Since the revision of the MLBL in Japan in 2006, Yamikin-related crimes seem to have subsided in the lending market. However, according to the media reports of those incidents, while the number of cases in which police have detected Yamikin has remained constant, recent Yamikin-criminals have evolved the business model more wisely to escape detection.

Under this circumstance, COVID-19 pandemic has led the global economy to shrink since this March, and the Japanese economy suddenly deteriorated. The media also reported that the damage caused by illegal financial transactions appeared to be increasing under the economic conditions in COVID-19 pandemic.

Therefore, in COVID-19 pandemic, we have focused on the two illegal financial services, bilateral factoring service and inter-personal lending service on SNS and examined these actual lending transactions. The result of analysis suggested that bilateral factoring for small and medium-sized enterprises has reduced the number of transactions, while inter-personal lending on SNS has seemed to be proliferated since this May, shortly after Japan’s economic started to resume.

The market of Chinese P2P Lending has rapidly grown in the last ten years. We use transaction records of RRD, which is one of the leading platforms in Chinese P2P Lending, to analyze the financial discrimination in this market. Using the non-financial characteristics of borrowers, including five variables――gender, age, educational background, marital status, and working location, we estimate the funding rate, default rate, and return rate of the loan securities. Different from standard economics, the estimation results of these variables are significant, which means that non-financial characteristics are as important as financial ones for lenders. Moreover, we find that the discrimination regarding gender, marital status, and working location is rational statistical discrimination, while discrimination on age is irrational taste-based discrimination.

Artificial intelligence is expected to be important driver of future innovation in many industries,but the use of big data is a prerequisite for its success. The reason why it is possible to develop creditbusiness using artificial intelligence in China is that it effectively uses a huge amount of data that cannotbe compared with Japan.

Alibaba Group, a leader in China's FinTech industry, is drawing attention for its efforts in the field of personal finance utilizing the big data. Alibaba Group's ability to utilize big data is largely due to its ability to collect and link vast amounts of data in Alibaba's e-commerce and its platforms.

China's advanced FinTech ecosystem in the field of personal finance captures not only electronic payment information, but also personal data in logistics and commercial distribution, such as various digital footprints and transaction histories of users. They use artificial intelligence to evaluate credit in real time and use the scoring for lending and various non-financial services.

In addition to the interests of latecomers who do not have legacy systems, Chinese IT companies have the potential to take advantage of the world's largest big data usage environment to upgrade retail financial services to the world's most advanced level.

The P2P lending suffered a big bankruptcy rush in mid-2018 in China. Prior studies explaining the reasons can be divided into external factor theory and market failure theory. The former is attributed to tight monetary policies, economic recession, and the tightening of regulations. The latter is attributed to information asymmetry and investor bias. We propose an internal factor theory that is different from prior studies. Chinese P2P lending platforms were forced to pursue scale expansion with significant risks (full guarantee risk and disclosure risk), which can cause platform bankruptcy, because the platform has a special characteristic: a financial company while being an IT company. Since this characteristic, platforms, entering the P2P lending market, are in the situation of“ prisoner's dilemma of the arms race” and are forced to scale up to monopolize the market. In other words, the reason for the bankruptcy rush is the same reason for the rapid growth of the P2P lending market. Risks that had been postponed for the expansion of scale come to the surface as the deterioration of the external environment. In short, the occurrence of the bankruptcy rush was already inevitable at the same time as the rapid growth of the P2P lending market.