Using Memory-Based Reasoning For Predicting Default Rates On Consumer Loans

In recent years, financial institutions have struggled with high default rates for consumer lending. An ability to reliably predict the probability of consumer loan defaults would have a significant impact of the profitability of that lending for these institutions. In response to this need, the financial institutions have employed loan analysis techniques such as logistic regression, discriminant analysis, and various machine learning techniques to improve the accuracy of detecting loan defaults.  The objective of these techniques is to more precisely identify creditworthy applicants who are granted credit, thereby increasing profits, from non-creditworthy applicants who would be then denied credit, thus decreasing losses. The objective of this article is to employ an emergent data analysis technique, memory-based or case-based reasoning method, to this problem to test its accuracy in discriminating between good and bad loans. This paper examines historical data from consumer loans issued by a financial institution to individuals that the financial institution considered to be qualified customers.  The data set consists of the financial attributes of each customer and includes a mixture of loans that the customers paid off or defaulted upon. The paper then compares the performance of this technique to other data mining techniques proposed in earlier works and analyzes the risk of default inherent in each loan for each technique

Construction Tender Subcontract Selection using Case-based Reasoning

Obtaining competitive quotations from suitably qualified subcontractors at tender tim n significantly increase the chance of w1nmng a construction project. Amidst an increasingly growing trend to subcontracting in Australia, selecting appropriate subcontractors for a construction project can be a daunting task requiring the analysis of complex and dynamic criteria such as past performance, suitable experience, track record of competitive pricing, financial stability and so on. Subcontractor selection is plagued with uncertainty and vagueness and these conditions are difficul_t o represent in generalised sets of rules. DeciSIOns pertaining to the selection of subcontr:act?s tender time are usually based on the mtu1t1onand past experience of construction estimators. Case-based reasoning (CBR) may be an appropriate method of addressing the chal_lenges of selecting subcontractors because CBR 1s able to harness the experiential knowledge of practitioners. This paper reviews the practicality and suitability of a CBR approach for subcontractor tender selection through the development of a prototype CBR procurement advisory system. In this system, subcontractor selection cases are represented by a set of attributes elicited from experienced construction estimators. The results indicate that CBR can enhance the appropriateness of the selection of subcontractors for construction projects

Ethics in tax practice: A study of the effect of practitioner firm size

While much of the empirical accounting literature suggests that, if differences do exist, Big Four employees are more ethical than non-Big Four employees, this trend has not been evident in the recent media coverage of Big Four tax practitioners acting for multinationals accused of aggressive tax avoidance behaviour. However, there has been little exploration in the literature to date specifically of the relationship between firm size and ethics in tax practice. We aim here to address this gap, initially exploring tax practitioners’ perceptions of the impact of firm size on ethics in tax practice using interview data in order to identify the salient issues involved. We then proceed to assess quantitatively whether employer firm size has an impact on the ethical reasoning of tax practitioners, using a tax context-specific adaptation of a well-known and validated psychometric instrument, the Defining Issues Test

Which heuristics can aid financial-decision-making?

© 2015 Elsevier Inc. We evaluate the contribution of Nobel Prize-winner Daniel Kahneman, often in association with his late co-author Amos Tversky, to the development of our understanding of financial decision-making and the evolution of behavioural finance as a school of thought within Finance. Whilst a general evaluation of the work of Kahneman would be a massive task, we constrain ourselves to a more narrow discussion of his vision of financial-decision making compared to a possible alternative advanced by Gerd Gigerenzer along with numerous co-authors. Both Kahneman and Gigerenzer agree on the centrality of heuristics in decision making. However, for Kahneman heuristics often appear as a fall back when the standard von-Neumann-Morgenstern axioms of rational decision-making do not describe investors' choices. In contrast, for Gigerenzer heuristics are simply a more effective way of evaluating choices in the rich and changing decision making environment investors must face. Gigerenzer challenges Kahneman to move beyond substantiating the presence of heuristics towards a more tangible, testable, description of their use and disposal within the ever changing decision-making environment financial agents inhabit. Here we see the emphasis placed by Gigerenzer on how context and cognition interact to form new schemata for fast and frugal reasoning as offering a productive vein of new research. We illustrate how the interaction between cognition and context already characterises much empirical research and it appears the fast and frugal reasoning perspective of Gigerenzer can provide a framework to enhance our understanding of how financial decisions are made

Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning

Decision support is a probabilistic and quantitative method designed for modeling problems in situations with ambiguity. Computer technology can be employed to provide clinical decision support and treatment recommendations. The problem of natural language applications is that they lack formality and the interpretation is not consistent. Conversely, ontologies can capture the intended meaning and specify modeling primitives. Disease Ontology (DO) that pertains to cancer's clinical stages and their corresponding information components is utilized to improve the reasoning ability of a decision support system (DSS). The proposed DSS uses Case-Based Reasoning (CBR) to consider disease manifestations and provides physicians with treatment solutions from similar previous cases for reference. The proposed DSS supports natural language processing (NLP) queries. The DSS obtained 84.63% accuracy in disease classification with the help of the ontology

THE INFLUENCE OF ACCOUNTING STUDENT MORAL REASONING AND ETHICAL SENSITIVITY TOWARD UNETHICAL ACADEMIC BEHAVIOUR

In the context of education in Indonesia, the phenomenon about the deterioration of moral values has become a kind of red light urging all parties, to immediately see an important synergy for the development of character education. Professional assessment cannot be separated from the basic value of honesty. This study aims to determine the influence of accounting student moral reasoning and ethical sensitivity toward unethical academic behaviour. The samples in this study are 200 respondents and the questionnaires were distributed to the accounting major student of economic and business faculty in Diponegoro University, Semarang. All questions were measured using a Likert scale with 5 rank answers from never to always. The data were processed using SPSS 23. Data analysis method used is quantitative analysis using validity test, reliability test, normality test, classic assumption test, multiple linear regression analysis tests, t-test, and f-test. The result of this study showed that the moral reasoning and ethical sensitivity variables have a significant influence on unethical academic behaviour on an accounting student who is studying accounting major in Diponegoro University, Semarang

Real Islamic Logic

Four options for assigning a meaning to Islamic Logic are surveyed including a new proposal for an option named "Real Islamic Logic" (RIL). That approach to Islamic Logic should serve modern Islamic objectives in a way comparable to the functionality of Islamic Finance. The prospective role of RIL is analyzed from several perspectives: (i) parallel distributed systems design, (ii) reception by a community structured audience, (iii) informal logic and applied non-classical logics, and (iv) (in)tractability and artificial intelligence

Investigating effort prediction of web-based applications using CBR on the ISBSG dataset

As web-based applications become more popular and more sophisticated, so does the requirement for early accurate estimates of the effort required to build such systems. Case-based reasoning (CBR) has been shown to be a reasonably effective estimation strategy, although it has not been widely explored in the context of web applications. This paper reports on a study carried out on a subset of the ISBSG dataset to examine the optimal number of analogies that should be used in making a prediction. The results show that it is not possible to select such a value with confidence, and that, in common with other findings in different domains, the effectiveness of CBR is hampered by other factors including the characteristics of the underlying dataset (such as the spread of data and presence of outliers) and the calculation employed to evaluate the distance function (in particular, the treatment of numeric and categorical data)

Practical reasoning in political discourse: The UK government's response to the economic crisis in the 2008 Pre-Budget Report

This article focuses on practical reasoning in political discourse and argues for a better integration of argumentation theory with critical discourse analysis (CDA). Political discourse and its specific genres (for example, deliberation) primarily involve forms of practical reasoning, typically oriented towards finding solutions to problems and deciding on future courses of action. Practical reasoning is a form of inference from cognitive and motivational premises: from what we believe (about the situation or about means—end relations) and what we want or desire (our goals and values), leading to a normative judgement (and often a decision) concerning action. We offer an analysis of the main argument in the UK government’s 2008 Pre-Budget Report (HM Treasury, 2008) and suggest how a critical evaluation of the argument from the perspective of a normative theory of argumentation (particularly the informal logic developed by Douglas Walton) can provide the basis for an evaluation in terms of characteristic CDA concerns. We are advancing this analysis as a contribution to CDA, aimed at increasing the rigour and systematicity of its analyses of political discourse, and as a contribution to the normative concerns of critical social science