Narrow Results

We examine the determinants of bank capital structure using a large sample of banks in the world. We find that banks determine their capital structure in much the same way as non-financial firms, except for growth opportunities. We also provide evidence that country-level factors, such as the legal system, bank-specific factors and economic conditions influence banks’ capital decisions through their impacts on bankruptcy costs, agency costs, information asymmetry and liquidity creation. The results show that, besides the direct effects, there are indirect impacts of country-level factors on the decision of bank capital. Our results have potential policy implications for the on-going regulatory reform.

INDONESIA – Biomed Analysis: Indonesia needs a central science fund.

KOREA – Agilent Technologies helps City of Daegu and Daegu Gyeongbuk Institute of Science and Technology search for biomarkers for neurological diseases.

SINGAPORE – New S$6.5m facility at NTU by SCELSE and Carl Zeiss to boost used water treatment and environmental life sciences engineering research in Singapore.

SINGAPORE – Chugai expands in Singapore with opening of second satellite research institute.

SINGAPORE – Rising Above the Present into the Next-Generation.

SINGAPORE – Austrianova Singapore announces new pancreatic cancer models.

SINGAPORE – IBN and Fortis Colorectal Hospital establish tissue bank for colorectal cancer research.

SINGAPORE – Electronic medical records progress from an enterprise-centric solution to a customer-specific application, finds Frost & Sullivan.

SINGAPORE – Global perspectives on Health IT from Harvard Medical School thought leader, Dr Blackford Middleton.

AUSTRALIA – World's first fluorescent flowers.

UNITED KINGDOM – AbD Serotec introduces bovine and ovine Dendritic Cell Growth Kits and antibodies.

USA – Medicago Successfully Completes the Production of More Than Ten Million Doses of H1N1 VLP Influenza Vaccine in One Month.

USA – Research validates BioNano genomics' mapping platform for complex human genome analysis.

USA – Nine population strategies to stop short of 9 billion.

USA – Virtual science libraries to be launched in Central Asia.

USA – Vaginal ring may help reduce HIV infections.

The Capital Purchase Program (CPP) was the first and most significant program under the Troubled Asset Relief Program (TARP) during 2008–2009 financial crisis. This study evaluates the effect of the CPP during this period on the cost of equity of 170 publicly listed banks in the United States that received funding. To control for the potential effects of endogeneity on our results, we use a propensity score matched sample of non-CPP banks. Using this approach, we document robust evidence that the liquidity provided by the government bailout reduced the cost of equity for recipient banks, especially for those banks that repaid their bailout funds in full. This decrease in the cost of equity is particularly significant for banks with high market-to-book ratios, low concentrations of institutional ownership, and those banks with at least one large blockholder. Our findings have important implications for the assessment of government bailout programs and the future regulation of financial institutions.

This paper conducts a more in-depth study of employee performance to connect with compensation and job satisfaction and the work environment of employees in PT Bank Rakyat Indonesia (Persero) Tbk. (BRI). This research was conducted at PT Bank Rakyat Indonesia (Persero) Tbk. operating in Indonesia. The research population was all employees of the Branch Offices of PT Bank Rakyat Indonesia (Persero) Tbk. spread over in Sumatera, Jawa, Kalimantan, Sulawesi, Bali and Jayapura. The sample was collected using Proportional Random Sampling Stratified from six locations spread throughout Indonesia. Considering the wide area, the sampling technique is adjusted to the area, so sampling is based on the island as a sub-population. The sample of this study was 212 employees. This amount has met the minimum sampling requirements if using the Generalised Structural Component Analysis (GSCA) method. Compensation does not directly affect employee performance. Working environment directly influences the employee performance in PT Bank Rakyat Indonesia (Persero) Tbk. There is an influence of compensation and working environment on job satisfaction and employee performance in PT Bank Rakyat Indonesia (Persero) Tbk. The leader of PT Bank Rakyat Indonesia (Persero) Tbk. should improve employees’ performance by taking into account the improvement of compensation which includes the suitability of wages and salaries, incentives, benefits and facilities with their performance.

Corporate governance carries strategic importance and should be addressed correctly by decision-makers. Corporate finance literature suggests that diverse boards are a part of good corporate governance practice. However, it is not clear how diverse board characteristics might affect innovation and innovation search strategies. Utilising the data from 25 banks listed in the UAE stock exchanges, this study evaluates the impact of boardroom diversity on firm innovativeness both before and after the drop in the oil prices. The results show that although gender and education do not significantly affect innovativeness of banks, having more experienced and independent board members enhances the innovation. The effect of experienced board members on innovation is more pronounced during the oil price drop period, whereas the effect of independent board members decreases after the drop in the oil prices.

Customer classification is one of the major tasks in customer relationship management. Customers often have both static characteristics and dynamic behavioral features. Using both kinds of data to conduct comprehensive analysis can enhance the reasonability of customer classification. In the proposed classification method, customer dynamic data is clustered using a hybrid genetic algorithm. The result is then combined with customer static data to give reasonable customer segmentation supported by neural network technique. A bank dataset-based experiment shows that applying the proposed method can obviously improve the accuracy of customer classification comparing with the traditional methods where only static data is used.

This work discusses some of the critical aspects of bank corporate governance in the European Union. Enhancing sound corporate governance practices has become one of the major concerns in the supervisory authority’s agenda and one of the critical features to evaluate banks’ stability. The global rethinking about corporate governance rules has translated into a stronger focus on board diversity for EU banks. The existing literature and sound corporate governance practices support the view that different types of board members may bring different capabilities to their banks. Even if board diversity may add complexity to the functioning of the board, the advantages it brings are of utmost importance in the challenging environment banks are facing. This work highlights the fragmentation of the EU corporate governance rules as banks have to comply with 27 sets of different regulations and codes. This complexity should not be ignored, as member states’ specificities, legal systems, and a more general openness to diversity influence the effect reforms may have on banks’ performance and stability.

This paper evaluates how the risks associated with mergers and acquisitions (M&As) affect Bank Holding Companies’ (BHCs) levels of insolvency risk. Bank insolvency is hypothesized to be affected by M&As directly and indirectly through banks’ market risk, geographical diversification, and activity diversification. The relationship between bank insolvency, diversification, and market risk is estimated as a system using the Generalized Method of Moments (GMM). The key finding is that M&As erode banks’ insolvency, both directly and indirectly through the effects associated with their geographical diversification.

The aim of this paper is to examine the performance and efficiency changes of commercial banks in Japan and Taiwan. Banks in both countries operate in similar environments: nationally oriented with protected domestic banking market. Data envelopment analysis (DEA) is applied to a panel of 6 nationwide banks in Japan and 12 in Taiwan between 2006 and 2011 and utilizes a Malmquist index to measure the relative importance of productivity changes. In this mode, five input variables (i.e., number of branches, number of employee per branch, share in total assets, share in total loans, and share in total deposits) and five output variables (i.e., ROA, ROE, net interest income/total assets, net interest income/total operating income, and non-interest income/total assets) are utilized. The results indicated that 2008 financial crisis did profoundly impact performance for commercial banks in Taiwan in terms of TE, SE and TFP, but did not seem to have great impact on the TE and TFP for commercial banks in Japan. It is found that the relative importance of productivity changes decline after 2008 financial crisis for Taiwanese group. However, Japanese group shows slight affects in terms of technical change and total factor productivity (TFP) change. These findings suggest that there is still some catching-up for the inefficient banks in Japan and Taiwan to be more competitive with the intention of facing a more globalized competition after 2008 financial crisis.

This study explores the status of the online risk disclosure practices on the listed Islamic banks in the Egyptian exchange market. Manual content analysis was employed as a research approach to examine the practices of the online risk disclosure for the three listed Islamic banks in Egypt, and based on a prior study, it developed a risk index composed of 10 main categories and a total of 61 sub-items as a research tool. The empirical analysis presents that all listed Islamic banks in the Egyptian exchange market have websites and all these banks report risk information in their published online reports (full annual report and full financial report). Furthermore, the results provide confirmatory evidence that there is a high adherence by all listed Islamic banks in Egypt to the mandatory risk disclosure requirements on their websites, while there is a low level of voluntary risk disclosure on the websites of these banks as well; in addition, the study pointed out that Al Baraka Bank has the highest average (67.2%) of online risk disclosure level among all Islamic banks, followed by Faisal Islamic Bank with an average of 65.5%, and finally, Abu Dhabi Islamic Bank came in the last place with an average of 60.6%. What’s more, the yielded data show that the total average level of online risk disclosure of the Islamic listed banks in Egypt is 64.5%. Finally, the results of this study outline that there are no significant differences between the levels of online risk disclosure at the level of the common categories for all Islamic listed banks in Egypt. The limitations of this study are as follows: the way the content analysis was conducted; in its reliance on the websites and the published online reports for examining risk disclosure information; due to its focus on the financial and non-financial risks; due to its focus on Islamic listed banks in Egypt; and due to its focus on the context of the Egyptian environment.

The emergence of FinTech has reshaped the financial sector landscape worldwide, while its potential effects are still far from clear. This chapter investigates the influence of FinTech on diversification strategies of traditional banks in China between 2012 and 2018. To this end, we construct measures of diversification from the two main perspectives taken into account so far in the literature: income-based indicators and asset-based indicators. The Peking University Digital Financial Inclusion Index is used to measure FinTech development in China; the methodological approach is instrumental quantile regression. The overall results establish a significant and positive link between FinTech and bank income diversification during the sample period, especially for national shareholding commercial banks. However, asset diversification strategies are not sensitive to FinTech for all bank tiers in China.

Big data and artificial intelligence (AI) assist businesses with decision-making. They help companies create new products and processes or improve existing ones. As the amount of data grows exponentially and data storage and computing power costs drop, AI is predicted to have great potentials for banks. This chapter discusses the implications of big data and AI for the banking industry. First, we provide background on big data and AI. Second, we identify areas in which banks can benefit from big data and AI, and evaluate their applications for the banking industry. Third, we discuss the implications of big data and AI for regulatory compliance and supervision. Last, we conclude with the limitations and challenges facing the use of big-data based AI.

The Kerala model of cooperatives has won international attention for its achievement in building sustainable models. Collective actions have been facilitated by the people to build up a socially, economically, and environmentally feasible society. The credit sector has built up considerable financial assistance and support for the people to sustain their livelihood. Driven by the need for detailed examination, this study highlights the cases of three cooperative banks, namely Kodiyathoor Service Co-operative Bank, Kizhathadiyoor Service Co-operative Bank, and Peringandur Service Co-operative Bank, which have built a sustainable model in the cooperative sector. This study is based on primary and secondary data collected to understand the process and practices in cooperatives. This study is also a contribution towards a cooperative model for sustainable growth in banks.

This study examines the implications of a bank’s activity mix and funding strategy for its liquidity management as defined in the Basel III accords or when they create more liquidity as measured by Berger and Bouwman (2009). Using an international sample of 624 banks in 65 countries, we find that, at low levels of noninterest income and nondeposit funding, there could be some risk diversification benefits in increasing these shares; however, at higher levels of noninterest income and nondeposit funding shares, additional increases result in higher illiquidity. Finally, better accounting disclosure will improve the effect on bank liquidity by both bank’s activity mix and funding strategy, but at the same time, they worsen the bank liquidity by stricter capital stringency and more market power.

Customer classification is one of the major tasks in customer relationship management. Customers have both static characteristics and dynamic behavioral features. To apply both kinds of data to conduct comprehensive analysis can enhance the reasonability of customer classification. In this paper, customer dynamic data is clustered using a hybrid genetic algorithm and then is combined with customer static data to give reasonable customer segmentation by using neural network technique. A novel classification method which considers both the static and dynamic data of customers is proposed. Applying the proposed method in a bank's datasets can obviously improve the accuracy of customer classification comparing with traditional methods where only static data is used.