Deep Neural Networks for Financial Transaction Risk Reduction in SMEs

The credit risk of an applicant is the major consideration that financial institutions look at when deciding whether to accept an application for factoring. The effect that blockchain technology has on credit risk should be given the utmost consideration in the decision-making process of financial institutions because it is of the biggest importance. This paper presents a case study of a small and medium-sized enterprise (SME) that satisfies the requirements of an incentive compatibility mechanism. The results show that the incentive subsidy that is provided by an incentive-compatible mechanism has a negative correlation with the effort level coefficient, the absolute risk aversion coefficient, and the external uncertainty of SMEs, while it has an effect on the maturity of its BCT and the operational capability of SME in a setting that is informationally symmetric and constrained by the goal of maximising the expected returns for all parties. When it comes to differentiating between different types of SMEs that have different capacities for their operations and providing different incentives for SME, the differential incentives with asymmetric information are more effective than the equal incentives. However, the effect of blockchain technology on the credit risk is the biggest consideration that the SCF must deal with that in order to find the better solution.