No abstract

Digital transformation creates challenges in all industries and business sectors. The development of digital transformation has also clearly triggered the emergence of fintech (financial technology) initiatives, which are recognized as some of the most important innovations in the financial industry. These initiatives are developing rapidly, driven in part by the sharing economy, regulations, and information technology. However, research in the field of fintech remains in its infancy. Fintech offers several services, such as funding, payment (including electronic wallets), e-aggregators, e-trading, and e-insurance, and cryptocurrencies such as Bitcoin. This provides an opportunity to more closely examine fintech’s research challenges and trends. This study aims to (1) determine the state of the art of financial technology research; (2) identify gaps in the financial technology research field; and (3) identify challenges and trends for future research potential. The novel proposal in this study includes theoretical contributions regarding financial technology. Using the systematic literature review approach of Kitchenham, in addition to thematic analysis, meta-analysis and observation to validate the quality of literature and analysis, the results of this study provide a theoretical basis fintech research from an information systems perspective, including the formulation of fintech technology concepts and their development.

Financial technology (fintech) is a growing industry in Indonesia, supported by advances in the technological infrastructure. At the end of 2019, the Financial Services Authority (OJK), the financial authority in Indonesia, recorded 164 registered and licensed fintech (P2P lending) companies. However, since early 2018, the Investment Alert Task Force (SWI) and the Ministry of Communication and Information Technology have blocked 1,350 illegal fintech platforms. Illegal fintech lending practices have mechanisms beyond the responsibility and authority of the OJK, including the risk of collection and distribution of personal data. The essence of this study is to discuss the landscape of fintech P2P lending in Indonesia from Indonesian Online News data, explore cases of fintech p2p lending in Indonesia, and understand the rules and policies. Qualitative research with a case study approach and Focus Group Discussion techniques were used to obtain data from 4 stakeholders in the Fintech P2P Lending Industry in Indonesia. VOS Viewer software is used to build keywords from Indonesian Online News collections, NVIVO 12 qualitative software is used to assist data analysis. The research found the keyword clusters most frequently discussed in the Indonesian Online News collection and five case themes such as public awareness about P2P lending (user understanding), data leakage, and restriction of data access, including personal data protection, personal data fraud, illegal fintech lending, and Product marketing ethics.

No abstract

Open data is a flagship initiative in open government program to increase transparency, social and commercial value, and participatory governance. Open data is a relatively new field and the factors affecting its continuance use by citizen has not been widely studied. A better understanding of these factors can help government to formulate policies and strategies that can improve the acceptance and use of open data website. The research model is based on the Theory of Planned Behavior and integrated with the technology quality and trust factors. Data collection was conducted using questionnaire. Structural Equation Modeling (SEM) was used to test the research model. The results show that attitude, subjective norm, perceived behavioral control and trust directly affect continuance intention to use open data website. Systems quality affects perceived ease of use, while information quality positively affects perceived usefulness, perceived ease of use, and trust. Both perceived usefulness and perceived ease of use affect user's attitude. The analysis of this study suggests that each influencing factor provides implications for government to stimulate the continuance use of open data website.