37 resultados para Credit Card


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Over the past twenty years brand loyalty has been an important topic for both marketing practitioners and academics. While practitioners have produced proprietary brand loyalty audit models, there has been little academic research to make transparent the methodology that underpins these audits and to enable practitioners to understand, develop and conduct their own audits. In this paper, we propose a framework for a brand loyalty audit that uses a tri-dimensional approach to brand loyalty, which includes behavioural loyalty and the two components of attitudinal loyalty: emotional and cognitive loyalty. In allowing for different levels and intensity of brand loyalty, this tri-dimensional approach is important from a managerial perspective. It means that loyalty strategies that arise from a brand audit can be made more effective by targeting the market segments that demonstrate the most appropriate combination of brand loyalty components. We propose a matrix with three dimensions (emotional, cognitive and behavioural loyalty) and two levels (high and low loyalty) to facilitate a brand loyalty audit. To demonstrate this matrix, we use the example of financial services, in particular a rewards-based credit card.

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Information fusion in biometrics has received considerable attention. The architecture proposed here is based on the sequential integration of multi-instance and multi-sample fusion schemes. This method is analytically shown to improve the performance and allow a controlled trade-off between false alarms and false rejects when the classifier decisions are statistically independent. Equations developed for detection error rates are experimentally evaluated by considering the proposed architecture for text dependent speaker verification using HMM based digit dependent speaker models. The tuning of parameters, n classifiers and m attempts/samples, is investigated and the resultant detection error trade-off performance is evaluated on individual digits. Results show that performance improvement can be achieved even for weaker classifiers (FRR-19.6%, FAR-16.7%). The architectures investigated apply to speaker verification from spoken digit strings such as credit card numbers in telephone or VOIP or internet based applications.

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Speaker verification is the process of verifying the identity of a person by analysing their speech. There are several important applications for automatic speaker verification (ASV) technology including suspect identification, tracking terrorists and detecting a person’s presence at a remote location in the surveillance domain, as well as person authentication for phone banking and credit card transactions in the private sector. Telephones and telephony networks provide a natural medium for these applications. The aim of this work is to improve the usefulness of ASV technology for practical applications in the presence of adverse conditions. In a telephony environment, background noise, handset mismatch, channel distortions, room acoustics and restrictions on the available testing and training data are common sources of errors for ASV systems. Two research themes were pursued to overcome these adverse conditions: Modelling mismatch and modelling uncertainty. To directly address the performance degradation incurred through mismatched conditions it was proposed to directly model this mismatch. Feature mapping was evaluated for combating handset mismatch and was extended through the use of a blind clustering algorithm to remove the need for accurate handset labels for the training data. Mismatch modelling was then generalised by explicitly modelling the session conditions as a constrained offset of the speaker model means. This session variability modelling approach enabled the modelling of arbitrary sources of mismatch, including handset type, and halved the error rates in many cases. Methods to model the uncertainty in speaker model estimates and verification scores were developed to address the difficulties of limited training and testing data. The Bayes factor was introduced to account for the uncertainty of the speaker model estimates in testing by applying Bayesian theory to the verification criterion, with improved performance in matched conditions. Modelling the uncertainty in the verification score itself met with significant success. Estimating a confidence interval for the "true" verification score enabled an order of magnitude reduction in the average quantity of speech required to make a confident verification decision based on a threshold. The confidence measures developed in this work may also have significant applications for forensic speaker verification tasks.

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We’ve had a bit of sticker shock in these parts. Well, apparently. Since my last missive, Brisbane’s Clem Jones Tunnel which was initially free now has a toll, at least partially, at the introductory rate of $2.95 for a one-way car ride between 5a.m. and midnight – free overnight. From 9 May 2010 the toll will be $4.28. Since the introductory toll was introduced, use of the tunnel appears to have declined somewhat – no surprise to transport professionals I suppose. An additional factor may have been that the “novelty value” of driving through the tunnel for free had worn off. This demonstrates to me that much of the community may still see the use of road infrastructure as a rite of passage, with only some actually weighing up the true value of their travel time and vehicle wear and tear against their out of pocket (or onto credit card) cost. Thus, we’re in pioneering times and the role of transport economics in the overall transport infrastructure planning realm is of considerable importance – especially as much of the new big ticket infrastructure is likely to be tolled into the future. The Queensland Premier, Anna Bligh, made poignant commentary about Brisbane City Council’s tunnel use in that such infrastructure is built for future times and not just as a quick fix for current traffic problems. My expectation is that once Airport Link, which is really the northern half of the corridor, opens in 2012, there will be a significant spike in Clem7 usage.

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Fusion techniques have received considerable attention for achieving lower error rates with biometrics. A fused classifier architecture based on sequential integration of multi-instance and multi-sample fusion schemes allows controlled trade-off between false alarms and false rejects. Expressions for each type of error for the fused system have previously been derived for the case of statistically independent classifier decisions. It is shown in this paper that the performance of this architecture can be improved by modelling the correlation between classifier decisions. Correlation modelling also enables better tuning of fusion model parameters, ‘N’, the number of classifiers and ‘M’, the number of attempts/samples, and facilitates the determination of error bounds for false rejects and false accepts for each specific user. Error trade-off performance of the architecture is evaluated using HMM based speaker verification on utterances of individual digits. Results show that performance is improved for the case of favourable correlated decisions. The architecture investigated here is directly applicable to speaker verification from spoken digit strings such as credit card numbers in telephone or voice over internet protocol based applications. It is also applicable to other biometric modalities such as finger prints and handwriting samples.

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Introduction Cybercrime consists of any criminal action or behaviour that is committed through the use of Information Technology. Common examples of such activities include cyber hacking, identity theft, cracking, spamming, social engineering, data tampering, online fraud, programming attacks, etc. The pervasive use of the internet clearly indicates that the impacts of cybercrime is far reaching and any one, may it be a person or an entity can be a victim of cybercriminal activities. Recently in the US, eight members of a global cybercrime ring were charged in one of the biggest ever bank heists. The cybercrime gang allegedly stole US$45 million by hacking into credit card processing firms and withdrawing money from ATMs in 27 countries (Jessica et al. 2013). An extreme example, the above case highlights how IT is changing the way crimes are being committed. No longer do criminals use masks, guns and get-a-way cars, criminals are able to commit crimes in the comfort of their homes, millions of miles from the scene of the crime and can access significant sums of money that can financially cripple organisations. The world is taking notice of this growing threat and organisations in the Pacific must also be proactive in tackling this emerging issue.

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Designers need to develop good observational skills in order to conduct user studies that reveal the subtleties of human interactions and adequately inform design activity. In this paper we describe a game format that we have used in concert with wiki-web technology, to engage our IT and Information Environments students in developing much sharper observational skills. The Video Card Game is a method of video analysis that is suited to design practitioners as well as to researchers. It uses the familiar format of a card game similar to "Happy Families,, to help students develop themes of interactions from watching video clips. Students then post their interaction themes on wiki-web pages, which allows the teaching team and other students to edit and comment on them. We found that the tangible (cards), game, role playing and sharing aspects of this method led to a much larger amount of interaction and discussion between student groups and between students and the teaching team, than we have achieved using our traditional teaching methods, while taking no more time on the part of the teaching staff. The quality of the resulting interaction themes indicates that this method fosters development of observational skills.In the paper we describe the motivations, method and results in full. We also describe the research context in which we collected the videotape data, and how this method relates to state of the art research methods in interaction design for ubiquitous computing technology.

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There are two key ways in which the Australian Uniform Consumer Credit Code seeks to protect consumers in relation to consumer credit transactions. The first is by means of disclosure regulation where information is required to be disclosed to the consumer before the credit contract is entered into and the second is by way of “safety net” provisions, where contracts can be varied or set aside in the event of hardship, a finding that the transaction was unjust, or a finding of unconscionable fees or charges. This article explores the limitations of both of these means of protection, particularly in the case of vulnerable, low-income consumers. In order to highlight the inadequacies of these forms of consumer protection and the need for regulatory reform, we draw on interviews conducted with 30 low-income consumers who had recently signed a credit contract, focusing on their understanding of information disclosed in the contract, as well as their responses to hypothetical unfair terms and their understanding of their rights, for example in the event of an unjust transaction. These interviews were conducted as part of a joint research project between Brotherhood of St Laurence and Griffith University’s Centre for Credit and Consumer Law, funded by Consumer Affairs Victoria.

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Australia is going through a major reform of consumer credit regulation, with the implementation of a proposal to transfer regulatory responsibility from the State and Territory Governments to the Commonwealth Government. While the broad policy approach is supported, the reform process has missed a significant opportunity to engage directly with issues of financial exclusion and with the potential role of regulation to reduce financial exclusion. The imposition of an interest rate cap can limit the impact of financial exclusion. However, the future of the existing interest rate caps is uncertain, given the diversity of approaches, and the heated debate that surrounds this issue. In the absence of support for regulatory initiatives to increase the availability of low cost, small loans, permitting regulatory diversity on this issue of interest rate caps, within an otherwise centralised regulatory framework., can minimise the impact of financial exclusion on consumers.

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Mirroring the trends in other developed countries, levels of household debt in Australia have risen markedly in recent years. As one example, the total amount lent by banks to individuals has risen from $175.5 billion in August 1995 to $590.5 billion in August 2005.1 Consumer groups an~ media commentators here have long raised concerns about the risks of increasing levels of household debt and over-commitment, linking these issues at least in part to irresponsible lending practices. And more recently, the Reserve Bank Governor has also expressed concerns about the ability 'of some households to manage if personal or economic circumstances change.2

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Micro-finance, which includes micro-credit as one it its services, has become big business with a range of models – from those that operate on a strictly business basis to those who come from a philanthropic base, through Non Government organisations (NGOs). Success is often measured by the numbers involved and the repayment rates – which are very high, largely because of the lending models used. The purpose of this paper is to identify whether the means used to deliver micro-credit services to the poor are socially responsible. This paper will explore the range of models currently used and propose a model that addresses some of the social responsibility issues that appear to plague delivery. The model is being developed in Beira, the second largest city in Mozambique. Mozambique exhibits many of the characteristics found in other African countries, so the model, if successful, may have implications for other poor African nations.

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These cards are designed as a resource for implementing participatory action research (PAR) in social programs. Each card covers one of the five key stages of PAR as outlined in the manual 'On PAR- Using participatory Action Research to Improve Early Intervention' (Crane and O'Regan 2010).

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Micro-finance, which includes micro-credit as one of its core services, has become an important component of a range of business models – from those that operate on a strictly economic basis to those that come from a philanthropic base, through Non Government Organisations (NGOs). Its success is often measured by the number of loans issued, their size, and the repayment rates. This paper has a dual purpose: to identify whether the models currently used to deliver micro-credit services to the poor are socially responsible and to suggest a new model of delivery that addresses some of the social responsibility issues, while supporting community development. The proposed model is currently being implemented in Beira, the second largest city in Mozambique. Mozambique exhibits many of the characteristics found in other African countries so the model, if successful, may have implications for other poor African nations as well as other developing economies.