Hasil untuk "Banking"

Michael L. Smirlock

Yener Altunbaş, E. Gardener, P. Molyneux et al.

C. Jayawardhena, P. Foley

Heikki Karjaluoto, Minna Mattila, T. Pento

Helmut Elsinger, Alfred Lehar

I. Isik, M. Hassan

André Uhde, Ulrich Heimeshoff

Thi Thuy Hang Le

This study uses a PVAR model to analyze the impact of non-cash payments and legal institutions on corruption levels in ASEAN-5 and Vietnam during the period 1996–2022. Illegal transactions for corruption often take advantage of anonymity, mainly avoiding the banking system and using cash to avoid leaving traces. Therefore, the prevalence of cash in the economy can be an important factor affecting corruption, emphasizing the role of the central bank in restricting large-value cash to control corruption. The study provides empirical evidence on two aspects: the impact of non-cash payments on corruption in ASEAN-5 and Vietnam, as well as the relationship between legal institutions, administrative development and corruption. The results identify causal relationships between the rule of law index (RLI), institutional quality (RQI), online transaction value (IUP), mobile transactions (MB) and corruption index (CPI). These effects persist over time. Specifically, fluctuations in online transaction value affect the corruption index by about 8% from the third period, while mobile transactions affect the corruption index by about 2%. These effects are statistically significant and persistent.

Pierre Gosselin, Aïleen Lotz

In a previous paper, we applied a field formalism to analyze capital allocation and accumulation within a microeconomic framework of investors and firms. The financial connections were modeled by a field of stakes, representing the links between agents. We showed that the resulting collective states were composed of interconnected groups of agents defined by their connections, their returns and disposable capital. However, within this framework, the collective states exhibited structural instability, as capital shortages in specific sectors could trigger cascades of defaults. The present model refines this framework by introducing a third type of agent, banks, a type of investor that can create money through loans. We show that money creation neither eliminates systemic instability nor prevents the emergence of defaults. In fact, the effect of banks on system stability and defaults is ambiguous: When banks favor firms over investors, money creation stabilizes the system by providing the necessary capital to prevent initial defaults, whereas when banks favor investors over firms, investors' influence is strengthened, potentially amplifying instability and defaults. Moreover, regardless of whether they favor investors or firms, banks may facilitate the propagation of defaults once they have started. Ultimately, because banks are themselves investors, the emergence of highly capitalized, high-return banks can directly generate instability in the system. Beyond these mechanisms, the analysis reveals the structural limits of macroprudential regulation. Highly capitalized, high-return investors and banks may appear more diversified and resilient, yet they constitute the primary source of endogenous instability. The model thus highlights that systemic fragility is inherent to the very structure of financial interdependence and capital flows.

Gary B. Gorton, Andrew Metrick

J. Puschel, J. Mazzon, J. M. C. Hernandez

Alphonse Mefoute Badiang, Emile Saker Nkwei

AbstractThis study examines the antecedents of Mobile banking (M-banking) app adoption, explores post-adoption effects, and tests the moderating effect of consumer status orientation on the relationship between adoption intention and its consequences. The conceptual model hypothesized 20 relationships, including 10 moderations. Hypotheses are tested using the structural equation modeling method (PLS-SEM) on a sample of 509 individuals. The results reveal that the main variables of ‘users’ rational perception, namely behavioral control and terminal security, significantly influence the intention to adopt the application, which in turn impact relationship quality and financial inclusion. However, hedonic expectations do not have a significant impact on the intention to adopt the application; the impact of culture in these relationships is further established; indeed, traditional and modern values moderate the impact of the intention to adopt the application on key post-adoption factors, financial inclusion, and relationship quality. The main recommendations and limitations of the research are discussed.

Junbao Zhou, Ziqi Pang, Yu-Xiong Wang

With recent video object segmentation (VOS) benchmarks evolving to challenging scenarios, we revisit a simple but overlooked strategy: restricting the size of memory banks. This diverges from the prevalent practice of expanding memory banks to accommodate extensive historical information. Our specially designed "memory deciphering" study offers a pivotal insight underpinning such a strategy: expanding memory banks, while seemingly beneficial, actually increases the difficulty for VOS modules to decode relevant features due to the confusion from redundant information. By restricting memory banks to a limited number of essential frames, we achieve a notable improvement in VOS accuracy. This process balances the importance and freshness of frames to maintain an informative memory bank within a bounded capacity. Additionally, restricted memory banks reduce the training-inference discrepancy in memory lengths compared with continuous expansion. This fosters new opportunities in temporal reasoning and enables us to introduce the previously overlooked "temporal positional embedding." Finally, our insights are embodied in "RMem" ("R" for restricted), a simple yet effective VOS modification that excels at challenging VOS scenarios and establishes new state of the art for object state changes (on the VOST dataset) and long videos (on the Long Videos dataset). Our code and demo are available at https://restricted-memory.github.io/.

Connor Sullivan, Alex Manley, Mohammad Alian et al.

Modern commercial-off-the-shelf (COTS) multicore processors have advanced memory hierarchies that enhance memory-level parallelism (MLP), which is crucial for high performance. To support high MLP, shared last-level caches (LLCs) are divided into multiple banks, allowing parallel access. However, uneven distribution of cache requests from the cores, especially when requests from multiple cores are concentrated on a single bank, can result in significant contention affecting all cores that access the cache. Such cache bank contention can even be maliciously induced -- known as cache bank-aware denial-of-service (DoS) attacks -- in order to jeopardize the system's timing predictability. In this paper, we propose a per-bank bandwidth regulation approach for multi-banked shared LLC based multicore real-time systems. By regulating bandwidth on a per-bank basis, the approach aims to prevent unnecessary throttling of cache accesses to non-contended banks, thus improving overall performance (throughput) without compromising isolation benefits of throttling. We implement our approach on a RISC-V system-on-chip (SoC) platform using FireSim and evaluate extensively using both synthetic and real-world workloads. Our evaluation results show that the proposed per-bank regulation approach effectively protects real-time tasks from co-running cache bank-aware DoS attacks, and offers up to a 3.66$\times$ performance improvement for the throttled benign best-effort tasks compared to prior bank-oblivious bandwidth throttling approaches.

Abhishek Trivedi, Sourajit Mukherjee, Rajat Kumar Singh et al.

Extraction of transaction information from bank statements is required to assess one's financial well-being for credit rating and underwriting decisions. Unlike other financial documents such as tax forms or financial statements, extracting the transaction descriptions from bank statements can provide a comprehensive and recent view into the cash flows and spending patterns. With multiple variations in layout and templates across several banks, extracting transactional level information from different table categories is an arduous task. Existing table structure recognition approaches produce sub optimal results for long, complex tables and are unable to capture all transactions accurately. This paper proposes TabSniper, a novel approach for efficient table detection, categorization and structure recognition from bank statements. The pipeline starts with detecting and categorizing tables of interest from the bank statements. The extracted table regions are then processed by the table structure recognition model followed by a post-processing module to transform the transactional data into a structured and standardised format. The detection and structure recognition architectures are based on DETR, fine-tuned with diverse bank statements along with additional feature enhancements. Results on challenging datasets demonstrate that TabSniper outperforms strong baselines and produces high-quality extraction of transaction information from bank and other financial documents across multiple layouts and templates.

Makan Rafiee, Lars Hupel

Central Bank Digital Currency (CBDC) is a new form of money, issued by a country's or region's central bank, that can be used for a variety of payment scenarios. Depending on its concrete implementation, there are many participants in a production CBDC ecosystem, including the central bank, commercial banks, merchants, individuals, and wallet providers. There is a need for robust and scalable Public Key Infrastructure (PKI) for CBDC to ensure the continued trust of all entities in the system. This paper discusses the criteria that should flow into the design of a PKI and proposes a certificate hierarchy, together with a rollover concept ensuring continuous operation of the system. We further consider several peculiarities, such as the circulation of offline-capable hardware wallets.

Rawa Saman Maaroof, Shamazad Rahim, Shahla Othman Salih et al.

In this paper we have 623 cases of diabetes patients, the data partitioned in to training dataset (500 observations) and testing dataset (123 observations), and the aim is to estimate the impact of pregnancy duration in weeks, systolic and age as factors on diabetes of the women patients for this purpose SVR has been used. According to the results radial kernel function gave highest performance compared to the other kernel functions, the R2 = 83% this implies the factors capable of explaining 83% of diabetes variable with MSE and RMSE of (0.000958 and 0.030956) respectively. And p-values of the three aforementioned variables are less than the significant level of 0.01, implying that the three factors have a statistically significant impact on the response variable. Where Pregnancy duration in weeks has an impact of 0.401 on the patient, that means if duration increase by one week, then diabetes will increase by 0.401 units, also both Systolic and age have a significant positive effect on the response variable, and the amount of impact is (0.621 and 0.557) respectively.

Jacob Yarassoula YARABATIOULA, Kiswendsida Paul Ismaël NANA

Since the 1950s, Artificial Intelligence (AI) has been used in virtually every field of activity, ranging from sectors such as health to agriculture, banking, finance, armaments, etc. Thus, the Cultural and Creative Industries (CCI) are not on the sidelines. This ICC-IA filiation has grown over the years in advanced ecosystems such as the Americas, Europe and even Asia. In light of the revolutions they generate, the uses of Artificial Intelligence in the Burkinabe cultural and creative industries are grounds for several apprehensions and questions. This article aims to immerse ourselves in the relationship between Artificial Intelligence and Cultural and Creative Industries in Burkina Faso, which is marked by upheavals in the processes of actors in the links of the different value chains, resistance on the part of conservative actors, socio-political, economic, technical-artistic issues as well as many challenges to be met.

Seyed Safdar Hosseini, Hassan Mafee, Seyed Fakhreddin Fakhrhosseini

Purpose: Nowadays, one of the multifaceted topics in monetary and banking studies is using the finance of banks and credit institutions. Correctly using finance tools can significantly affect the development of financial markets and economic growth. This article prioritizes available Islamic finance ways, policies, and strategies at Ayandeh Bank.Methodology: This study prioritizes 12 Islamic banks' finance ways by focusing on three criteria of attractiveness and efficiency of the financing method (demand-side acceptance commitments), executive capacities (supply-side institutional compatibility commitments), and macro-environment (bank macro environment). In addition, 30 experts in the field of investment and finance have been collected at Ayandeh Bank. The study also uses the AHP approach.Findings: The results show that foreign currency and Rial deposits have the highest priority, and buying and selling debts, securities, guarantees, and agencies have the lowest priority. Ultimately, a competitive strategy model with the SWOT methodology is proposed for the Islamic finance of Ayandeh Bank to synchronize Ayandeh Bank policies with Iran's business cycles.Originality/Value: Due to prioritizing Islamic financing methods in Ayandeh Bank, these results help bank managers make more appropriate decisions to achieve the bank's goals. Furthermore, the proposed competitive strategy model for Islamic financing provides a suitable model for their plans for synchronizing the bank's policies with Iran's business cycles.

Yueyang Zhang

It is known that a Bank-Laine function $E$ is a product of two normalized solutions of the second order differential equation $f"+Af=0$ $(\dagger)$, where $A=A(z)$ is an entire function. By using Bergweiler and Eremenko's method of constructing transcendental entire function $A(z)$ by gluing certain meromorphic functions with infinitely many times, we show that, for each $λ\in[1,\infty)$ and each $δ\in[0,1]$, there exists a Bank--Laine function $E$ such that $E=f_1f_2$ with $f_1$ and $f_2$ being two entire functions such that $λ(f_1)=δλ$ and $λ(f_2)=λ$, respectively. We actually provide a simpler construction of the special Bank--Laine functions given by Bergweiler and Eremenko.