Hasil untuk "Banking"

Gary B. Gorton

Allen N. Berger, A. Kashyap, J. Scalise

E. Detragiache, P. Garella, L. Guiso

Minjoon Jun, Shaohan Cai

Allen N. Berger

J. Goddard, P. Molyneux, John O. S. Wilson

B. Casu, P. Molyneux

Connor Rudy Sullivan, Amin Mamandipoor, Cole Ridge Strickler et al.

Modern multicore system-on-chips (SoCs) share off-chip DRAM across cores, where bank-level interference can significantly degrade performance and threaten real-time guarantees. While prior work has focused on per-core bandwidth regulation, these approaches treat main memory as a monolithic resource and overlook DRAM's inherent bank-level parallelism. We show that DRAM interference is fundamentally a bank-level phenomenon. We characterize the guaranteed bandwidth of modern DRAM, demonstrate that it remains effectively constant across generations, and show how this limitation can be exploited by single-bank attacks. These results highlight the need for bank-aware memory management for predictable and efficient real-time systems. We design and implement a novel per-bank memory bandwidth regulator in an open-source RISC-V SoC and evaluate it using FireSim with both synthetic and real-world workloads. Our evaluation demonstrates that per-bank regulation effectively mitigates adversarial bank contention and achieves a 5.74x average throughput improvement for best-effort workloads over traditional bank-oblivious approaches while providing the same-level of performance isolation guarantees for real-time workloads.

John-Mark Akandekumtiim, Busani Moyo

The study analyses the presence and determinants of economies of scale in Ghana's Banking sector, using 366 unbalanced annual panel data observations from 29 banks in Ghana from 2007 to 2023. A stochastic cost function was used to estimate scale economies, while the determinants of scale economies were estimated using panel regression. The study found that scale economies and technological progress are widespread across various banking groups, with an average scale elasticity of 1.15, indicating that a 100% increase in output quantities results in an average rise in total cost of only 85%, and that Ghanaian banks, on average, recorded a cost reduction of about 3.3% over the sample period due to technological progress. The results also show that factors such as net interest margin and technological progress have a positive influence on scale economies. In contrast, investment banking activities have a negative impact, while capitalisation has a non-linear inverted U-shape relationship with scale economies. The study concludes that the consolidation that occurred in Ghana's banking sector may have led to stronger banks that allow them to enjoy larger economies of scale. Nevertheless, the non-linear relationship between capitalisation and scale economies suggests that policymakers must be mindful that excessive capitalisation may eventually lower scale economies. Policymakers should also pursue policies that will encourage and facilitate the adoption of new banking technologies to improve business processes and the delivery of banking services.

Tuire Kuisma, Tommi Laukkanen, M. Hiltunen

Yan Li

The issue of local government debt is widely recognized as one of the "gray rhinos" affecting the stable development of China's economy. Government debt can transmit risks to local banks, which are among the primary holders of local debt, thereby triggering systemic financial risks. Consequently, exploring debt resolution pathways and evaluating the systematic effects of debt servicing policies has become critically important. This study employs panel data from 348 local commercial banks across 29 provincial-level administrative regions in China from 2010 to 2023, and constructs a difference-in-differences (DID) model to investigate the impact of the State Council's special supervision of debt servicing on local bank risks. The findings indicate that the government's debt servicing policy essentially represents a shift of government debt from explicit to implicit forms, significantly increasing the risks faced by local banks and producing outcomes contrary to the policy's original intent. This effect is particularly pronounced for rural commercial banks and banks with high customer concentration and fewer branches. Mechanism analysis reveals two key insights. First, local banks are heavily influenced by local government control; the government's debt servicing requires banks to support the government by purchasing government bonds and other financial instruments, which leads to a deterioration in asset quality and an expansion of risk exposure. Second, government debt crowds out private credit from local banks, weakening the region's repayment capacity and ultimately increasing bank risk. Our research uncovers the counterintuitive effects of government debt servicing and offers corresponding policy recommendations.

Abdoulaye Sakho, Emmanuel Malherbe, Carl-Erik Gauthier et al.

This study investigates rare event detection on tabular data within binary classification. Standard techniques to handle class imbalance include SMOTE, which generates synthetic samples from the minority class. However, SMOTE is intrinsically designed for continuous input variables. In fact, despite SMOTE-NC-its default extension to handle mixed features (continuous and categorical variables)-very few works propose procedures to synthesize mixed features. On the other hand, many real-world classification tasks, such as in banking sector, deal with mixed features, which have a significant impact on predictive performances. To this purpose, we introduce MGS-GRF, an oversampling strategy designed for mixed features. This method uses a kernel density estimator with locally estimated full-rank covariances to generate continuous features, while categorical ones are drawn from the original samples through a generalized random forest. Empirically, contrary to SMOTE-NC, we show that MGS-GRF exhibits two important properties: (i) the coherence i.e. the ability to only generate combinations of categorical features that are already present in the original dataset and (ii) association, i.e. the ability to preserve the dependence between continuous and categorical features. We also evaluate the predictive performances of LightGBM classifiers trained on data sets, augmented with synthetic samples from various strategies. Our comparison is performed on simulated and public real-world data sets, as well as on a private data set from a leading financial institution. We observe that synthetic procedures that have the properties of coherence and association display better predictive performances in terms of various predictive metrics (PR and ROC AUC...), with MGS-GRF being the best one. Furthermore, our method exhibits promising results for the private banking application, with development pipeline being compliant with regulatory constraints.

Tatsuru Kikuchi

I develop a nonparametric framework for identifying spatial boundaries of treatment effects without imposing parametric functional form restrictions. The method employs local linear regression with data-driven bandwidth selection to flexibly estimate spatial decay patterns and detect treatment effect boundaries. Monte Carlo simulations demonstrate that the nonparametric approach exhibits lower bias and correctly identifies the absence of boundaries when none exist, unlike parametric methods that may impose spurious spatial patterns. I apply this framework to bank branch openings during 2015--2020, matching 5,743 new branches to 5.9 million mortgage applications across 14,209 census tracts. The analysis reveals that branch proximity significantly affects loan application volume (8.5\% decline per 10 miles) but not approval rates, consistent with branches stimulating demand through local presence while credit decisions remain centralized. Examining branch survival during the digital transformation era (2010--2023), I find a non-monotonic relationship with area income: high-income areas experience more closures despite conventional wisdom. This counterintuitive pattern reflects strategic consolidation of redundant branches in over-banked wealthy urban areas rather than discrimination against poor neighborhoods. Controlling for branch density, urbanization, and competition, the direct income effect diminishes substantially, with branch density emerging as the primary determinant of survival. These findings demonstrate the necessity of flexible nonparametric methods for detecting complex spatial patterns that parametric models would miss, and challenge simplistic narratives about banking deserts by revealing the organizational complexity underlying spatial consolidation decisions.

Rani Putri Yasmin, Kartono Kartono, Edy Hartono

In the corporate world, it is the obligation of every employee to meet the targets set by the company, in practice there are many factors that support the good or bad performance of an employee in completing the goals set by the company. In Bank Syariah Indonesia, especially the frontliner, which is the vanguard in banking services, is also the vanguard in the company's business, it is certainly a challenge in running services and selling the company's business. Especially in the world of Islamic banking in carrying out business and service aspects, it is supported by many factors, including the existence of an organizational culture that serves as a guideline for employees to harmonize the same in culture and organization. Another factor in improving or decreasing employee performance in the company is inseparable from the factors of superiors or leaders of each supervision. To create achievement motivation that can encourage every employee to complete the targets given by the company. The method applied in this research is quantitative, which indicates that this research is causal in nature, where the researcher aims to analyze and describe the cause-and-effect relationship or mutual influence relationship between the variables studied. The number of samples used from the overall population was 100 respondents using a questionnaire with a linkert scale of 1-5 Statistical tests were used to assess the significance of regression results and to measure the strength of the relationship between each variable studied. This data management focuses on the security of the data of the respondents. In this study, it is known that the overall variables studied, namely organizational culture, leadership function and employee performance mediated by achievement motivation in Islamic banking in the Bandung region have a significant impact on each other. Employee performance in each employee of the company has the influence of the variables that have been studied.

Hung-Yi Wu, G. Tzeng, Yi-Hsuan Chen

Louis H. Marting, Kenichi Karatsu, Akira Endo et al.

Many superconducting on-chip filter-banks suffer from poor coupling to the detectors behind each filter. This is a problem intrinsic to the commonly used half wavelength filter, which has a maximum theoretical coupling of 50 %. In this paper we introduce a phase coherent filter, called a directional filter, which has a theoretical coupling of 100 %. In order to to study and compare different types of filter-banks, we first analyze the measured filter frequency scatter, losses, and spectral resolution of a DESHIMA 2.0 filter-bank chip. Based on measured fabrication tolerances and losses, we adapt the input parameters for our circuit simulations, quantitatively reproducing the measurements. We find that the frequency scatter is caused by nanometer-scale line-width variations and that variances in the spectral resolution is caused by losses in the dielectric only. Finally, we include these realistic parameters in a full filter-bank model and simulate a wide range of spectral resolutions and oversampling values. For all cases the directional filter-bank has significantly higher coupling to the detectors than the half-wave resonator filter-bank. The directional filter eliminates the need to use oversampling as a method to improve the total efficiency, instead capturing nearly all the power remaining after dielectric losses.

Teng Liu

The agricultural sector is particularly susceptible to the impact of climate change. In this paper, I investigate how vulnerability to climate change affects U.S. farms' credit access, and demonstrates that such impact is unequally distributed across farms. I first construct a theoretical framework of bank lending to farms faced with climate risks, and the model helps discipline ensuing empirical analyses that use novel panel datasets at county and at bank levels. I find that higher exposure to climate change, measured by temperature anomaly, reduces bank lending to farms. Such impact is persistent, nonlinear, and heterogeneous. Small and medium farms almost always experience loss of loan access. In comparison, large farms see less severe credit contraction, and in some cases may even see improvement in funding. While small banks carry the burden of continuing to lend to small farms, their limited market share cannot compensate for the reduction of lending from medium and large banks. These results suggest that factors such as farm size and bank type can amplify the financial impact of climate change.

Rahman Aulia Fuad, Agusti Rosalita Rachma, Kurniawati Desi Tri

The mounting environmental concerns have become a pressing issue across industries. Nevertheless, the banking sector has a distinct influence in shaping economic growth and development. This study sought to evaluate the impact of green banking in strengthening corporate value through its level of sustainability reporting in order to address these concerns. A research framework was developed based on theoretical support. The sampled data was collected from banks listed on the Indonesian Stock Exchange from 2018-2021. An empirical analysis was performed through hierarchical regression. The study’s findings indicated that green banking positively and significantly impacts firm value. Furthermore, there is a mediating effect between green banking and business value due to the quality of sustainability reporting. The empirical test revealed that the quality of sustainability reporting has a mediating effect to some extent. The results also showed that there is an interaction between business size (assets) and correlations between firm value and green banking. By undertaking a data-driven research that explains the impact of green banking on business value, this study aims to fill a significant gap in the body of knowledge on green banking and sustainability reporting.

C. Goodhart

Shirshendu Ganguli, S. Roy