Revisiting the role of web assurance seals in business-to-consumer electronic commerce

There is conflicting evidence as to the current level of awareness and impact of Web Assurance Seal Services (WASSs). This study examines the effects of an educational intervention designed to increase consumer's knowledge, of security and privacy aspect of business-to-consumer (B2C) e-commerce websites and assurance seal services. The study further explores the relationships among consumers' perceptions about online security, including WASSs awareness, importance of WASS, privacy concerns, security concerns, and information quality, before and after the educational intervention. The study finds that educating consumers about the security and privacy dangers of the web, as well as the role of web assurance seals, does increase their awareness and perceived importance of the seals. However, despite this increased awareness, there is little association between these assurance seals and the two indicators of trustworthiness, concerns about privacy and perceived information quality, of an e-commerce site, even after the intervention. Only security concerns have a statistically significant relationship with WASSs awareness before and after the educational intervention. Implications for theory and practice are discussed.     

Optimization strategy of credit line management for credit card business

Adjusting the credit lines of card users is an important issue. It is essential to establish an optimized approach for credit card companies to identify the proper amount of credit to offer for their customers. Most of the related research concentrated on the prediction of credit card users׳ default. Our contribution is a consideration of a holistic and heuristic approach that looks at the credit line that maximizes the net profits of the credit card companies. We first apply regression models to find the probability of default of customer and customer׳s current balance as a function of credit line. Next we use a regression tree to identify groups of customers assigned with the same credit line. The results are then used to formulate the net profit and genetic algorithm is used to find optimally adjusted credit line for each group of customers. It is expected that our study can contribute to present strategic guidelines for the management of credit lines for card companies.     

Examining the impact of intangible product features and e-commerce institutional mechanics on consumer trust and repurchase intention

The present study examines virtual try-on technology (VTO), return policies, pay-on-delivery (POD) mode of payment, vendor-specific guarantees, and free shipping policy of online retailers as antecedents of trust. The study also examines the role of perceived effectiveness of e-commerce institutional mechanisms (PEEIM) as a moderator between repurchase intention and trust. Data were collected through an online survey. The link to the questionnaire for the online survey was shared on different social media platforms and social networking sites. A total of 614 responses were considered for the study. Results revealed that return policies, POD mode of payment, free shipping policy, and VTO technology emerged significant predictors of trust. Surprisingly, vendor-specific guarantee had a negative relationship with trust. Trust, in turn, influenced repurchase intention. Considering the trust and survey responses, the results confirmed that PEEIM negatively moderates the relationship between trust and repurchase intention. This study contributes to the literature by empirically validating the impact of return policies, VTO technology, POD mode of payment, free shipping policies, and vendor-specific guarantees on trust. Most of these constructs have been analyzed as solitary constructs. In this study, the impact of these constructs is measured collectively, thereby indicating their importance as compared with other policies implemented by an online retailer. This is a first-of-its-kind study that validates the policies of online retailers in the Indian context.

     

基于数据挖掘技术的信用卡审批模型研究

针对分类预测建模数据的非对称性,提出一种基于神经网络和决策树技术结合的非对称性数据集合预测分类建模方法,建立了信用卡审批模型.结果表明:增加预测类标识决策属性后,在用不同比例的建模数据集建立的所有模型中,比例为33.33%:66.67%的数据集建立的神经网络模型最好,模型的准确率达到88.49%.     

A cost-sensitive decision tree approach for fraud detection

With the developments in the information technology, fraud is spreading all over the world, resulting in huge financial losses. Though fraud prevention mechanisms such as CHIP&PIN are developed for credit card systems, these mechanisms do not prevent the most common fraud types such as fraudulent credit card usages over virtual POS (Point Of Sale) terminals or mail orders so called online credit card fraud. As a result, fraud detection becomes the essential tool and probably the best way to stop such fraud types. In this study, a new cost-sensitive decision tree approach which minimizes the sum of misclassification costs while selecting the splitting attribute at each non-terminal node is developed and the performance of this approach is compared with the well-known traditional classification models on a real world credit card data set. In this approach, misclassification costs are taken as varying. The results show that this cost-sensitive decision tree algorithm outperforms the existing well-known methods on the given problem set with respect to the well-known performance metrics such as accuracy and true positive rate, but also a newly defined cost-sensitive metric specific to credit card fraud detection domain. Accordingly, financial losses due to fraudulent transactions can be decreased more by the implementation of this approach in fraud detection systems.     

Securing credit card transactions with one-time payment scheme

Traditional credit card payment is not secure against credit card frauds because an attacker can easily know a semi-secret credit card number that is repetitively used. Recently one-time transaction number has been proposed by some researchers and credit card companies to enhance the security in credit card payment. Following this idea, we present a practical security enhancement scheme for one-time credit card payment. In our scheme, a hash function is used in generation of one-time credit card numbers with a secret only known to the card holder and issuer. Compared with related work, our scheme places less burden on credit card issuers, and can be easily deployed in on-line or off-line payment scenarios. Analysis and simulation show that the time and space complexity is affordable to the card issuer with desired security features.     

Why do we trust new technology? A study of initial trust formation with organizational information systems

Recent trust research in the information systems (IS) field has described trust as a primary predictor of technology usage and a fundamental construct for understanding user perceptions of technology. Initial trust formation is particularly relevant in an IS context, as users must overcome perceptions of risk and uncertainty before using a novel technology. With initial trust in a more complex, organizational information system, there are a number of external determinants, trusting bases, that may explain trust formation and provide organizations with the needed levers to form or change individuals’ initial trust in technology. In this study, a research model of initial trust formation is developed and includes trusting bases, trusting beliefs, trusting attitude and subjective norm, and trusting intentions. Eight trusting base factors are assessed including personality, cognitive, calculative, and both technology and organizational factors of the institutional base. The model is empirically tested with 443 subjects in the context of initial trust in a national identity system (NID). The proposed model was supported and the results indicate that subjective norm and the cognitive–reputation, calculative, and organizational situational normality base factors significantly influence initial trusting beliefs and other downstream trust constructs. Factors from some of the more commonly investigated bases, personality and technology institutional, did not significantly affect trusting beliefs. The findings have strategic implications for agencies implementing e-government systems and organizational information systems in general.     

The Legal Significance of Trustmarks

To help them attain the ultimate goal of selling their goods and services, Netstores adorn their websites with graphics, information and unimaginable details of all sorts as well as peppering them with both conspicuous and hidden 'metatags' to attract more visits ('hits') than others, pay higher fees for search engine providers ('portals') to place themselves at the head of the list of favoured sites. The use of special tags, 'trustmarks' or logos that indicate some level of believability and reputation, is on the rise to add to the success in that scramble. While it has taken many international companies a succession of decades to establish trust and confidence in the line of business or type of wares and services they have offered to their customers, the current wave of start ups feel hard pressed to succeed fast in the 'Wild Web' or else perish with the same speed that they sprout. There is a growing general expectation that a declaration of good business practices and specific standards ('codes') of conduct, including the execution of measures against the recalcitrant, to guide the concerned industry (on the Internet) could instil such trust in Netconsumers. Study after study has showed that consumers worry about the privacy and security of e-commerce and desist from transacting for fear that their details (including credit card numbers) might be intercepted by hackers, that they would be duped into transacting with parties which do not exist, or supply what they promise but do so defectively leaving the buyers without any adequate or clear avenue for legal redress. This article seeks to examine the legal status of trustmarks, or seals of approval, and the rights and liabilities they engender. Section 1 sets the stage by detailing briefly the kind of practises that compromise the security of computer networks and the Internet. Section 2 explores the rationale for the creation of trustmarks. Section 3 surveys and compares the main types and state of development of trustmarks across the world. Section 4 appraises the issues of potential liability that might follow from their use or abuse. Section 5 considers the proprietary aspect of trustmarks and the protection that may be available to them. The conclusion highlights the need to find solutions to the increasing confusion and overlaps that have emerged with the proliferation of trustmarks both within single states and across them.     

How website socialness leads to website use

Website designers are beginning to incorporate social cues, such as helpfulness and familiarity, into e-commerce sites to facilitate the exchange relationship. Website socialness elicits a social response from users of the site and this response produces enjoyment. Users patronize websites that are exciting, entertaining and stimulating. The purpose of our study is to explore the effects of website socialness perceptions on the formation of users’ beliefs, attitudes and subsequent behavioral intentions. We manipulate website socialness perceptions across two different online shopping contexts, one for functional products and the other for pleasure-oriented products, and draw from the responses of 300 Internet users. Our findings show that website socialness perceptions lead to enjoyment, have a strong influence on user intentions and these effects are invariant across shopping contexts.     

The Real Cost of Fraud to E-tailers

With 27 billion credit card transactions conducted annually, credit card spending is at its highest rate ever. Estimates suggest that 2%, or 540 million, of these transactions are conducted over the Internet. Unfortunately, the boom in online spending comes hand in hand with an increase in E-commerce credit card fraud. The statistics say that E-commerce fraud is 10 to 20 times more likely than face-to-face, with some research claiming rates as high as 5-10%. The actual cost truly shows the shortcomings, with companies like Expedia incurring a $4 million fraud bill last year.     

Behavioral assessment of recoverable credit of retailer’s customers

The increasing rate of late payments by credit card customers, which are caused by the recent economic downturn, is causing not only reduced profit margins but also significant sales losses for retail companies. Under pressure to increase revenues, credit prediction should be a part of customer delinquency management. In this study, a credit prediction model has been developed to manage delinquents holding retail credit cards. The hybrid model combines a Kohonen network and a Cox’s proportional hazard model. A Kohonen network is used to cluster credit delinquents into homogeneous groups. A Cox’s hazard model is used to analyze repayment patterns of delinquents in each group. The model estimates the expected time of credit recovery from delinquents. This model’s prediction accuracy scored above 93%.     

A Novel Cardholder Behavior Model for Detecting Credit Card Fraud

Because credit card fraud costs the banking sector billions of dollars every year, decreasing the losses incurred from credit card fraud is an important driver for the sector and end-users. In this paper, we focus on analyzing cardholder spending behavior and propose a novel cardholder behavior model for detecting credit card fraud. The model is called the Cardholder Behavior Model (CBM). Two focus points are proposed and evaluated for CBMs. The first focus point is building the behavior model using single-card transactions versus multi-card transactions. As the second focus point, we introduce holiday seasons as spending periods that are different from the rest of the year. The CBM is fine-tuned by using a real credit card transaction data-set from a leading bank in Turkey, and the credit card fraud detection accuracy is evaluated with respect to the abovementioned two focus points.     

Employing transaction aggregation strategy to detect credit card fraud

Credit card fraud costs consumers and the financial industry billions of dollars annually. However, there is a dearth of published literature on credit card fraud detection. In this study we employed transaction aggregation strategy to detect credit card fraud. We aggregated transactions to capture consumer buying behavior prior to each transaction and used these aggregations for model estimation to identify fraudulent transactions. We use real-life data of credit card transactions from an international credit card operation for transaction aggregation and model estimation.     

Attitude contagion in consumer opinion platforms: posters and lurkers

The study details why and how product reviews from consumer opinion platforms affect individual users’ brand buying behavior. Drawing on social theories, the authors predict that consumers’ perceptions of other consumers’ product reviews affect brand buying intentions through two intervening variables: product- and brand-related attitudes. Moreover, the authors investigate whether these relationships are contingent on user type (i.e., active posters or passive lurkers). The empirical results support a multiple mediation framework in which product- and brand attitudes mediate the effects of consumer product reviews on individual brand buying intentions. In addition, consumer product reviews appear to more strongly affect the brand-related attitudes of posters than lurkers. Lurkers, who make up the majority of opinion platform users, are much less influenced by the opinions of others than posters. Encouraging variations in poster- and lurker rates may be an effective means for companies to manage and control consumer-to-consumer communication.     

Constructing credit auditing and control & management model with data mining technique

The 2008 financial tsunami, hitting the globe across all types of industries, causing tides of bankruptcies and severe unemployment, had its epicenter at American subprime in the housing market. In fact, the US subprime storm was just a premonition, while the root cause of the financial tsunami lied in the oversupply of structured credit products. Credit card business, one of the structured credit products, which under an intensively competitive environment, have been released by many banks with high spread, high return, and easy-to-apply appeals to carter to consumers needs. In order to allure the customers, some banks even go to the extent as simplify the credit rating, which in turn has increased credit risk, causing high non-performing ratio, increased debt collection cost, and growing bad debt counts. Accordingly, credit risk auditing plays a vital role in the successful management of credit card business. In response to such needs, the present study aims to conduct analysis and investigation on the current status of the industry with CRISP-DM model. First, customers’ demographic data and payment-related statistics were analyzed to identify feature variables, which were then sorted out as demographic data, debt data, payment rating etc. Next, by utilizing artificial neural network of data mining technique, the study tries to predict customer’s regular pattern of consumption, payment and/or default and bad debt, and to develop a set of credit granting principle by employing the decision tree technique. Since data mining classification model has a greater power in discriminating credit card granting, it can thus be used to construct accurate credit variable rules and predictive model, to further improve credit checking effect and credit risk control. Using the credit auditing data of a certain bank as a case study, the study intends to verify that the model constructed by the researcher can effectively identify the potential key factors of its credit card granting rule, to minimize the cost loss of Model I and Model II credit business, and eventually enhance the stability and profitability of the bank’s credit card business.     

基于半监督建模的金融欺诈行为侦测研究

近年来,网络黑产犯罪事件层出不穷,形成较完备网络黑色产业链。为维护网络信息安全,中央网信办、工信部、公安部、中国人民银行等部门持续开展治理工作,相关企业也不断加大整治力度。信用卡盗用盗刷是网络黑产常见形式之一。本次研究基于信用卡历史交易数据,借助半监督学习,构建反欺诈预测模型,对信用卡盗刷行为及时预警。     

Your Money or your Website?

While the Internet has brought with it a rising tide of crime, carried out using and exploiting the latest technology, all too often there is nothing new about the motives — the age-old ones of blackmail and extortion. The problems of Internet credit card fraud and email scams in which consumers have been defrauded often make news but much less publicised are incidences of blackmail that involve companies whose networks have been breached and their data stolen. The victims receive a demand from the hackers who threaten to expose the systems’ vulnerabilities and the information if they do not pay up.     

Supplemental cryptographic hardware for smart cards

A smart card is a small computer in credit card format with no man-machine interface. This industry wide recognition expresses an essential fact. The specific properties of smart cards, compared with all other types of cards, are determined by a microcontroller integrated in a card, which controls, initiates, and monitors all activities. Software alone cannot satisfy all smart card requirements. Manufacturers must offer additional functions in hardware. The authors describe true random-number generators and an advanced encryption standard computation unit: two different special-purpose hardware blocks that can be integrated on the silicon substrate along with the usual functional units of a smart card microcontroller     

DM技术在信用卡管理中的应用

信用卡公司是一个服务性的金融企业,如何提高在服务过程中的服务质量,改进服务方法,使公司的决策更为准确及时,是信用卡公司追求的一个目标。文章在介绍了信用卡公司对数据挖掘的用户需求之后,对该数据挖掘系统进行了分析。描述了该系统中对数据挖掘的应用方法。最后给出了该系统实施的过程。     

基于软交换的流媒体QoS支撑环境的研究

在以软交换为基础的下一代网络（NGN）中,流媒体的应用将成为其运营商的主要业务.通过重点阐述MPLS、RRA模型、差错控制等支持用户QoS的关键技术,从不同的技术角度,探讨了在IP网络、无线移动网络和终端中为流媒体业务提供各种QoS的机制与策略.