Search results for: home credit

Authors: Neha Ahirwar

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In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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Authors: Nasir Mehmood, Muhammad Yar Khan, Anam Javeed

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This study aims to scrutinize the dynamics which tend to impact customer’s purchasing intention of Islamic credit card and nexus of product’s knowledge and religiosity with the attitude of potential Islamic credit card’s customer. The theory of reasoned action strengthened the idea that intentions due to its proven predictive power are most likely to instigate intended consumer behavior. Particularly, the study examines the relationships of perceived financial cost (PFC), subjective norms (SN), and attitude (ATT) with the intention to purchase Islamic credit cards. Using a convenience sampling approach, data have been collected from 450 customers of banks located in Rawalpindi and Islamabad. A five-point Likert scale self-administered questionnaire was used to collect the data. The data were analyzed using the Statistical Package of Social Sciences (SPSS) through the procedures of principal component and multiple regression analysis. The results suggested that customer’s religiosity and product knowledge are strong indicators of attitude towards buying Islamic credit cards. Likewise, subjective norms, attitude, and perceived financial cost have a significant positive impact on customers’ purchase intent of Islamic bank’s credit cards. This study models a useful path for future researchers to further investigate the underlined phenomenon along with a variety of psychodynamic factors which are still in its infancy, at least in the Pakistani banking sector. The study also provides an insight to the practitioners and Islamic bank managers for directing their efforts toward educating customers regarding the use of Islamic credit cards and other financial products.

Keywords: attitude, Islamic credit card, religiosity, subjective norms

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Authors: Bo-wen Zhu, Bin Wu, Feng Chen

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It has become a common measure among governments to support green development of enterprises through Green Credit policies. In China, the Central Bank of China and other authorities even put forward corresponding assessment requirements for proportion of green credit in commercial banks. Policy changes might raise concerns about commercial banks turning a blind eye to greenwashing behavior by enterprises. The lack of effective regulation may lead to a diffusion of such behavior, and eventually result in the phenomenon of “bad money driving out good money”, which could dampen the incentive effect of Green Credit policies. This paper employs a complex network model based on an evolutionary game analysis framework involving enterprises, banks, and regulatory authorities to investigate inhibitory effect of the Green Credit regulation on enterprises’ greenwashing behavior, banks’ opportunistic and collusive behaviors. The findings are as follows: (1) Banking opportunism rises with Green Credit evaluation criteria and requirements for the proportion of credit balance. Restrictive regulation against violating banks is necessary as there is an increasing trend of banks adopting opportunistic strategy. (2) Raising penalties and probability of regulatory inspections can effectively suppress banks’ opportunistic behavior, however, it cannot entirely eradicate the opportunistic behavior on the bank side. (3) Although maintaining a certain inspection probability can inhibit enterprises from adopting greenwashing behavior, enterprises choose a catering production strategy instead. (4) One-time rewards from local government have limited effects on the equilibrium state and diffusion trend of bank regulatory decision-making.

Keywords: green credit, greenwashing behavior, regulation, diffusion effect

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

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Authors: Hai Chien Pham, Thi Phuong Anh Vo, Chansik Park

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Risks management in construction projects is important to ensure the positive feasibility of the projects in which financial risks are most concerned while construction projects always run on a credit basis. Credit risks, therefore, require unique and technical tools to be well managed. Underwriting technique in credit risks, in its most basic sense, refers to the process of evaluating the risks and the potential exposure of losses. Risks analysis and underwriting are applied as a must in banks and financial institutions who are supporters for constructions projects when required. Recently, construction organizations, especially contractors, have recognized the significant increasing of credit risks which caused negative impacts to project performance and profit of construction firms. Despite the successful application of underwriting in banks and financial institutions for many years, there are few contractors who are applying this technique to analyze and mitigate the credit risks of their potential owners before signing contracts with them for delivering their performed services. Thus, contractors have taken credit risks during project implementation which might be not materialized due to the bankruptcy and/or protracted default made by their owners. With this regard, this study proposes a model using the underwriting technique for contractors to analyze and assess credit risks of their owners before making final decisions for the potential construction contracts. Contractor’s underwriters are able to analyze and evaluate the subjects such as owner, country, sector, payment terms, financial figures and their related concerns of the credit limit requests in details based on reliable information sources, and then input into the proposed model to have the Overall Assessment Score (OAS). The OAS is as a benchmark for the decision makers to grant the proper limits for the project. The proposed underwriting model is validated by 30 subjects in Asia Pacific region within 5 years to achieve their OAS, and then compare output OAS with their own practical performance in order to evaluate the potential of underwriting model for analyzing and assessing credit risks. The results revealed that the underwriting would be a powerful method to assist contractors in making precise decisions. The contribution of this research is to allow the contractors firstly to develop their own credit risk management model for proactively preventing the credit risks of construction projects and continuously improve and enhance the performance of this function during project implementation.

Keywords: underwriting technique, credit risk, risk management, construction project

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Authors: Margarita Gáfaro, Karelys Guzmán, Paola Poveda

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This paper establishes the theoretical aspects that explain the barriers to accessing credit for small agricultural producers in developing countries and identifies successful policy experiences to mitigate them. We will test two hypotheses. The first one is that information asymmetries, high transaction costs and high-risk exposure limit the supply of credit to small agricultural producers in developing countries. The second hypothesis is that low levels of financial education and productivity and high uncertainty about the returns of agricultural activity limit the demand for credit. To test these hypotheses, a review of the theoretical and empirical literature on access to rural credit in developing countries will be carried out. The first part of this review focuses on theoretical models that incorporate information asymmetries in the credit market and analyzes the interaction between these asymmetries and the characteristics of the agricultural sector in developing countries. Some of the characteristics we will focus on are the absence of collateral, the underdevelopment of the judicial systems and insurance markets, and the high dependence on climatic factors of production technologies. The second part of this review focuses on the determinants of credit demand by small agricultural producers, including the profitability of productive projects, security conditions, risk aversion or loss, financial education, and cognitive biases, among others. There are policies that focus on resolving these supply and demand constraints and managing to improve credit access. Therefore, another objective of this paper is to present a review of effective policies that have promoted access to credit for smallholders in the world. For this, information available in policy documents will be collected. This information will be complemented by interviews with officials in charge of the design and execution of these policies in a subset of selected countries. The information collected will be analyzed in light of the conceptual framework proposed in the first two parts of this section. The barriers to access to credit that each policy attempts to resolve and the factors that could explain its effectiveness will be identified.

Keywords: agricultural economics, credit access, smallholder, developing countries

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Authors: Adewale Oladapo, C. A. Afolami

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The study analyzed the effect of micro credit access on poverty reduction among small scale women entrepreneurs in Ondo state, Nigeria. Primary data were collected in a cross-sectional survey of 100 randomly selected woman entrepreneurs. These were drawn in multistage sampling process covering four local government areas (LGAS). Data collected include socio economics characteristics of respondents, access to micro credit, sources of micro credit, and constraints faced by the entrepreneur in sourcing for micro credit. Data were analyzed using descriptive statistics, Foster, Greer and Thorbecke (FGT) index of poverty measure, Gini coefficients and probit regression analysis. The study found that respondents sampled for the survey were within the age range of 31-40 years with mean age 38.6%. Mostly (56.0%) of the respondents were educated to the tune of primary school. Majority (87.0%) of the respondents were married with fairly large household size of (4-5). The poverty index analysis revealed that most (67%) of the sample respondents were poor. The result of the Probit regression analyzed showed that income was a significant variable in micro credit access, while the result of the Gini coefficient revealed a very high income inequality among the respondents. The study concluded that most of the respondents were poor and return on investment (income) was an important variable that increased the chance of respondents in sourcing for micro-credit loan and recommended that income realized by entrepreneur should be properly documented to facilitate loan accessibility.

Keywords: entrepreneurs, income, micro-credit, poverty

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Authors: Titus Wuyah Yunana

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This study analyzed the impact of commercial agricultural credit scheme on income of beneficiary farmers in Kaduna State using the Net farm income and double difference method. A questionnaire was used to source the data from 306 farmers comprising of 153 beneficiaries and 153 non-beneficiaries. The results indicated that the net farm income of the commercial agricultural credit scheme beneficiaries increases from N15,006,352.00 before scheme to N24,862,585.00 after the first and the second phases of the scheme. There was also an increase in the net farm income of the non-beneficiaries from N9, 670,385.40 to N14, 391,469.00 during the scheme. The double difference method analysis indicated a positive mean income difference value between beneficiaries and nonbeneficiaries after the first and the second phases of the scheme. The study recommends expansion in the number of beneficiaries and efficient allocation and utilization of the resources. The government should also introduce more programs that will assist the farmers to increase their productivity, income and the economy as a whole.

Keywords: agriculture, credit scheme, farmers, income, beneficiary

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Authors: Hafsat Mustapha Hanga

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The purpose of the this study was to investigate the effect of broken home on students' academic performance. Therefore, it focused on academic performance and Parental care of the student from and intact home from a cognitive motivational perceptive. The broken and intact home and also to find out if they differ in parental care this is done by using 376 subjects out of the population of 21,378. The sample was obtained using stratified random sampling techniques as the population contained sub-groups the study design was ex-post facto. The data was collected using 3 kind of instruments. To test the first and second hypotheses. Junior secondary school placement examination result was obtained to test the academic performance of the boys fron broken home and boys from and boys from intact home and then girl from broken home and girls from intact home.T-Test was used in the analysis of first and second hypotheses. For the third hypotheses two different kind of questionnaires were developed, the first was used to identify student that are from broken home while the second was for testing parental care between the subject. Chi-square was used to analyze the third hypotheses. Alkh the three 3 hypotheses were tested and rejected and were all in favor of student from intact home. The study found that there was a significant difference in the academic performance of the boys from brokeb and boys from intact home. When boys from intact home better then those boys from broken home. It also reveals that a student from a intact from intact home receives good parental care, love and concern than those from broken home.on the strength of these findings the need to establish an institution which will help those parent who have parenting problems was stressed and also the need to foster. Home school partnership was also stressed and advocate.

Keywords: broken homes, academic performance, parental care, foster

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Authors: Adewale Oladapo, Carolyn A. Afolami

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Agricultural production should be the major financial contributor to the Nigerian economy; however, the petroleum sector had taken the importance attached to this sector. The situation tends to be more worsening unless necessary attention is given to adequate credit supply among food crop farmers. This research analyses the effect of credit use on the technical efficiency of cassava farmers in Ondo State, Nigeria. Primary data were collected from two hundred randomly selected cassava farmers through a multistage sampling procedure in the study area. Data were analysed using descriptive statistics and stochastic frontier analysis (SFA). Findings revealed that 95.0% of the farmers were male while 56.0% had no formal education and were married. The SFA showed that cassava farmer’s efficiency increased with farm size, herbicide and planting material at 5%,10% and 1% respectively but decreased with fertilizer application at 1% level while farmers’ age, education, household size, experience and access to credit increased technical inefficiency at 10%. The study concluded that cassava farmers are technically inefficient in the use of farm resources and recommended that adequate and workable agricultural policy measures that will ensure availability and efficient fertilizer distribution should be put in place to increase efficiency. Furthermore, the government should encourage youth participation in cassava production and ensure improvement in farmer’s access to credit to increase farmer’s technical efficiency.

Keywords: agriculture, access to credit, cassava farmers, technical efficiency

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Authors: Eneken Titov, Ly Hobe

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The collaboration between the universities and companies has been a challenging topic for many years, and although we have many good experiences, those seem to be single examples between one university and company. In Ülemiste Smart City in Estonia, the new initiative was started in 2020 fall, when five Estonian universities cooperated, led by the Ülemiste City developing company Mainor, intending to provide charge-free university courses for the Ülemiste City companies and their employees to encourage university-company wider collaboration. Every Ülemiste City company gets a certain number of free educational credit hours per year to participate in university courses. A functional and simple web platform was developed to mediate university courses for the companies. From January 2021, the education credit platform is open for all Ülemiste City companies and their employees to join, and universities offer more than 9000 hours of courses (appr 150 ECTS). Just two months later, more than 20% of Ülemiste City companies (82 out of 400) have joined the project, and their employees have registered for more than in total 3000 hours courses. The first results already show that the project supports the university marketing and the continuous education mindset in general, whether 1/4 of the courses are paid courses (e.g., when the company is out of free credit).

Keywords: education, educational credit, smart city, university-industry collaboration

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Authors: Aida Alemany, Laura Ballester, Ana González-Urteaga

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From 2007 subprime crisis to the recent Eurozone debt crisis the European banking industry has experienced a terrible financial instability situation with increasing levels of CDS spreads (used as a proxy of credit risk). This paper investigates whether volatility transmission channels in European banking markets have changed after three significant crises’ events during the period January 2006 to March 2013. The global financial crisis is characterized by a unidirectional volatility shocks spillovers effect in credit risk from inside to outside the Eurozone. By contrast, the Eurozone debt crisis is revealed to be local in nature with the euro as the key element suggesting a market fragmentation between distressed peripheral and non-distressed core Eurozone countries, whereas retaining the local currency have acted as a firewall. With these findings we are able to shed light on the impact of the different crises on the European banking credit risk dynamics.

Keywords: CDS spreads, credit risk, volatility spillovers, financial crisis

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Authors: M. Chumburidze, N. Salia, T. Namchevadze

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This work deal with case processing problems in business. The task of strategic credit requirements management of cases portfolio is discussed. The information model of credit requirements in a binary tree diagram is considered. The algorithms to solve issues of prioritizing clusters of cases in business have been investigated. An implementation of priority queues to support case management operations has been presented. The corresponding pseudo codes for the programming application have been constructed. The tools applied in this development are based on binary tree ordering algorithms, optimization theory, and business management methods.

Keywords: credit network, case portfolio, binary tree, priority queue, stack

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Authors: A. Bolaji Adesoye, Alimi Olorunfemi

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This paper examines the impact of small and medium-scale enterprises (SMEs) credit financing and financial market development and their shocks on the output growth of Nigeria. The study estimated a VAR model for Nigeria using 1970-2013 annual data series. Unit root tests and cointegration are carried out. The study also explores IRFs and FEVDs in a system that includes output, commercial bank loan to SMEs, domestic credit to private sector by banks, money supply, lending rate and investment. Findings suggest that shocks in commercial bank credit to SMEs has a major impact on the output changes of Nigeria. Money supply shocks also have a sizeable impact on output growth variations amidst other financial instruments. Lastly, neutrality of investment does not hold in Nigeria as it also has impact on output fluctuations.

Keywords: SMEs financing, financial development, investment, output, Nigeria

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Authors: Noelia Collado-Rodriguez

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The Mortgage Credit Directive 2014/17/UE should have been transposed the 21st of March of 2016. However, in Spain not only we did not meet the deadline, but currently we just have a preliminary draft of the so-called Mortgage Credit Act. Before we analyze the preliminary draft from the standpoint of the responsible lending principle, we should point out that this preliminary draft is not a consumer law statute. Through the text of the preliminary draft we cannot see any reference to the consumer, but we see references to the borrower. Furthermore, and more important, the application of this statute would not be, according to its text, circumscribed to borrowers who address the credit to a personal purpose. Instead, it seems that the preliminary draft aims to be one more of the rules of banking transparency that already exists in the Spanish legislation. In this sense, we can also mention that the sanctions contained in the preliminary draft are referred to these laws of banking ordination and oversight – where the rules of banking transparency belong –. This might be against the spirit of the Mortgage Credit Directive, which allows the extension of its scope to credits aimed to acquire other immovable property beyond the residential one. However, the borrower has to be a consumer accordingly with the Directive. It is quite relevant that the prospective Spanish Mortgage Credit Act might not be a consumer protection statute; specially, from the perspective of the responsible lending principle. The responsible lending principle is a consumer law principle, which is based on the structural weakness of the consumer’s position in the relationship with the creditor. Therefore, it cannot surprise that the Spanish preliminary draft does not state any of the pre contractual conducts that express the responsible lending principle. We are referring to the lender’s duty to provide adequate explanations; the consumer’s suitability test; the lender’s duty to assess consumer’s creditworthiness; the consultation of databases to perform the creditworthiness assessment; and the most important, the lender’s prohibition to grant credit in case of a negative creditworthiness assessment. The preliminary draft just entitles the Economy Ministry to enact provisions related to those topics. Thus, the duties and rules derived from the responsible lending principle included in the EU Directive will not have legal character in Spain, being mere administrative regulations. To conclude, the two main questions that come up after reading the Spanish Mortgage Credit Act preliminary draft are, in the first place, what kind of consequences might arise from the Mortgage Credit Act if finally it is not a consumer law statute. And in the second place, what might be the consequences for the responsible lending principle of being developed by administrative regulations instead of by legislation.

Keywords: consumer credit, consumer protection, creditworthiness assessment, responsible lending

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Authors: N. Yachou, R. Aboulaich

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Home is a basic necessity for human life, that why home financing takes a large chunk of people’s income. Therefore, Islamic and Conventional Banks try to offer new product in order to respond to customer needs related to home financing. Basing on this fact, we propose a Modified Diminishing Partnership model based on profit and loss sharing to reduce the duration of getting the full shares in the house property. Our proposition will be represented by the rental that customer has to give every month to the bank with redemption to increase his shares on the property of the house.

Keywords: home financing, interest rate, rental rate, modified diminishing partnership

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Paramita Nur Kurniati, Stanislaus Riyanta

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In the midst of the heightened usage of electronic money (e-money), Indonesian government expenditure is yet governed through cash-basis transactions. This conventional system brings about a number of potential risks and obstacles to operational conduct, including state financial liquidity issue. Consequently, Ministry of Finance is currently establishing the cashless payment methods for State Budget (APBN). Included in those advance methods is credit card facility as a government expenditure payment scheme. This policy is one of the innovations within the public sector learned from other countries’ best practices. Moreover, this particular method is already prominent within the private-sector realm. Qualitative descriptive analysis technique is implemented to evaluate the contemporary innovation of using government credit card in the path towards cashless society. This approach is expected to generate several benefits for the government, particularly in minimizing corruption within the state financial management. Effective coordination among policy makers and policy implementers is essential for the success of this policy’s exercise, without neglecting prudence and public transparency aspects. Government credit card usage shall be the potent resolution for enhancing the government’s overall public service performance.

Keywords: cashless basis, cashless society, government credit card, public sector innovation

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Authors: R. H. Fattepur, Sameer R. Fattepur, D. K. Sreekantha

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Dairy Farming is one of the key industries in India. India is the leading producer and also the consumer of milk, milk-based products in the world. In this paper, we have attempted to the replace the human expert system and to develop an artificial expert system prototype to increase the speed and accuracy of decision making dairy farming credit risk evaluation. Fuzzy logic is used for dealing with uncertainty, vague and acquired knowledge, fuzzy rule base method is used for representing this knowledge for building an effective expert system.

Keywords: expert system, fuzzy logic, knowledge base, dairy farming, credit risk

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Authors: Pranvera Shehaj

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Unlike any prior analysis on the withholding tax rates negotiated in tax treaties, this study looks at the treaty heterogeneity content, by investigating the impact of the residence country’s double tax relief method and of tax-sparing agreements, on the difference between developing countries’ domestic withholding taxes on dividends on one side, and treaty negotiated withholding taxes at source on portfolio dividends on the other side. Using a dyadic panel dataset of asymmetric double tax treaties between 2005 and 2019, this study suggests first that the difference between domestic and negotiated WHTs on portfolio dividends is higher when the OECD member uses the credit method, as compared to when it uses the exemption method. Second, results suggest that the inclusion of tax-sparing provisions vanishes the positive effect of the credit method at home on the difference between domestic and negotiated WHTs on portfolio dividends, incentivizing developing countries to negotiate higher withholding taxes.

Keywords: double tax treaties, asymmetric investments, withholding tax, dividends, double tax relief method, tax sparing

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Authors: Ahlam Elkilani, Bayan Elsheikh Ali, Rasha Abu Romman, Amjed Al-mousa, Belal Sababha

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The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.

Keywords: green home, resident aware, resident profile, activity learning, machine learning

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Authors: N. M. Tawil, A. R. Musa, A. I Che-Ani, H. Basri

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It is known that rising of house prices recently has affected the home ownership, especially for the future. Hence to overcome the rose of housing prices, the self-build home or DIY concept is perceived as one of the solution. This concept is proposed to be implemented for the future housing design as a strategy in helping the government to provide affordable housing, especially for middle income group to own a landed housing property. This concept is expected to offer a lower housing price for middle-income buyers and provide an opportunity for buyers to design their dream’s home with the self-build home or 'Do It Yourself' (DIY) concept. In order to implement this concept as affordable housing for MIG, the public perceptions and acceptances on the self-build home/ DIY concept itself should be identified. To achieve this aim this study was conducted by using 2 method namely literature review and questionnaire survey. The questionnaire survey was distributed to 200 respondents randomly in Lembah Klang and were analysed through the SPSS program. The results show that respondents are very interested in buying a home that they can have with the appropriate size of the home. Average of them known about Do It Yourself (DIY) concept but none of respondent have implement this concept. Most of respondents were agreed that this DIY method suitable to be implemented in the housing industry in Malaysia and they were agreed that this concept can offer a cheaper housing price because the construction costs were reduced. Moreover by providing a basic home the owner can renovate their home according to their need and financial capability.

Keywords: affordable housing, Do It Yourself, self-Built home, perception, middle income group

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Authors: Sebastian Luber

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The study demonstrates that tail inflation risk is priced into stock returns and credit spreads. This holds true even when controlling for current and historical inflation moments. The analysis employs inflation caps and floors to obtain the distribution of future inflation under the risk-neutral measure. Credit spreads decrease as the mean and median of future inflation rise, but they respond positively to tail risks. Conversely, stocks serve as a robust hedge against future inflation. Stock returns increase with a higher mean and median of future inflation and rising inflationary tail risk, while they decrease with rising deflationary tail risk.

Keywords: asset pricing, inflation expectations, tail risk, stocks, inflation derivatives, credit

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

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Authors: Mekdes Lulu

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This study assessed the soil organic C (SOC) and soil nutrients in smallholding home garden, woodlot, grazing land, and cropland at two soil depths and two sites in Wolaita Zone, southern Ethiopia. The results showed that soil properties were significantly influenced by land use. The home garden had significantly higher (p < 0.05) SOC and soil nutrients when compared to the cropland. When the home garden was compared to the woodlot and grazing land uses, it had significantly higher (p < 0.05) values except in SOC, total N (TN), cation exchange capacity (CEC), and exchangeable Ca. Cropland, in comparison with grazing land and woodlot, had a non-significant difference except TN. The SOC stock (0–40 cm) in the home garden, woodlot, grazing land and cropland was 79.5, 68.0, 65.0, and 58.1 Mg ha–1, respectively. Home garden significantly differed (p <0.05) in SOC only from cropland, and this was attributed not only to the relatively higher organic input in the home garden but also to the little organic matter input and frequently tillage of the cropland. The similar SOC among the home garden, woodlot and grazing lands may imply that the balance between inputs and outputs could be nearly similar for the land uses. Soil TN and CEC had a nearly similar pattern of difference as in SOC among the land uses because of their close relationship with SOC. In general, the land use influence on soil nutrients can be in the order: home garden > wood land » grazing land » cropland, with home garden showing the least difference from the woodlot and the greatest from the cropland. In the agroecosystem, in general, the influence of smallholding home garden on SOC and soil nutrient was marginally different from Eucalyptus woodlot and grazing lands but evidently different from cropland.

Keywords: cropland, grazing land, home garden, soc stock, soil nutrients, woodlot

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Fuchun Li, Hong Xiao

Abstract:

We propose a new early warning model for predicting financial stress events for a given future time. In this model, we examine whether credit conditions play an important role as a nonlinear propagator of shocks when predicting the likelihood of occurrence of financial stress events for a given future time. This propagation takes the form of a threshold regression in which a regime change occurs if credit conditions cross a critical threshold. Given the new early warning model for financial stress events, we evaluate the performance of this model and currently available alternatives, such as the model from signal extraction approach, and linear regression model. In-sample forecasting results indicate that the three types of models are useful tools for predicting financial stress events while none of them outperforms others across all criteria considered. The out-of-sample forecasting results suggest that the credit-regime switching model performs better than the two others across all criteria and all forecasting horizons considered.

Keywords: cut-off probability, early warning model, financial crisis, financial stress, regime-switching model, forecasting horizons

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Authors: Liyu Adhi Kasari Sulung

Abstract:

Poverty has been a major problem in Indonesia. Islamic micro finance (IMF) named Baitul Maal Wat Tamwil (Bmt) plays a prominent role to eradicate this. Indonesia as the biggest muslim country has many successful applied products such as worldwide adopt group-based lending approach, flexible financing for farmers, and gold pawning. The Problems related to these models are operation risk management and internal control system (ICS). A proper ICS will help an organization in preventing the occurrence of bad financing through detecting error and irregularities in its operation. This study aims to seek a proper risk management scheme of credit system in Bmt and internal control system’s rank for every stage. Risk management variables are obtained at the first In-Depth Interview (IDI) and Focus Group Discussion (FGD) with Shariah supervisory boards, boards of directors, and operational managers. Survey was conducted covering nationwide data; West Java, South Sulawesi, and West Nusa Tenggara. Moreover, Content analysis is employed to build the relationship among these variables. Research Findings shows that risk management Characteristics in Indonesia involves ex ante, credit process, and ex post strategies to deal with risk in credit system. Ex-ante control consists of Shariah compliance, survey, group leader reference, and islamic forming orientation. Then, credit process involves saving, collateral, joint liability, loan repayment, and credit installment controlling. Finally, ex-post control includes shariah evaluation, credit evaluation, grace period and low installment provisions. In addition, internal control order sort three stages by its priority; Credit process as first rank, then ex-post control as second, and ex ante control as the last rank.

Keywords: internal control system, islamic micro finance, poverty, risk management

Procedia PDF Downloads 407

Authors: Marija Vicic

Abstract:

The purpose of commercial credit regulation in an unified way under Law on Foreign Exchange Operations in Republic of Serbia allows an easier state monitoring of credit operations performed by non-professionals on foreign exchange market. By broadly defining the term “commercial credits“, the state (i.e. National Bank of Serbia) is given the authority to monitor the performance of all obligations under commercial contracts in which the obligations are not performed simultaneously. In the first part of the paper, the author analyses the economic gist of commercial credits with the purpose of giving an insight into their special treatment. The author examines the term „commercial credits“ given in Law on foreign exchange operations and the difference between financial credits and irregular commercial credits (exports and imports of goods and services deemed to be commercial credits) is particularly highlighted. In the second part, the author emphasizes the specifics of commercial credit contracts, especially the effects of special requests for the parties to these contracts to notify National Bank of Serbia and specific regulations regarding maturity of obligations under these commercial credits and the assignment and compensation of the said contracts.

Keywords: commercial credit, foreign exchange operations, commercial transactions, deferred payment, advance payment, (non) resident

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