Leveraging employee relationship management to foster agility: The mediating role of employee empowerment in the Indian banking sector

This study investigates the Millennials and Gen Z perception toward Fintech services, their usage intention, and their financial behavior. The study took place in the Palestinian context with a global comparison among these generations. The authors used the questionnaire-based technique to meet the study objective. West Bank respondents were selected for this purpose; the study instrument was distributed through different social media channels. The findings show that reliability/trust and ease of use are the main issues in using a financial service. Millennials are more aware (48%) of Fintech services than Gen Z (38%), which is different from the global view where Gen Z is the highest. The smartphone penetration rate is 100% among both generations, while the financial inclusion ratio in Palestine is around 36.4%; these clear indicators are the main Fintech drivers to promote Fintech services in Palestine, and these are global indicators for Fintech adoption intention. Both generations (84%) intend to use e-wallet services, Millennials (87%) and Gen Z is (70%) prefer using real-time services. Half of the respondents see that Fintech plays a complementary role with banks. The majority see that Fintech services are cheaper than bank services. Wealth management, and robot advisor services, and both generations are looking to acquire them in the long run. The authors revealed that 85% of respondents from both generations trust banks, so it is recommended that banks digitize their financial services to meet the customers’ needs, considering that 90% of respondents see that promotions are a key issue in adopting Fintech services. Promoting e-wallet services by banks is highly recommended due to the massive rivalry with Fintech parties.

In the article, the essence of the concept of a banking institution “capitalization” is revealed. The current state of capitalization level of domestic banks is investigated. The directions of strengthening the capitalization are offered, which will increase the com¬petitiveness of domestic banking institutions in the world financial market and will ensure the national economy stability on the way toward integration into the world economy.
It is proved that the prospects for the development of any bank are largely determined by its capitalization level. Lack of proper development inhibits both individual banks and the banking sector as a whole.
In the context of the recent financial crisis, the provision of sufficient capital for banks has been one of the key issues, because the lack of capital was the greatest threat to the banking system stability. With this in mind, the issue of the banking system capitaliza¬tion is particularly topical.
Today, the development of the Ukrainian banking system under economic instability has faced the increase in competitiveness of domestic banks compared with foreign ones, in order to preserve the national priorities of the banking system in general under conditions of foreign capital movement.
The processes of concentration in the banking system of Ukraine are analyzed using Herfindahl-Hirschman index in terms of assets and equity, allowing to estimate the level of monopolization and, therefore, the impact on economic development. To con¬sider the increase in the level of capitalization and reliability of the banking institutions of Ukraine, it would be advisable, first of all, for banks to improve the quality of capital and to ensure a sufficient level of coverage of risks taken by banks.

The rise of robo-advisor wealth management services, which constitute a key element of fintech revolution, unveils the question whether they can dominate human-based advice, namely how to address the client’s behavioral biases in an automated way. One approach to it would be the application of machine learning tools during client profiling. However, trained neural network is often considered as a black box, which may raise concerns from the customers and regulators in terms of model validity, transparency, and related risks. In order to address these issues and shed more light on how neurons work, especially to figure out how they perform computation at intermediate layers, this paper visualizes and estimates the neurons’ sensitivity to different input parameters. Before it, the comprehensive review of the most popular optimization algorithms is presented and based on them respective data set is generated to train convolutional neural network. It was found that selected hidden units to some extent are not only specializing in the reaction to such features as, for example, risk, return or risk-aversion level but also they are learning more complex concepts like Sharpe ratio. These findings should help to understand robo-advisor mechanics deeper, which finally will provide more room to improve and significantly innovate the automated wealth management process and make it more transparent.