Barriers in adoption of internet banking: A structural equation modeling - Neural network approach

Comparatively, less attention has been paid to the factors that obstruct consumers to use internet banking. Therefore, this study aims to analyze the barriers in the adoption of Internet banking in Karachi, Pakistan. A survey research questionnaire was adopted and, in total, 300 useable responses were used from the banks’ customers. First exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied for the establishment of measurement model and structural equation modeling (SEM) was used to find the significant influence barriers on Internet banking adoption. In the second phase, the neural network model was used to rank the relative influence of significant predictors obtained from SEM. The results indicate a significant positive relationship between value barrier, risk barrier, and image barrier with the usage of Internet banking. Only, the traditional barrier has a negative insignificant effect on the usage of Internet banking. The image barrier has a higher impact on usage of Internet banking followed by the value barrier and risk barrier. Results also indicate that males are facing high barriers in comparison with females. Findings provide guidelines to banks for developing facilities that enable the consumer to use Internet banking for their financial transactions. This study will be highly beneficial for the banking industry to improve their online services and revise their policies to facilitate consumers by meeting their needs.     

Fuzzy Decision Model: Evaluating and Selecting Open Banking Business Partners

The finance supply chain has always been a different supply chain compared to product supply chain being a service supply chain. Open Banking (OB) is one of the most important milestones since the beginning of financial technology innovation and service supply chain. As these are activities provided by traditional banks, non-bank financial institutions also provide financial service with access to consumer banking, transactional and other financial data to develop financial applications and services tailored to their customers. The development of financial technology, “Open banking”, promotes financial services to begin this transformation. However, evaluating and selecting open banking business partners from multiple perspectives for banks are underexplored. Thus, the authors in this research proposed a hybrid multi-criteria decision-making model which includes a Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) model and a Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) model with supports from seasoned domain experts. The contribution of this research is a proposition of a fuzzy decision model for evaluating and selecting open banking business partners. The model successfully determined a suitable open bank provider in order to assist decision makers decide objectively.     

存货质押委托监管模式下基于双边道德风险的收益分配模型研究

存货质押融资作为一项多主体的融资业务,道德风险是其不可忽视的一种重要风险。在存货质押委托监管模式的初始授信环节,银行与物流企业的努力程度为隐匿信息,因此银行与物流企业双方都有可能存在道德风险问题,收益分配作为一种激励机制,可以对双方道德风险起到一定约束作用。本文在存货质押融资委托监管模式下,基于委托代理理论,研究了考虑初始授信环节中银行与物流企业存在双边道德风险时的收益分配问题,建立了银行与物流企业的收益分配模型,推导出银行与物流企业间的最优收益分配比例,以防范银行与物流企业的双边道德风险。最后通过数值算例进一步对收益分配比例随物流企业实力变动的趋势进行了分析。     

商业银行绩效评价体系及影响因素研究

为寻找商业银行绩效影响因素及构建合理的商业银行绩效评价体系,从财务特征和治理特征选择影响商业银行绩效的因素,以1998~2008年各上市商业银行混合面板数据为样本,建立多元回归模型进行实证检验,利用序数分析法构建商业银行绩效评价体系。研究结果表明股份制商业银行绩效排名较高,国有商业银行居中,而城市商业银行绩效较低。     

Factors affecting the behavioral intention to adopt mobile banking: An international comparison

Over the past decade, the markets for mobile and wireless services have been among the world's fastest-growing, especially in Asian countries, presenting financial institutions with significant opportunities to offer value-added services. Mobile banking has since emerged as a new channel enabling the banks to react strategically to changes in competitive forces and to enhance customer convenience.Based on Diffusion of Innovations (DOI) theory, the Technology Acceptance Model (TAM), the Decomposed Theory of Planned Behavior (DTPB) model, this study develops an integrated model to provide a fuller understanding of factors facilitating or impeding the adoption of mobile banking, focusing on consumers in Taiwan and Vietnam. While subjective norms had a significant effect on the intention to adopt, three attributes of mobile banking (compatibility, perceived usefulness, and perceived risk) were found to have indirect effects on intention to adopt mobile banking through attitude toward adoption for consumers in both Taiwan and Vietnam. Intention to adopt mobile banking was indirectly influenced by self-efficacy and facilitating conditions, and directly affected by perceived behavioral control in both nations. Some differences in intention to adopt mobile banking between Taiwanese and Vietnamese are also discussed. Based on the research findings, managerial implications for financial institutions and mobile service providers are discussed.     

高违约率下融资租赁信用风险的多属性评价

提出了一种高违约率下融资租赁信用风险的评价方法,基于专家群体对评价指标赋值类型的不同引入多属性决策的指标权重确定方法。以我国工程机械行业融资租赁信用风险评价为例,分析了我国工程机械行业融资租赁信用风险的特征,构建了以定量的财务指标与定性的非财务指标相结合的信用风险评价指标体系,进而运用上述方法确定了各级指标的权重,阐述了该评价方法的合理性。     

A study on credit scoring modeling with different feature selection and machine learning approaches

A bit hurdle for financial institutions is to decide potential candidates to give a line of credit identifying the right people without any credit risk. For such a crucial decision, past demographic and financial data of debtors is important to build an automated artificial intelligence credit score prediction model based on machine learning classifier. In addition, for building robust and accurate machine learning models, important input predictors (debtor's information) must be selected. The present computational work focuses on building a credit scoring prediction model. A publicly available German credit data is incorporated in this study. An improvement in the credit scoring prediction has been shown with the use of different feature selection techniques (such as Information-gain, Gain-Ratio and Chi-Square) and machine learning classifiers (Bayesian, Naïve Bayes, Random Forest, Decision Tree (C5.0) and SVM (support Vector Machine)). Further, a comparative analysis is performed between different machine learning classifiers and between different feature selection techniques. Different evaluation metrics are considered for analyzing performance of the models (such as accuracy, F-measure, false positive rate, false negative rate and training time). After analysis, a best combination of machine learning classifier and feature selection technique are identified. In this study, a combination of random forest (RF) and Chi-Square (CS) is found good, among other combinations, with respect to good performance accuracy, F-measure and low false positive and false negative rates. However, training time for this particular combination was found to be slightly higher. Result of C5.0 with chi-square was comparable with the best one. This study provides an opportunity to financial institutions to build an automated model for better credit scoring.     

Customer satisfaction with bank services: The role of cloud services,security, e-learning and service quality

The banking industry is rapidly developing to utilize e-banking as an efficient and suitable tool to satisfy customers. Online banking service is the general service suggested by customary banks to provide faster and more reliable services for customers. With fast technology improvement, e-banking has been utilized to absorb subscribers and conduct banking transactions. Still, the major problem with e-banking is satisfying customers who are now using Internet banking. Customer satisfaction is a significant factor in helping banks to keep their competitive advantage. Therefore, the present investigation aims to examine the factors influencing the satisfaction of customer with e-banking services. Four factors that can drive customer satisfaction towards e-banking are cloud services, security, e-learning, and service quality. This study has utilized the structural equation modeling method to evaluate the causal model with the measurement model's validity and reliability. The research model is analyzed based on the data which are collected from the questionnaires using SMART PLS 3.2. The results have shown that cloud services, security, e-learning, and service quality are four significant factors influencing customer satisfaction in using Internet banking services.     

Banks and Industrial Finance in the 1990s

This paper examines the role of the banking system in the German model of industrial development. It argues that banks continue to fulfil several of their traditional functions in industrial finance despite dramatic changes in financial regulation and the internationalisation of product and capital markets. The strength of the financial system in fulfilling these traditional functions, however, is at the same time a barrier to the creation of new high-tech industries — a major competitive challenge for Germany.     

Lending decisions under uncertainty: a DEA approach

Credit markets have experienced phenomenal growth in the last years, and there is no evidence to expect that this trend will invert in the next decade. Given that, virtually every segment of the industry is called to improve its skills in credit risk management with the threefold aim of managing concentration risk, meeting regulatory requirements and enhancing revenues. Clearly, for financial institutions, exposure to credit risk continues to be the leading source of problems and the challenging issue of managing credit risk is considered a crucial topic. This paper demonstrates the use of a stochastic DEA model for credit scoring which is one of the prevailing analytical technique to evaluate credit risk. Although the principles contained in this paper are most clearly applicable to the business of lending, they can be applied to all activities where credit risk is present.     

Technological innovation and the U.S. banking industry: Innovation in the U.S. retail and wholesale banking sectors

In this paper, case studies of “best practice” retail and wholesale banks are used to explore the influence of technological change on the banking industry. The impact that specific technologies are having on the retail and whole-sale sectors is discussed. Briefly, the evidence shows that there is tremendous pressure on the banking industry to restructure at the current level of technology and competition. Retail banks are looking to client-server, open systems, groupware, workflow software, and imaging technology to restructure and consolidate their operations. Wholesale banks are using information technology to support specialized fee-income generating strategies. Nonetheless, in both the retail and wholesale banking sectors, nonbank financial service providers such as pension funds, insurance companies, money market funds and mutual funds are gaining market share. As these competitors expand their role, I find that the financial services competitor with the best strategy and technology is increasingly no longer a traditional bank.     

AN EMPIRICAL STUDY ON ANALYZING THE PRODUCTIVITY OF BANK BRANCHES

Productivity analysis and its strategic implications are not only important for manufacturing sector but equally essential for other sectors as well. Branch banking sector is no exception in this sense and banks have to operate more efficiently and effectively in an increasingly competitive environment to sustain or improve their relative positions. This paper discusses the methodology of an empirical study that was employed in analyzing the operating productivities of a set of 44 bank branches of a major commercial bank offering relatively homogeneous products in a multi-market business environment. The methodology was based on the concepts and principles of Data Envelopment Analysis (DEA). The results of the study have indicated that this kind of productivity analysis is not only complementary to traditionally used financial ratios but also is a useful bank management tool in reallocating resources between the branches in order to achieve higher efficiencies.     

MSEs Credit Risk Assessment Model Based on Federated Learning and Feature Selection

Federated learning has been used extensively in business innovation scenarios in various industries. This research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment scenario. First, this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises (MSEs) using multi-dimensional enterprise data and multi-perspective enterprise information. The proposed model includes four main processes: namely encrypted entity alignment, hybrid feature selection, secure multi-party computation, and global model updating. Secondly, a two-step feature selection algorithm based on wrapper and filter is designed to construct the optimal feature set in multi-source heterogeneous data, which can provide excellent accuracy and interpretability. In addition, a local update screening strategy is proposed to select trustworthy model parameters for aggregation each time to ensure the quality of the global model. The results of the study show that the model error rate is reduced by 6.22% and the recall rate is improved by 11.03% compared to the algorithms commonly used in credit risk research, significantly improving the ability to identify defaulters. Finally, the business operations of commercial banks are used to confirm the potential of the proposed model for real-world implementation.     

银行国际贸易结算系统构件化设计与实现

国际贸易结算是银行业中一种必不可少的业务，占据着重要的地位，而且随着电子商务的发展，其重要性也越来越突出。但是，这一业务的计算机化相当困难。主要原因是：操作流程复杂；组合变化太多，对灵活性有很高要求；涉及面相当广，几乎涉及银行的每一个业务品种，是一个压缩版的银行系统。因此，开发这样的系统必须采用先进的而且较为合适的方法和技术。文章提出了以构建半成品构件系统为总体思想的开发方法；在设计和实现上，提出了以数据总线为统一接口，以菜单/功能图标为总控主体框架，以基本业务操作为基本组件，并能把基本组件包装裁剪成可在     

Ambidexterity in Service Organizations: Reference Models from the Banking Industry

This paper reviews the literature on ambidexterity in service organizations with a specific focus on the banking industry. We identify three key, cross-unit bank processes: governance (bank headquarters), sales (branch processes) and operations (ICT and facilities to support local (branch) and inter-unit (headquarters-to-branch) tasks). We suggest a framework that incorporates three main “reference models”, from an organizational design perspective. Model 1 (exploitative model) applies when the bank's headquarters work to formalize branch sales processes supported by operations processes. Model 2 (exploratory model) applies when the bank's headquarters allows flexibility in branch sales processes and uses operations processes to decentralize tasks. Model 3 (ambidextrous model) applies when a branch incorporates the characteristics of Models 1 and 2 simultaneously. We ground our claims using fieldwork conducted in 2004–2005 that involved a number of major Italian banks. We show that while large organizations, such as banks, base their ambidextrous innovation on organizational design, contextual elements such as trust and commitment, and management styles and leadership play a role in dealing with efficiency-oriented vs. flexibility-oriented tasks within the same bank branch.     

Systemic risk: the dynamics of model banking systems

The recent banking crises have made it clear that increasingly complex strategies for managing risk in individual banks have not been matched by corresponding attention to overall systemic risks. We explore some simple mathematical caricatures for ‘banking ecosystems’, with emphasis on the interplay between the characteristics of individual banks (capital reserves in relation to total assets, etc.) and the overall dynamical behaviour of the system. The results are discussed in relation to potential regulations aimed at reducing systemic risk.     

Sustainability and branchless banking: The development and validation of a distinct measurement scale

This study aimed to develop and validate a new scale for measuring the sustainability and development of branchless banking. The study followed the scale development procedure based on Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) using SPSS 22 and Structural Equation Modelling (SEM) analyses through SmartPLS. The data was collected from 150 respondents from different stakeholders of branchless banking. The EFA reported with the seven-factor solution including social sustainability, product responsibility, economic sustainability, labor practices and decent work, environmental sustainability, human rights and ethics, and branchless banking development. The structural model further validated the positive impact of human rights and ethics, labor practice and decent work, product responsibility, and social sustainability on the development of branchless banking. The study has a novelty to develop and validate the first-ever scale for measuring sustainable branchless banking. Besides, the study also provides many theoretical and practical implications for different stakeholders including academia, researchers, top management of the banks, and practitioners.     

Capital Structure of Foreign Direct Investments: A Transaction Cost Analysis

Transaction cost theory (TCT) plays a major role in theorizing about the boundaries of the multinational enterprise (MNE), and is increasingly being applied to intra-MNE governance. We apply TCT to capital structure decisions for MNE subsidiaries. According to TCT, equity and debt are not just financial instruments, but alternative governance structures. Equity is useful for projects involving specific assets that do not serve well as collateral, and for knowledge intensive activities where information asymmetry and public good issues make external financing more costly. We study under what conditions MNE headquarters may wish to partially re-introduce market mechanisms inside the MNE through the use of external or internal debt to finance subsidiaries. This can allow economizing on governance costs and strengthen subsidiary manager incentives, but may be inappropriate if subsidiary assets are MNE-specific or subsidiary-specific. Empirically testable propositions are developed.     

RankXGB-Based Enterprise Credit Scoring by Electricity Consumption in Edge Computing Environment

With the rapid development of the internet of things (IoT), electricity consumption data can be captured and recorded in the IoT cloud center. This provides a credible data source for enterprise credit scoring, which is one of the most vital elements during the financial decision-making process. Accordingly, this paper proposes to use deep learning to train an enterprise credit scoring model by inputting the electricity consumption data. Instead of predicting the credit rating, our method can generate an absolute credit score by a novel deep ranking model–ranking extreme gradient boosting net (rankXGB). To boost the performance, the rankXGB model combines several weak ranking models into a strong model. Due to the high computational cost and the vast amounts of data, we design an edge computing framework to reduce the latency of enterprise credit evaluation. Specially, we design a two-stage deep learning task architecture, including a cloud-based weak credit ranking and an edge-based credit score calculation. In the first stage, we send the electricity consumption data of the evaluated enterprise to the computing cloud server, where multiple weak-ranking networks are executed in parallel to produce multiple weak-ranking results. In the second stage, the edge device fuses multiple ranking results generated in the cloud server to produce a more reliable ranking result, which is used to calculate an absolute credit score by score normalization. The experiments demonstrate that our method can achieve accurate enterprise credit evaluation quickly.     

基于专题数据库的统一社会信用代码创新应用研究

本文以应用创新为驱动,在全面分析了统一社会信用代码应用现状及问题的基础上,对统一社会信用代码应用方式进行了重构和再设计,即以应用为导向,以实践验证为路径,研究建立了以统一社会信用代码专题数据库为核心的数据组织方式、以开放共享的系统架构为核心的数据服务模式、以应用数据标准化为核心服务"互联网+监管"的统一社会信用代码解决方案,形成了深化和拓展统一社会信用代码应用的创新方法,为统一社会信用代码在服务"互联网+监管"、推进社会信用体系建设和国家治理体系和治理能力现代化建设中发挥作用提供了方法和路径的建议。