Within recent years, Financial Credit Risk Assessment (FCRA) has become an increasingly important issue within the financial industry. Therefore, the search for features that can predict the credit risk of an organization has increased. Using multiple statistical techniques, a variance of features has been proposed. Applying a structured literature review, 258 papers have been selected. From the selected papers, 835 features have been identified. The features have been analyzed with respect to the type of feature, the information sources needed and the type of organization that applies the features. Based on the results of the analysis, the features have been plotted in the FCRA Model. The results show that most features focus on hard information from a transactional source, based on official information with a high latency. In this paper, we readdress and -present our earlier work [1]. We extended the previous research with more detailed descriptions of the related literature, findings, and results, which provides a grounded basis from which further research on FCRA can be conducted.
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The rise of financial technology (fintech) driven business models in banking poses a challenge for financial regulators. While the positive effects on the banking sector in terms of greater diversity and competition are generally recognized and encouraged by regulators, the nature of fintech business models may increase the risk of financial instability. Regulators are exploring ways to resolve this dilemma. The paper in hand makes a contribution to the literature by providing a framework for resolving the dilemma that is evaluated in the context of the regulatory response to the rise of fintech credit in the Netherlands. The semi-structured interviews which we conducted with four senior Dutch regulators resulted in three areas that–from their perspective–required urgent action: fintech credit companies need to lower the risk of overlending, increase pricing transparency, and improve lending standards. These findings were confirmed by the results of they survey among fintech credit clients. The current regulatory response to the rise of fintech in banking in the Netherlands provides an interesting case study that delineates the features of the future regulation of fintech in banking.
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Vietnamese farmed pangasius products have experienced major price fluctuations over numerous crop cycles exposing this important export commodity to risk and uncertainty. This study focuses on two distinct areas of risk. First, this study seeks to measures the farm-gate price volatility, explores farmers’ perceptions about the price volatility risk related to the input sourcing and output selling activities, and quantifies the effectiveness of price volatility risk management strategies. Second, the relationships between farm and farmer socioeconomic characteristics, perceptions about the price volatility risk and management strategies are also examined. To respond to these research questions, a focus group workshop was conducted with 29 stakeholders and a structured survey with 92 farmers located in the provinces of An Giang, Can Tho, and Dong Thap of the Vietnamese Mekong Delta. Results illustrated that the pangasius farm-gate price fluctuates significantly over time. Vietnamese pangasius farmers are mainly concerned about the volatilities of input and output prices, additionally with the instability of the volume input supply, instability in demand volume, and weak legislation on sale contracts. Results further indicate that price volatility risk management strategies are less effective in practically protecting farmers against price volatility risks. Farmers with higher education knowledge opt for fully integrated farms and are less concerned about the output price volatility risk. Promoting risk-sharing schemes such as contract farms or insurance for farmers with higher educational levels and being accessible to credit could support Vietnamese pangasius farmers toward increasing the sustainability of pangasius production.
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