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.
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.
Financial constraints and risk taking are two well-established determinants of firm performance, however, no research analyzes how these variables are connected in the context of a high risk environment. Using data from microfinance clients in Tanzania, we derive a novel financial constraints measure and incorporate a psychometric risk taking scale. Results confirm the importance of access to finance and risk attitudes for business development. Also, we provide preliminary evidence for an interaction between financial constraints and risk taking. Financial constraints “throw sand in the wheels” and protect risk taking entrepreneurs from the negative impact of risk taking on microenterprise performance.
