Conventional Credit Research Articles

Evaluating the Gendered Credit Constraints and Uptake of an Insurance-Linked Credit Product Among Smallholder Farmers in Kenya

Using data from a multi-arm experiment among maize and bean smallholder farmers in Kenya, we evaluate the gender differences in credit rationing, and whether an insurance-bundled credit product, known as risk-contingent credit (RCC) could enhance credit access for both men and women. Using 3 years of household survey data, we find that female-headed households are significantly more risk-rationed (or demand-side rationed) than men. Post-intervention, we find that the impacts of RCC on credit uptake decisions are significantly larger than those of conventional credit. We also find that RCC impacts do not vary across the different gender categories.

Robust integration of blockchain and explainable federated learning for automated credit scoring

This article examines the integration of blockchain, eXplainable Artificial Intelligence (XAI), especially in the context of federated learning, for credit scoring in financial sectors to improve the credit assessment process. Research shows that integration of these cutting-edge technologies is in its infancy, specifically in the areas of embracing broader data, model verification, behavioural reliability and model explainability for intelligent credit assessment. The conventional credit risk assessment process utilises historical application data. However, reliable and dynamic transactional customer data are necessary for robust credit risk evaluation in practice. Therefore, this research proposes a framework for integrating blockchain and XAI to enable automated credit decisions. The main focus is on effectively integrating multi-party, privacy-preserving decentralised learning models with blockchain technology to provide reliability, transparency, and explainability. The proposed framework can be a foundation for integrating technological solutions while ensuring model verification, behavioural reliability, and model explainability for intelligent credit assessment.

Penerapan Prinsip Kehati-hatian Pada Data Nasabah Pinjaman Secara Online

Introduction: Process of providing loans without intermediaries such as banks and credit institutions, there is a special website in the form of an implementation platform where the user can become a giver. In online loans, some are guaranteed and some are without collateral, this can lead to misuse of personal data for users of financial technology services.Purposes of the Research: The purpose of writing this thesis is to find out and explain the application of the precautionary principle of online loan customer data and how the form of legal protection for online loan customer data.Methods of the Research: The research method used in this study is normative juridical with a conceptual approach and statutory regulations and legal materials used are primary and secondary legal materials.Results of the Research: The The results of this study indicate that financial technology is an innovation or a combination of conventional banking credit agreement systems with a touch of modern technology. The system for managing credit agreements in financial technology includes: Basic Banking Law No. 10 of 1998, Bank Indonesia Regulation (PBI) No. 19/12/PBI/2017 concerning the Implementation of Fintech, Financial Services Authority Regulation No. 77/POJK.01/2016 regarding Information Technology-Based Money Borrowing Services Digital Financial Services, then Regulations regarding the principle of prudence in fintech credit agreements have the same rights and obligations between conventional credit agreements with fintech.

Study of the Differentiation of Conventional Credit Card and Sharia Card Products in Sharia Banks

The development of sharia banking in Indonesia has experienced quite significant growth. It is based on the innovation of the credit card product issued by Sharia banking, namely the Syariah Card. This research aims to explain the differences between conventional credit card products and sharia cards regarding mechanism and product use. This research uses a qualitative method with a descriptive approach. The research results found that the differences between conventional credit card products and Sharia cards are in the transaction agreement scheme used, interest and the use of fees (juror) on Sharia cards. The existence of Sharia cards refers to the fatwa of the National Sharia Council of the Indonesian Ulema Council regarding the permissibility of Sharia credit cards No.54/DSN-MUI/X/2006 concerning Sharia Cards. The difference between Sharia cards and conventional credit cards is that Sharia cards are not allowed to charge interest but only remuneration (juror) or fees from each transaction. Conventional credit cards use interest-based because they assume the "time value of money" is money. It is just a medium of exchange that turns into a commodity that can reproduce only because of the opportunity factor of time, without the role of humans who work on it. Sharia banking needs to use this as a reference in making products for the public.

Impact of Financial Inclusion Efforts Among the Tribal Groups in Wayanad-Kerala

This examination explores the effect of monetary consideration drives on ancestral gatherings in Weaned, explicitly zeroing in on their admittance to formal financial administrations. Notwithstanding the ubiquity of money, ancestral networks in Wayanad display a hesitance to completely embrace monetary innovation, credited to their one-of-a-kind social design. In any case, a mind-boggling 94.8% of ancestral families in the locale have ledgers, mirroring a significant mix into the formal monetary area. Remarkably, support in the MGNREGS program arises as a critical driver, with 54.5% of clans referring to it as the essential inspiration for getting ledgers. In any case, the review highlights that monetary consideration alone doesn't resolve the basic issue of financial weakness. Clans, as other low-pay gatherings, face difficulties in getting credit from formal banks because of rigid circumstances. Thusly, casual monetary players, common in regions with low monetary proficiency, assume a pivotal part in gathering the credit needs of these monetarily denied networks. These 'non-status moneylenders' in many cases exploit the monetary weaknesses of clans, propagating their desperate conditions. The exploration features the unavoidable dependence on casual sources and highlights the current holes in the conventional credit market, encouraging the requirement for fitted monetary answers for elevate monetarily denied networks.

An explainable federated learning and blockchain-based secure credit modeling method

Federated learning has drawn a lot of interest as a powerful technological solution to the “credit data silo” problem. The interpretability of federated learning is a crucial issue due to the lack of user interaction and the complexity of credit data monitoring. We advocate the importance of a credit data processing-as-a-service model, which completes conventional credit models in local environments, in order to overcome these restrictions. In particular, we describe an explainable federated learning and blockchain-based credit scoring system (EFCS) in this work. First, we propose an explainable federated learning method with controllable machine learning efficiency and controllable credit model decision making, thus having controllable credit model complexity and transparent and traceable credit decision-making mechanism. Then, we suggest an explainable federated learning training mechanism for credit data that prevents leakage of the model gradients trained by individual nodes during the training of the overall model. Neither the credit data provider nor the data user has access to the raw data in the credit model training ecosystem. Therefore, privacy protection, model performance, and algorithm efficiency, the core triangular cornerstones of federated learning, when added with model interpretability, together constitute a more secure and trustworthy federated learning-based methodology, thus providing a more reliable service for credit model training and construction. The EFCS scheme is presented via simulations of different types of federated learning and their resistance to system attack, applying the proposed model to six different credit scoring datasets. Extensive experimental analyses support the efficiency, security, and explainability of the EFCS.

Female smallholder farmers’ preferences for digital and conventional credit attributes: evidence from Madagascar

PurposeDigital credit is spreading rapidly across Sub-Saharan Africa and holds potential for financial inclusion and female financial autonomy. Women in developing economies have long been targeted by microfinance institutions due to the women’s reliability and positive spillover effects. Yet, adoption rates for digital financial innovations remain moderate among rural women in Sub-Saharan Africa. The authors explore whether female preferences for digital and conventional credit differ from males.Design/methodology/approachThe authors conduct a Discrete Choice Experiment with 420 smallholder farmers in central Madagascar, one of the region's poorest countries, to assess preferences for selected digital and conventional credit attributes.FindingsResults of the mixed logit model and the comparison of the willingness-to-pay via Poe-test suggest high general demand for both credit forms. The demand of female respondents is higher than that of males, suggesting that they might be underserved. This holds for both credit forms. However, differences in willingness to pay for the credit attributes are mostly not statistically significant, indicating that designing gender-specific services may not be advisable.Originality/valueThis article is believed to be the first to assess and compare gendered willingness to pay for digital and conventional credit. The study’s findings give valuable insights to decision-makers in development politics as well as the fintech industry.

Structural credit risk model driven by Lévy process under knight uncertainty.

As per the projections of conventional credit risk structured model, the risky asset values tend to adhere to the geometric Brownian motion. On the contrary, the risky asset values remain a non-continuous and dynamic ones and jump based on the conditions. Is not possible to measure the real Knight Uncertainty risks in financial markets with the help of a single probability measure. In this background, the current research work analyzes a structural credit risk model that belongs to Levy market under Knight Uncertainty. With the help of Lévy-Laplace exponent, the authors developed a dynamic pricing model in this study and acquired the price intervals for default probability, stock value and the bond value of enterprise. To be specific, the study intended to establish explicit solutions for three value processes, discussed earlier, with an assumption that the jump process follows a log-normal distribution. At the end, the study also conducted numerical analysis to understand the crucial role played by Knight Uncertainty upon the pricing of default probability and the stock value of the enterprise.

COMPARISON OF THE PERFORMANCE OF SHARIA BANKS AND CONVENTIONAL BANKS

This study aims to find out and analyze the significant differences between the performance of conventional banks and Islamic banks and to find out and analyze which banking performance is better between Islamic and conventional banking. This study uses a qualitative descriptive method using secondary data. From the results of the study there is a significant difference between conventional banking and Islamic banking such as the absence of interest in Islamic banking considering that interest is forbidden in Islamic law as usury. Furthermore, in terms of risk in conventional credit, the customer still has to pay the full loan and interest as previously agreed. Both when the business makes a profit or loss while sharia credit if the contract used is capital sharing,

Research and Implementation of Credit Investigation Sharing Platform Based on Double Blockchain

As the development of the modern economy is increasingly inseparable from credit support, the traditional credit investigation mode has yet to meet this demand. Because of the difficulties in conventional credit data sharing among credit investigation agencies, poor data portability, and centralized supervision, this paper proposes a data-sharing scheme for credit investigation agencies based on a double blockchain. Given the problems such as difficult data sharing, difficult recovery of damaged data, and accessible data leakage between institutions and users with non-traditional credit investigation data other than credit, this paper proposes a data-sharing scheme for credit investigation subjects based on the digital envelope. Based on the above two solutions, this paper designs a double blockchain credit data-sharing platform based on the “public chain + alliance chain” from credit investigation agencies’ and visiting subjects’ perspectives. The sharing platform uses the alliance chain as the management chain to solve the problem of complex data sharing between credit bureaus and centralized supervision, uses the public chain as the use chain to solve the problem of complex data sharing between the access subject and the credit bureaus, uses the interplanetary file system and digital envelope and other technologies to solve the problem of difficult recovery of damaged data, data leakage, and other issues. After the upload test, the average upload speed reaches 80.6 M/s. The average download speed of the system is 88.7 M/s after the download test. The multi-thread stress test tests the linkage port on the system package, and the average response time for the hypertext transfer protocol (HTTP) is 0.6 ms. The system performance and security analysis show that the sharing platform can provide safe and reliable credit-sharing services for organizations and users and high working efficiency.

FROM CREDIT SCORING TO REGULATORY SCORING: COMPARING CREDIT SCORING MODELS FROM A REGULATORY PERSPECTIVE

Conventional credit scoring models evaluated by predictive accuracy or profitability typically serve the financial institutions and can hardly reflect their contribution on financial stability. To remedy this, we develop a novel regulatory scoring framework to quantify and compare the corresponding regulatory capital charge errors of credit scoring models. As an application of RegTech, the proposed framework considers the characteristic of example-dependence and costsensitivity in credit scoring, which is expected to enhance the ability of risk absorption of financial institutions and thus benefit the regulators. Validated on two real-world credit datasets, empirical results reveal that credit scoring models with good predictive accuracy or profitability do not necessarily provide low capital charge requirement error, which further highlights the importance of regulatory scoring framework. The family of gradient boosting decision tree (GBDT) provides significantly better average performance than industry benchmarks and deep multilayer perceptron network, especially when financial stability is the primary focus. To further examine the robustness of the proposed regulatory scoring, sampling techniques, cut-off value modification, and probability calibration are employed within the framework and the main conclusions hold in most cases. Furthermore, the analysis on the interpretability via TreeSHAP algorithm alleviates the concerns on transparency of GBDT-based models, and confirms the important roles of loan characteristics, borrowers’ solvency and creditworthiness as powerful predictors in credit scoring. Finally, the managerial implications for both financial institutions and regulators are discussed.

The Value of Open Banking Data for Application Credit Scoring: Case Study of a Norwegian Bank

Banks generally use credit scoring models to assess the creditworthiness of customers when they apply for loans or credit. These models perform significantly worse when used on potential new customers than existing customers, due to the lack of financial behavioral data for new bank customers. Access to such data could therefore increase banks’ profitability when recruiting new customers. If allowed by the customer, Open Banking APIs can provide access to balances and transactions from the past 90 days before the score date. In this study, we compare the performance of conventional application credit scoring models currently in use by a Norwegian bank with a deep learning model trained solely on transaction data available through Open Banking APIs. We evaluate the performance in terms of the AUC and Brier score and find that the models based on Open Banking data alone are surprisingly effective in predicting default compared to the conventional credit scoring models. Furthermore, an ensemble model trained on both traditional credit scoring data and features extracted from the deep learning model further outperforms the conventional application credit scoring model for new customers and narrows the performance gap between application credit scoring models for existing and new customers. Therefore, we argue that banks can increase their profitability by utilizing data available through Open Banking APIs when recruiting new customers.

Manifestation of Sharia-based credit in its realization fulfilling needs using a credit system

Sharia credit is the provision of money based on a loan agreement or agreement between the lender and the recipient. The recipient must return the money within the agreed timeframe in exchange for profit sharing. This article aims to analyze and explain the description of Sharia credit, distinguish Sharia credit from conventional credit, and the effectiveness of Sharia credit in Indonesia. Sharia credit is a product of Sharia-based financial institutions in which all transactions are exempt from laws violating religion's provisions. The most fundamental difference between Islamic credit and conventional credit is in the remuneration system. Established credit uses interest rates, while Islamic credit uses a profit-sharing system based on an agreement. The results of writing this article show that Sharia credit is more down-to-earth than conventional credit with all the advantages possessed by Sharia credit. It does not apply an exciting system but implements a profit-sharing or <em>mudharabah</em> system. Through the profit-sharing system, Islamic credit is hoped to improve the economy by providing financing to those in need without violating Islamic religious rules.

Awareness towards Selection of Islamic Credit Card Among Malaysian Consumers

This study aimed to explore the level of awareness and understanding of Malaysian bank consumers on Islamic credit cards. The majority of bank consumers still lack awareness and knowledge in understanding about Islamic contracts in the bank. Still, only a few consumers are aware and choose Islamic credit cards facilities to avoid the prohibited element and get more benefits from Islamic credit cards. This study has used the quantitative method research. This study uses questionnaires to achieve the objectives of the research. A questionnaire has been designed and data was collected from 100 respondents of bank consumers in Malaysia. According to the findings, religious beliefs and attitudes were the most influential factors among Malaysian bank consumers' decisions to use Islamic credit cards. All of the hypotheses have been accepted. The limitation of this study was that only the employed respondents could answer this survey for the scope of this research. Furthermore, consumers who use Islamic credit cards are still the lowest compared to Conventional credit cards, thus the difficulty in collecting the data. The outcomes of this study will be used as a framework for future research in Islamic card usage and design. The Islamic credit card concept may also be applied to other Islamic products and services. These findings contribute to the level of knowledge of bank consumers in deciding to use Islamic credit cards.

The Islamic Finance in Relationship to the Financing and the Taxation of Small and Medium Enterprises in Tunisia

The present article aims to improve the understanding on how the Islamic financial contribute to the financing of small and medium enterprises (SME) in Tunisia. It discusses the difficulty of accessing to finance and the principles of the Islamic finance that most it brings to Tunisian SMEs. It adopts an exploratory survey approach in a population Tus, our survey was carried out on the basis of a sample of thirty SMEs operating in the city of Gafsa, and which working in various several sectors, and which are selected at randomly. The findings show that, the tax optimization of Islamic financing in the case of SMEs requires an adapted approach from the Tunisian tax administration. In this case, the amount of taxes payable would be close to that payable on the occasion of a conventional credit arrangement. The findings stipulate that the access to bank financing in Tunisia is difficult or even impossible due to several factors such as the lack of guarantees, numerous requirements, hard bureaucracy, lack of personal relations within the bank. The use of Islamic financing is important since more than half of the entrepreneurs have used Islamic finance products, the most of the entrepreneurs who have used Islamic financing have chosen the Murabaha type of financing with a percent of 80%, and the majority of entrepreneurs are satisfied with the products offered by Islamic institutions (56%). Islamic financial, SMEs, Murabaha, survey approach, Tunisia

ANALISIS PERSEPSI MASYARAKAT TENTANG LAYANAN PEMBIAYAAN BERBASIS TEKNOLOGI INFORMASI BERDASARKAN PRINSIP SYARIAH (Studi Desa Situ Udik Kecamatan Cibungbulang Kabupaten Bogor)

ABSTRACT
 
 The purpose of this study was to determine the knowledge and public perception of digital-based (online) financing services based on sharia principles. the method used is descriptive qualitative. The primary data in this study are the people of Situ Udik Village, Cibungbulang District, Bogor, while the secondary data is in the form of information obtained from the internet, books, journals, articles and other literature. Based on the results of the study, it can be concluded that most (70%) people do not know about digital-based services (online) based on sharia principles. In addition, the analysis of public perception in terms of needs (48%) of the community is quite in need and when viewed from the perspective of interest (44%) the community is quite concerned with using digital-based (online) financing services based on sharia principles. with the perception to avoid the practice of usury and avoid the frauds that occur in conventional credit. In this case, it is necessary to increase socialization and the existence of facilitators to increase public awareness in order to avoid the practice of usury.
 
 Keywords: Perception, Financing, Information Technology, Sharia Principles.

Muslims and non-Muslims intention to hold Shariah-compliant credit cards: a SmartPLS approach

PurposeThe purpose of this paper is to examine the relationship between attitude, subjective norm, perceived behavioural control, religiosity, knowledge and Shariah-compliance with intention to hold Shariah-compliant credit card (SCCC) amongst Muslims and non-Muslims.Design/methodology/approachResearchers used survey questionnaire to collect data and applied a purposive sampling method, then analyzing the data using descriptive statistics and also multi-group analysis of SmartPLS.FindingsFor Muslims, attitude, subjective norm, Shariah-compliance, knowledge and religiosity are positively significant. While for non-Muslims, only attitude and subjective norm are positively significant to intention to hold SCCCs.Research limitations/implicationsThe behavioural study only focusses on intention to hold Islamic credit cards, which is constraining the extended model of the theory of planned behaviour (TPB) without the actual performance of the behaviour, which is holding SCCCs. Secondly, the research caters for a single method, namely, quantitative without including the qualitative method to better understand and explore other factors affecting consumers’ behavioural intention. The qualitative part can be carried out by conducting interviews with practitioners, regulators and customers. Thirdly, the cultural dimensions are not combined as parts of TPBs’ antecedents for extended model that could be affecting intention, as Malaysia has diverse ethnic groups with different religious background.Practical implicationsIn terms of managerial implications, the findings will further assist financial service providers to develop more effective marketing strategies for Islamic financial products not just to cater for the Muslims but also the non-Muslims, who are increasingly attracted to Islamic banking. As many Muslims are still holding conventional credit cards, it is timely for the Islamic financial institutions to attract them with the SCCCs.Social implicationsFinancial marketers are expected to be qualified and well-versed on the different Islamic product structures and also the conventional products. By having such enables them to enlighten and create awareness amongst the targeted consumers in seeking Shariah-compliant financial-related products.Originality/valueThe research will contribute to new theoretical knowledge of an extended behavioural model in relation to customers’ perception towards SCCCs’ acceptance.

Experiences from the Dutch instant payment project: From 0 to 289 million in one year

In May 2015 the leading Dutch banks announced their ambition to offer instant payments (IP) to the Dutch market in four years. The complex and innovative programme, led by the Dutch Payments Association, delivered, in mid-2019, a new IP infrastructure that has now become one of the fastest growing IP environments, with over 289 million interbank IP transactions processed in its first year (April 2019–March 2020). This paper looks back on that period and focuses on the elements that, in our view, were important to the successful introduction of this new payments infrastructure. The challenges, dilemmas and the rationale for the decision of the Dutch banking community to organise the IP project are described. The journey towards achieving all the set goals by means of a clear joint effort from the Dutch payments community was intense and rewarding. IP is expected to become the new normal for SEPA payments in the years to come, provided that some hurdles to full interoperability and reachability in SEPA will be overcome. This paper aims to share insights that may be useful to other parties that are considering introducing IP or that want to push a similar transition from conventional credit transfers towards a 24/7 available, interbank IP backbone (See figure 1 for actual transaction volumes on this new IP backbone).

Farmers' willingness to pay for digital and conventional credit: Insight from a discrete choice experiment in Madagascar.

In recent decades, microfinance institutions with financial products designed for low income groups have been established all over the world. However, credit access for farmers in developing countries remains low. Digital financial services are rapidly expanding globally at the moment. They also bear great potential to address the credit needs of farmers in remote rural areas. Beyond mobile money services, digital credit is successively offered and also discussed in literature. Compared to conventional credit which is granted based on a thorough assessment of the loan applicant’s financial situation, digital credit is granted based on an automated analysis of the existing data of the loan applicant. Despite the potential of digital credit for serving the credit needs of rural farmers, empirical research on farmers’ willingness to pay for digital credit is non-existent. We employ a discrete choice experiment to compare farmers’ willingness to pay for digital and conventional credit. We apply loan attributes which reflect typical characteristics of both credit products. Our results indicate a higher willingness to pay for digital credit compared to conventional credit. Furthermore, we find that the proximity to withdraw borrowed money has a higher effect on farmers’ willingness to pay for digital credit compared to conventional credit. Furthermore, our results show that instalment repayment condition reduces farmers’ willingness to pay for digital credit whilst increasing their willingness to pay for conventional credit. Additionally, we find that longer loan duration has a higher effect on farmers’ willingness to pay for digital credit compared to conventional credit whereas higher additional credit cost has a lower effect on farmers’ willingness to pay for conventional credit compared to digital credit. Our results highlight the potential of digital credit for agricultural finance in rural areas of Madagascar if a certain level of innovation is applied in designing digital credit products.

Promises and pitfalls of digital credit: Empirical evidence from Kenya.

Digital credit is a recent innovation that raises hopes of improving credit access in developing countries. However, up until now, empirical research on the extent to which digital credit actually reaches people who are otherwise excluded from conventional credit markets and whether increased credit access is sustainable or threatened by high default and blacklisting rates is very scarce. Using representative data from Kenya, this article shows that digital credit increases borrowing opportunities, including for people less likely to otherwise have credit access in the conventional credit markets. However, we find that digital credit borrowing is also responsible for 90% of all blacklistings, which is partially driven by higher default rates in the digital credit market but also by a higher probability that digital credit defaults lead to blacklisting of the borrower, compared to defaults in other credit markets.