bhayuta Yudhi Putera, Melia Famiola

This study in the banking industry examines the influence of attitudinal loyalty on customer advocacy and cross buying behavior, alongside the moderating roles of Quality of Life and Corporate Social Responsibility support in the CSR fit and loyalty relationship. Employing Structural Equation Modeling, it reveals that higher attitudinal loyalty significantly boosts customer advocacy and propensity for cross buying. The findings highlight the importance of nurturing customer loyalty through valuable and relevant offerings, as CSR fit alone does not define the loyalty of the banking customer. Banks are advised to target customers with a high Quality of Life and engage with those who support CSR initiatives aligning with the banks objectives, to enhance loyalty and deepen customer relationships.

Ana Kovacevic, Sonja D. Radenkovic, Dragana Nikolic

The rapid advancements in artificial intelligence (AI) have presented new opportunities for enhancing efficiency and economic competitiveness across various industries, espcially in banking. Machine learning (ML), as a subset of artificial intelligence, enables systems to adapt and learn from vast datasets, revolutionizing decision-making processes, fraud detection, and customer service automation. However, these innovations also introduce new challenges, particularly in the realm of cybersecurity. Adversarial attacks, such as data poisoning and evasion attacks, represent critical threats to machine learning models, exploiting vulnerabilities to manipulate outcomes or compromise sensitive information. Furthermore, this study highlights the dual-use nature of AI tools, which can be used by malicious users. To address these challenges, the paper emphasizes the importance of developing machine learning models with key characteristics such as security, trust, resilience and robustness. These features are essential to mitigating risks and ensuring the secure deployment of AI technologies in banking sectors, where the protection of financial data is paramount. The findings underscore the urgent need for enhanced cybersecurity frameworks and continuous improvements in defensive mechanisms. By exploring both opportunities and risks, this paper aims to guide the responsible integration of AI in the banking sector, paving the way for innovation while safeguarding against emerging threats.

T. Zhang, Can Lu, M. Kizildag

Purpose This paper aims to examine consumers’ adoption of mobile technology to facilitate their banking services and activities, and to investigate the factors influencing their adoption and engagement. Design/methodology/approach An online survey is used to test proposed relationships between factors and consumers’ mobile banking adoption. Structural equation modeling is performed to analyze consumers’ intentions toward mobile banking. Findings Traditional technology acceptance model factors – perceived usefulness and perceived ease of use – are identified as effective factors in influencing consumers to adopt mobile technology for facilitating banking services. Moreover, technology safety concerns, including reliability and privacy factors, are found to play an important role in motivating consumers to embrace mobile banking. The “fun” feature of the technology and consumers’ innovativeness characteristics are considered important in influencing mobile banking adoption. Trust in the banks has its predominant role in mobile technology adoption for banking services. Practical implications A bank gaining trust from its clients is key to active adoption of mobile banking technology. Bankers are advised to pay more attention to reliability and privacy features when designing and promoting mobile banking technology to consumers. Moreover, advertisements to bank clients should stress the “fun” aspects of the mobile banking apps to attract them to the use of mobile banking technology. Originality/value This paper investigates the factors influencing bank consumers to adopting mobile banking apps to facilitate their banking services. Nine key factors in the technology adoption area are examined to provide a comprehensive understanding of bank clients’ use of mobile banking apps, which advances the understanding of mobile technology applied in the banking industry in the literature.

Samar Rahi, M. Ghani, A. Ngah

Abstract The banking sector has evolved in information technology for their internal and external business operations. In effect, user acceptance of internet banking is considered as one of the most fundamental issue in banking sector. In order to identify which factors affect user intention to adopt internet banking, this study develops an amalgamated model based on technology and social psychological literature. The research model was empirically tested using 398 responses from customers of commercial banks. Data was analyzed using structural equation modeling (SEM). The results of this study provided theoretical and empirical support for newly developed integrated model. Importance performance matrix analysis (IPMA) revealed that assurance is the most influential factor among all others to determine user's intention to adopt internet banking. These findings provide valuable insight to marketers and managers to understand customer behavior towards adoption of technology, especially in emerging e-payment domain. To the best of our knowledge, this is the first study that investigates internet banking adoption issues with integrated technology model (UTAUT & E-SQ) in South Asia. Finally the study calls for researchers to use current integrated model in other e-commerce domains such as online shopping websites to establish the external validity of the model.