Financial Services Authority

The aim of the paper is to explore the accounting challenges faced by Fintech in Indonesia. Specifically, on how the implementation of IFRS 15 Revenue from Contract with Customers to the P2P Lending business model. This exploratory study employs qualitative research method. The data for this study was derived from the focus group discussions (FGD) with P2P Lending top management and industry regulator. Two discussions were held and there were 44 Participants in the discussions which represent 8 P2P Lending entities. This paper finds that the challenges to apply IFRS 15 consistently mostly because there are differences among P2P Lending practitioners on the notion of performance obligation in providing the service. Despite similar business model, the understanding of performance obligation in IFRS 15 varies among P2P Lending practitioners. This paper contributes to the literature of fintech which currently lack of investigation on how fintech operation is mapped in to relevant IFRS. This paper also offers recommendation to the regulator on how to improve the comparability of P2P Lending financial reporting by clarifying the regulation and improving the accounting policies. This is the first paper we are aware of to look in to the accounting aspect of the fintech P2P Lending.

This paper shows evidence of a dramatic change in the structure and time-varying patterns of volatility connectedness between Indonesian and global stock market volatility during the COVID-19 outbreak. The Diebold-Yilmaz volatility spillover. The dynamic total connectedness across the stock market was moderate and relatively stable until early 2020. After that, the real connectedness spikes, and the direction of connectedness alters, which concurs with the COVID-19 outbreak. DJIA and EURO indices were the primary transmitters of shocks before the pandemic, whereas JKSE became the primary transmitter of shocks during the COVID-19 pandemic. Even though JKSE was a robust transmitter during the COVID-19 outbreak, the connection with DJIA warrants close and regular observation due to the very high spillover. The COVID-19 episode had immediate and unsettling impacts, which are essential for formulating policies to achieve financial stability. The findings are also very important not only for investors but also for policymakers.

This paper provides a comparative analysis of global regulatory frameworks governing digital assets, emphasizing legal definitions, classifications, and jurisdictional approaches. Digital assets—defined as cryptographically secured digital representations of value—are categorized into cryptocurrencies, utility tokens, security tokens, stablecoins, NFTs, and CBDCs. The study examines regulatory regimes in the United States, European Union, Hong Kong SAR (China), Japan, and Singapore, highlighting varying degrees of regulatory fragmentation, harmonization, and innovation support. Key regulatory goals include transparency, fraud prevention, AML/KYC compliance, consumer protection, and international coordination. The paper concludes with policy recommendations aimed at enhancing global cooperation, regulatory clarity, and consumer education, while acknowledging challenges such as jurisdictional divergence and resource limitations in developing nations.

Implementing distributed cloud-based applications commonly at the basis of user-facing services goes through several challenges. In particular, such applications must be scalable to accommodate increasingly large user bases, providing consistency on accesses to shared data while executing on highly distributed concurrent commodity hardware. In addition, as these applications are subject to workload fluctuations, they must be elastic , i.e., able to scale out to accommodate workload increases as well as to scale back in to avoid over-provisioning and thus unnecessarily high costs in case of workload decreases. This paper presents AEON, a programming framework that supports the development of scalable elastic cloud-based distributed applications. In short AEON leverages two synergistic “levels” of programming: I. An application programming language (APL) allows programmers to conceive scalable applications using the popular actor paradigm, augmented with an intuitive notion of event to capture non-interleaved executions across multiple actors as needed for non-trivial shared data, all the while avoiding error-prone manual concurrency control. That is, based on a simple type-based ownership analysis asserting that references in AEON applications follow a DAG-based referencing structure, events are executed efficiently in a serializable fashion leveraging a lightweight synchronization protocol which is also exploited for creating consistent snapshots of the distributed application’s shared data. II. An elasticity programming language (EPL) allows application managers to define policies for guiding efficient fine-grained automated scaling — in and out — of applications at runtime. While these policies refer to applications written with I, they only refer to high-level abstractions in those (e.g., types of actors and methods), are inversely not referred to by them, and avoid side-effects to minimize effects on application performance. After presenting our programming framework with its language design choices and runtime system implementation, we present a study applying it to several use cases, and evaluate its performance. In short, our APL’s synchronization model scales better than manual locking or the use of automated traditional two-phase locking with existing actor languages, or the use of an external transactional store; under workload fluctuations our EPL allows programs to be executed with significantly improved performance without increased resource usage, or with similar performance but significantly fewer resources.