The objective of this research is for describing the key role of financial (FinTech) regulation to manage the risks, keep-up the balance and stability of FinTech ecosystem from the highest impact of risks’ in this industry. FinTech lending has grown rapidly in recent years in many countries and becomes a promising business model in the future, because it is a disruptive innovation to today's financial and banking markets. The rapid development of FinTech lending due to the use of internet-based mobile application platforms, so that it is easily accessible by anyone and anywhere, it encourages an increase in lending to the customers, however credit risk (although absorbed by lenders or investors, still indirectly affects the platform operators), experienced an increase due to non performing loan or NPL. The increase in NPL is an important concern for FinTech lending industry stakeholders, and if it is not addressed it will disrupt the FinTech ecosystem, let alone cause systemic risk, it will be the toughest disturbance in the stability of the FinTech ecosystem, considering that the risk of FinTech lending has a significant influence on the FinTech ecosystem, so that if the level of risk increases, it affects the FinTech ecosystem, this condition requires the key role of financial (FinTech) regulation that can mitigate risk, because financial (FinTech) regulation has a very strong correlation or relationship, so that it can mitigate the risks faced. Another key role of financial (FinTech) regulation is to strengthen the FinTech ecosystem, with new elements needed by the industry and encourage the industry to develop the concept of ecosystem-based risk management in this industry, because it is believed that this concept can mitigate risk as well. Fundamental risks in the FinTech lending industry include: (i) credit risk, (ii) operational risk and (iii) liquidity risk, meanwhile pandemic risk is a new element that is also being investigated, the results of the study show that pandemic risk has a positive correlation with start-up FinTech companies, this means that a pandemic still allows this industry to develop and grow. Financial (FinTech) regulation as a key role is supported by 2 (two) main rules, namely (i) regulatory and (ii) supervisory and 2 (two) complementary provisions to strengthen regulations related to IT process support, namely big data analytics, automation & robotics and FinTech consumer protection agency. The FinTech ecosystem also needs to be strengthened, with new elements needed to exist, such as credit insurance institutions that stand alone and are separated from traditional financial institution element and FinTech consumer protection agency.

The purpose of this research for analyzing the affect and correlation risk to the fintech ecosystem on the P2P lending industry in Indonesia with the quantitative approach and using the analysis tools of SEM-Amos. The result is shown that risk has an affect and correlation significantly to the fintech ecosystem, it can prove that the risk changing has affect to fintech ecosystem stability. The key of activity on this industry is loan disbursement so the potential risk will come up is NPL (non-performing loan), which can cause credit risk. Credit risk can be mitigated by doing customer segmentation precisely. Mitigation is done by other risks, namely, operation, market, liquidity, legal, strategic, and pandemic risk-covid 19. Pandemic risk-covid 19 is an additional risk and positively correlates to start-up fintech elements. It is proof that the existence of pandemic-covid 19, the business of this industry is still running well and has no effect on it, causing this industry to use the mobile application and the transactions without meetings and still keep up social distancing. Another anticipation of empowering the fintech ecosystem by doing cooperation, coordination and collaboration between elements each other. This industry needs to add 2 (two) fintech ecosystem elements, they are credit insurance institutions and fintech consumer protection agency for anticipating the industry's need in the future.

This study uses a quantitative-descriptive approach, with SPSS 22 analysis tool to test the model. This study was conducted to analyze the significance of the influence of holistic marketing mix variables, namely product, price, promotion, place people, process, program and performance on customer loyalty savings. Holistic marketing mix variables have a significant effect on customer loyalty savings, namely: product, price, people and performance, while the variables that have no significant effect are: promotion, place, process and program. The coefficient of determination or R is 0.955, this indicates that the holistic marketing mix is ​​able to affect customer loyalty savings by 95.50% of which 4.50% is influenced by other variables not examined. Banks can focus on 4 (four) significant variables by improving the performance of product, price, people and performance variables, namely in terms of making strategies, business plans and work programs to increase savings customer loyalty, so as to increase benefits and profits for banks both for the time being. this time and in the future, meanwhile, banks can improve the performance of promotion, place, process and program, so that they can contribute positively to savings performance.

This quantitative study aims to analyze the significant effect of the application of the canvasing business model on risk. The data were analysed using structural equation modeling (SEM) on 100 respondents through the distribution of questionnaires. In addition, interviews were also conducted with several P2P lending fintech stakeholders to obtain an in-depth analysis of the problem. The result showed that the canvasing business model variable has a significant effect on risk with an estimate of 0.871. The P2P lending fintech industry has an inherent risk, namely credit risk and there are 7(seven) components of the canvasing business model (CBM) that have a correlation to credit risk and the risk of the COVID-19 pandemic. Credit risk due to NPL caused by unbanked and underserved can be mitigated by implementing the CBM components and the customer segments. The application of customer segments and keys of partnership can mitigate fraudster. Over debt can be mitigated by the application of a key of partnership. Meanwhile, the risk of pandemic-covid 19 is one type of risk that is added for research in addition to 8 (eight) types of risk, which can be mitigated by implement-ing one component or element of CBM. CBM is a channel, by utilizing e-channels, through the use and use of mobile applications.