Bank Information Research Articles

Information effects of monetary policy announcements on oil price

If the information held by the central bank is different from that of market participants, then the central bank’s announcement not only affects the view of monetary policy but also the view of economic fundamentals. This study investigates the information effects of monetary policy announcements on oil prices using a structural vector autoregression (VAR) model identified by sign restrictions. The sign restrictions rely on the high-frequency linkage between stock prices and interest rates surrounding the policy announcements. We find that a positive central bank information shock, which raises the interest rate by six basis points, leads to a 1.7% increase in oil prices within two months. We also find that central bank information shocks affect oil prices through the finance and expectation channels.

Learning by Sharing: Monetary Policy and Common Knowledge

A common view states that central bank releases decrease central banks' own information about the economy and are harmful if about inefficient disturbances, such as cost-push shocks. This paper shows how neither is true in a microfounded macroeconomic model in which households and firms learn from central bank releases and the central bank learns from the observation of firm prices. Central bank releases make private sector and central bank expectations closer to common knowledge. This helps transmit dispersed information between the private sector and the central bank. As a result, the release of additional central bank information decreases the central bank's own uncertainty and can be beneficial, irrespective of the efficacy of macroeconomic fluctuations. A calibrated example suggests that the benefits of disclosure are substantial. (JEL D82, D83, D84, E12, E52, E58)

HOW CAN BLOCKCHAIN REVOLUTIONIZE THE JORDANIAN BANKING SECTOR?

This article aims to explore blockchain, its applications, and its impact on banks in Jordan. The potential applications and improvements that blockchain might bring to the financial industry are astounding. Specifically, this study discussed the importance and possible areas of deploying blockchain technology in the banking sector of an emerging country with a fast-growing economy, namely Jordan, for different reasons. First, due to the shrinking interest-rate spread, Jordan's financial sector lacks long-term lending and unsecured loans. Second, many economic revolutions, such as the internet and banking innovations, have impacted the Jordanian banking sector. As a result, the banking sector must undergo significant transformation to increase performance and attain new levels of growth. Third, the underlying technology in clearing payment and credit bank information systems could be revolutionized by blockchains. Fourth, blockchain applications facilitate "obtain credit, unsecured loans" scenarios, improving banking efficiency. Finally, while blockchain has much appeal because it allows free and self-governing transfers, overall regulation and security for this decentralized system are still being created and agreed upon. We argue that for blockchain to change Jordan's financial system, legal frameworks must be in place to control banking transactions. This study explores the technology of blockchain, the emerging technology that powers Bitcoin and other cryptocurrencies. It highlights the features of the blockchain and shows why it could profoundly influence the entire banking sector in areas ranging from payments to settlements and identity services.

Central bank information and private‐sector expectations

AbstractRecent advances in the literature allow disentangling the pure information component from the interest rate component of US monetary policy surprises. This article quantifies the information revealed around FOMC announcements using forecast revisions from Blue Chip Economic Indicators. Following a typical central bank information shock, survey participants revise their now‐ and short‐term forecasts of both real GDP growth and the GDP deflator upwards, consistent with a shift of the aggregate demand curve along the aggregate supply curve. While now‐ and forecast revisions in real GDP growth are driven by negative central bank information shocks, those in the GDP deflator respond broadly symmetrically to good and bad news.

Inklusi Keuangan pada Industri Kreatif Berskala Mikro Kecil dalam Pengembangan Wilayah Masyarakat Pedesaan di Kota Binjai Provinsi Sumatera Utara

Limited access to finance is a major obstacle in the development of an area, especially rural communities. This study aims to analyze financial inclusion in the Micro Small-Scale Creative Industry towards the development of rural communities in Binjai City. This research uses a qualitative research approach with a case study method. Furthermore, a series of observations and interviews were conducted on the informants through a purposive sampling technique which was further developed through the snowball sampling technique. The results of the study inform that financial inclusion in micro-small-scale creative industries that are managed that are less educated, small-scale, have limited assets and are located in rural areas tend to have limited financing information as well as major obstacles so that the development of rural communities does not increase. The diversity of regional characteristics such as internet access and the use of financial inclusion in the creative industry, especially in obtaining banking information, alternative sources of financing that are more diverse can encourage improvements in the development of rural community areas in Binjai City. This study recommends the importance of education through training and mentoring as well as the use of the internet for Micro Small Scale Creative Industry entrepreneurs in rural Binjai City.

Distance, information and bank lending in China

This study aims to examine whether branch-firm distance, branch-headquarter distance and local bank competition affect bank lending in China. By incorporating loan transactions and geographic information of banks and firms, this study applies a three-way regression analysis among listed firms in China. Both branch-firm and branch-headquarter distances are found significantly decreasing loan amount, by increasing information cost and cutting off soft information. The demand for soft information reduces loan credit, which is more salient among samples of Big 4 banks. The above pattern is also found more apparent for inter-province loans, where branch is collecting information at a relatively higher cost and lack of soft information. Additionally, distant loans are also found vulnerable to credit reduction of banks. This study also finds that the bank branch facing greater local competition would issue greater amount of loans to borrowing firms. The major academic contribution of this paper is the innovative measure of soft information demand as the distance between bank branch and its headquarter, which highlights the study on soft information and helps clarify issues on bank loans in China.

Information effects of euro area monetary policy

This paper provides evidence for central bank information effects in the euro area. ECB announcements seem to convey information not only about monetary policy, but also about economic fundamentals. I separate these “information surprises” from “pure policy surprises” via sign restrictions and find intuitive effects of both surprise on a wide set of financial market prices, survey expectations and macroeconomic aggregates. Both surprise series are updated and made publicly available.

A labor-market approach to understanding information sharing among banks: Discussions on “A tale of two markets: Labor market mobility and bank information sharing”

A labor-market approach to understanding information sharing among banks: Discussions on “A tale of two markets: Labor market mobility and bank information sharing”

Value Relevance of Accounting Information and Noise Trading in Banks and Financial Institutions

This study aimed to analyze the financial accounting information's relative and incremental value relevance between 2012 and 2019. It also analyzed the relationship between noise trading and the value relevance of financial accounting information using 564 firm-year observations on banks and financial institutions in the Indonesia Stock Exchange (IDX) from 2012 to 2019. The price valuation model prepared by Ohlson [1] was used to test the value relevance of accounting information. The findings showed the relative and incremental value relevance of earnings and book value during the study. Furthermore, noise trading has a moderating effect on the earnings' value relevance. The samples used were from the financial sector to compare value relevance from previous literature on manufacturing companies. The results could be useful to current and potential investors while considering investing in the financial sector.

How Do Bank-Specific Factors Impact Non-Performing Loans: Evidence from G20 Countries

Abstract Banking is important for the stability and success of the economy. The success of the banking system on financial intermediation in developing countries is directly affected by non-performing loans (NPLs). Many factors can be treated as NPL determinants. Accordingly, the factors that explain NPLs contain very important information for banks. To this end, the study is an attempt to examine various banking factors that affect NPLs with respect to developing economies. In this study, the bank-specific and macroeconomic factors affecting the NPL rates were analysed through the dynamic panel data analysis. Analyses were made using described G20 countries between 1998 and 2017. The results indicate that the lagged value of NPLs, return on equity, credit growth and credit costs have a significant positive relationship with NPLs, while capital adequacy and GDP have a negative association with NPLs. The results confirm that if the bank-specific conditions change, the credit quality and bank management of banks are affected. It was concluded that the performance of banks is responsive to an effective loan monitoring policy. The findings of the study have implications for policymakers and regulators in the banking sector.

Perancangan Sistem Informasi Bank Darah Menggunakan Basis Data NoSQL

The existence of a blood exchange transaction process through a system carried out by the community, causing storing and managing data on a large scale is now causing problems in terms of scalability for blood bank managers in Yogyakarta. The process of blood transactions carried out by PMI units and hospitals at any time, makes the structure of relations in the blood banking system more complicated. In fact, every PMI unit and hospital in Yogyakarta requires a real-time data collection and storage process, considering that access to mobility of blood transactions is carried out almost 24 hours a day. Implementing an information system using a non-relational database model, is an alternative in the process of simplifying the relational structure in data relationships, this is because the non-relational database uses a NoSQL database model that provides support for database speed so that it remains optimal. In the research conducted, an information system was created that applied a non-relational database model to a case study of a blood bank information system. Where the NoSQL database is suitable for blood bank systems because it has high performance and is non-relational with real-time data storage and retrieval processes. The research conducted resulted in a blood bank information system that was developed using the Firebase database, where this system can display some data from the database such as viewing blood stocks, hospitals, blood donor events, and other information that is carried out in real time.

Multi-Image Cryptographic Based Two-Factor Authentication in Banking Systems and Services

Core banking is a back end system with a set of services provided by a cluster of bank branches which is associated with retail banking. Core banking functions include many operations like bank patrons can access their deposits and achieve fundamental transactions from the associate branch offices. The most important problem in core banking is the credibility of the client. It is quite tough to trust the data on the net due to the inevitable hacking of the record on the network. To resolve this downside of authentication, a system is proposed with algorithmic rules associated by IP and VC. This paper defines a method of processing the signature and dividing it into shares of a client. The total diversity of shares will be created based on the premise preferred by the bank. Once two shares are formed, one is held on within the bank information and therefore the difference is unbroken by the client. The client has to demonstrate the share all through of his transactions. This share is laden with the major share to induce the first signature and the correlation methodology has been employed to lay hold of the conclusion on adherence or decline of the output and display to the client.

A tale of two markets: Labor market mobility and bank information sharing

We develop a theory of bank information sharing, highlighting the interactions between credit and labor markets. A better-informed relationship bank competes with a less informed foreign bank for borrowers under asymmetric information about borrowers’ creditworthiness. Credit market competition triggers competition for the relationship bank’s loan officers, who possess valuable information about the borrowers’ creditworthiness. The relationship bank can share credit information to soften the labor market competition, despite intensifying the credit market competition. When labor market mobility is moderate, information sharing emerges as the optimal strategy of the relationship bank.

DIVERSIFICATION OF THE BANK'S ACTIVITY AND THE ROLE OF BANKING SERVICES IN INCOME FORMATION

The development of modern financial and economic relations falls on the period of deep transformation processes in banking, the application of innovations in the organization and forms of customer service, methods of bank management. Traditional types of banking activities have become more complicated, have acquired qualitatively new features, and due to the introduction of financial transactions that previously had no analogues in banking practice. Using the annual financial information of Ukrainian banks for the period 2014-2021, the impact of diversification on the bank's performance is considered. It was revealed that there is a discrepancy between the standard organizational structures of the bank and the principles of customer-oriented technologies, in connection with which a number of proposals were made to implement new principles of program activities. A thorough analysis of the interpretations of the concept of "financial innovation", "banking innovation", "banking product innovation" available in the scientific literature and identified several approaches to understanding it. The procedure of assessment of diversification of commercial bank activity is carried out. The research of foreign and domestic scientists of innovative activity of banks as satisfaction of needs of clients with new products and services is analyzed. Effective ways to implement a diversification strategy in a commercial bank are presented. The qualities of a competitive bank are determined and the requirements for banking products are singled out. The study revealed that a less integrated financial market in Ukraine gives banks an advantage in achieving greater diversification. The paper outlines the principles of determining the factor influence on the diversification of banking services in competitive languages. The results of the study showed that income diversification increases the efficiency of the bank, but further research is needed to explore other possibilities that may explain this relationship. The proposed system provides specific recommendations for the implementation of the strategy of diversification of operations for banking institutions.

APLIKASI MULTI BANK SAMPAH BERBASIS WEB

Material waste is unwanted residue after the end of a process. Waste reduction activities aim to make all levels of society, including the government, the business world and the wider community able to carry out activities to reduce, reuse, recycle (3R) through smart, efficient and programmatic efforts. The best solution to this problem is a waste bank. Waste Bank is a place for sorting and collecting waste that can be recycled and reused which has economic value. Waste bank work mechanisms such as sorting waste, submitting waste to waste banks, weighing waste, recording, selling the delivered waste are entered into a savings book and revenue sharing for the sale of waste between savers and implementers.The multi waste bank information system can help the waste bank work.The multi waste bank information system can be used by the waste bank for the publication of the location of the waste bank, data collection of waste bank customers, recording and archiving customer transaction data and helping the waste bank to find customers with the online customer registration feature. The multi waste bank information system is built on a web basis using the laravel framework. The method applied in the development of a multi bank waste information system uses the waterfall model. The multi waste bank information system has been successfully built by testing the system's functionality using black box testing and expert judgement. The results that the system can function according to user expectations and needs.

A COMPARATIVE ANALYSIS BETWEEN WESTERN BALKAN COUNTRIES AND SELECTED OECD COUNTRIES (2010 - 2019) OF THE EFFECT OF UNEMPLOYMENT ON NON-PERFORMING LOAN

The main purpose of this paper is to determine the effect of unemployment on non-performing loans through a comparative analysis between the Western Balkans countries and some selected OECD countries. The size of non-performing loans (NPLs) plays a key role in the stability of the banking sector of a country. Macroeconomic factors that explain the NPLs contain very important information for banks as well as for a country and studies in this regard, which compare developing countries and already developed ones have received little attention. To carry out this study, panel data and quantitative econometric models have been applied, specifically Linear Regression, Random Effect, Fixed Effect, Huasman - Taylor Regression and Generalized Estimating Equations (GEE Model) on secondary data from official reports of the World Bank, Organization for Economic Cooperation and Development, during the period from 2010 to 2019. Based on economic theory and our findings, we can say that the relationship between the unemployment rate and non-performing loans is directly proportional: an increase in the unemployment rate will lead to an increase in the non-performing loan rate. Moreover, Findings show that controlling the rate of unemployment helps in controlling the level of non-performing loans

Current capacity, bottlenecks, and future projections for offsetting habitat loss using Mitigation and Conservation banking in the United States

Habitat banking in its many iterations is an established and popular mechanism to deliver environmental offsets. The United States can look back at over 30 years of banking experience with the underlying framework and policies being consistently updated and improved. Given the increased demand in habitat banking, we provide insights into how bank area capacity is distributed across the United States for four different bank targets (wetlands, streams, multiple ecosystems, species) based on information extracted from the Regulatory In-lieu Fee and Bank Information Tracking System, as well as, estimating future capacities and area reserves through a predictive modeling approach based on data from the past 26 years. Future predictions indicate a decrease in available reserves for banks targeting wetlands or multiple ecosystems, with potential bottlenecks relating to large reserves being limited to the southeast and release schedules not catching up to the current and anticipated demand. Banks targeting species or streams are predicted to meet future demand, with species banks (conservation banks) following a different legislative and operational approach based on the listing of endangered species and pro-active approaches with anticipated future demand. Most current reserves for all four bank types are restricted to very few service areas with around one-third of all bank areas still awaiting release, limiting their availability on a broader scale. Strategic planning networks are necessary to meet future demand on a national scale and to identify areas suitable for banking or likely to experience future environmental or developmental stress.

The impact of COVID-19 on financial structure and performance of Islamic banks: a comparative study with conventional banks in the GCC countries

PurposeThe aim of this paper has twofold: (1) to explain and compare the financial evolution of Islamic and conventional banking sector in the Gulf Cooperative Council (GCC) countries before and during the COVID-19 pandemic and (2) to explore the key success factors that might affect Islamic and conventional banks performance before and mainly during COVID-19 pandemic period.Design/methodology/approachOrbis Bank Focus database and annual financial reports are used to collect financial information of Islamic and conventional banks in GCC countries over four years: 2017, 2018, 2019 and 2020. Descriptive statistics, T-test, multiple regression, and 2SLS and GMM models are employed to analyze the financial structure and performance of Islamic and conventional banks before and during the COVID-19 pandemic period.FindingsResults of this study reveal that (1) there is a significant difference between Islamic banks and conventional banks during the crisis of COVID-19, where the conventional banks have presented a higher level of financial performance and financial liquidity than their Islamic counterparts, (2) conventional banks have revealed higher capacity to manage their financial risk during the crisis period, and (3) a high level of non-performing loan, high inflation rate and high percentage of non-important cost have a negative impact on the financial performance of Islamic banks mainly during the pandemic period of COVID-19. However, the result indicates that a high level of liquidity risk increased the performance of Islamic banks but this impact falls sharply during the pandemic period.Originality/valueThis study provides information that supports investors, regulators and executive managers in GCC countries. A well-structured balance sheet would improve the financial performance and risk management of the banking sector in GCC countries, especially in times of crisis and pandemics.

Least-Distance Range Adjusted Measure in DEA: Efficiency Evaluation and Benchmarking for Japanese Banks

This study aims to formulate the least-distance range adjusted measure (LRAM) in data envelopment analysis (DEA) and apply it to evaluate the relative efficiency and provide the benchmarking information for Japanese banks. In DEA, the conventional range adjusted measure (RAM) acts as a well-defined model that satisfies a set of desirable properties. However, because of the practicality of the least-distance measure, we formulate the LRAM and propose the use of an effective mixed integer programming (MIP) approach to compute it in this study. The formulated LRAM (1) satisfies the same desirable properties as the conventional RAM, (2) provides the least-distance benchmarking information for inefficient decision-making units (DMUs), and (3) can be computed easily by using the proposed MIP approach. Here, we apply the LRAM to a Japanese banking data set corresponding to the period 2017–2019. Based on the results, the LRAM generates higher efficiency scores and allows inefficient banks to improve their efficiency with a smaller extent of input–output modification than that required by the RAM, thereby indicating that the LRAM can provide more easy-to-achieve benchmarking information for inefficient banks. Therefore, from the perspective of the managers of DMUs, this study provides a valuable LRAM for efficiency evaluation and benchmarking analysis.

Fake E Job Posting Prediction Based on Advance Machine Learning Approachs

There are many jobs adverts on the internet, even on reputable job posting sites, that never appear to be false. However, following the selection, the so-called recruiters begin to seek money and bank information. Many candidates fall into their traps and lose a lot of money as well as their existing job. As a result, it is preferable to determine whether a job posting submitted on the site is genuine or fraudulent. Manually identifying it is extremely difficult, if not impossible! An automated online tool (website) based on machine learning-based categorization and algorithms are presented to eliminate fraudulent job postings on the internet. It aids in the detection of bogus job postings among the vast number of postings on the internet.