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Comparative Bank Financial Risk Management Models in Fintechs and Challenger Banks.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Comparative Bank Financial Risk Management Models in Fintechs and Challenger Banks./
作者:
Zhao, Kun.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
332 p.
附註:
Source: Dissertations Abstracts International, Volume: 83-04, Section: B.
Contained By:
Dissertations Abstracts International83-04B.
標題:
Information technology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28813585
ISBN:
9798544275268
Comparative Bank Financial Risk Management Models in Fintechs and Challenger Banks.
Zhao, Kun.
Comparative Bank Financial Risk Management Models in Fintechs and Challenger Banks.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 332 p.
Source: Dissertations Abstracts International, Volume: 83-04, Section: B.
Thesis (Ph.D.)--Sheffield Hallam University (United Kingdom), 2021.
This item must not be sold to any third party vendors.
Risk management in banking operations is a popular topic among researchers in the fields of management and banking. Due to developments in technology, research on financial technology has also become a hot topic. Banks and financial technology companies (fintechs) need to learn what risks impact their operations and how to manage these risks effectively. The aim of this study is to investigate the relationship between risk management and bank performance, compare it between traditional banks and challenger banks/fintechs, and make suggestions on how to improve performance by analyzing historical data.This thesis adopts a mixed-method approach, estimating risk variables and their impacts on bank performance through panel data regression models (random-effects and generalized method of moments) and conducting case studies to contribute to knowledge in theory and practice. This research investigates the relationship between five main types of risks (credit risk, market risk, liquidity and capital risk, reputational risk, and operational risk) and bank performance measured by three variables (ROA, ROE and EPS). This study confirms the importance of risk management in bank performance. For example, credit risk variables show negative impacts on all banks, which suggests that reducing credit risks could increase bank performance. Market risk variables are complex with both positive and negative effects on bank performance. Thus, banks should keep market risk at a balanced level to receive better performance. Moreover, bank performance could be increased by increasing liquidity, capital and reputation as well as reducing debt, operational issues and costs.The contributions of this research include the enhancement of literature on the relationship between bank performance and risk management. Also, this research creates a greater awareness of risk management for challenger banks and fintechs. Moreover, it fills gaps in the literature by comparing results for traditional banks with those for challenger banks and fintechs. The results of this research offer new insights into risk management for both traditional banks and challenger banks and fintechs for iii academics and have the potential to assist traditional banks and challenger banks and fintechs in managing their risks and improving their efficiency in practice.
ISBN: 9798544275268Subjects--Topical Terms:
532993
Information technology.
Subjects--Index Terms:
Financial risk
Comparative Bank Financial Risk Management Models in Fintechs and Challenger Banks.
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Risk management in banking operations is a popular topic among researchers in the fields of management and banking. Due to developments in technology, research on financial technology has also become a hot topic. Banks and financial technology companies (fintechs) need to learn what risks impact their operations and how to manage these risks effectively. The aim of this study is to investigate the relationship between risk management and bank performance, compare it between traditional banks and challenger banks/fintechs, and make suggestions on how to improve performance by analyzing historical data.This thesis adopts a mixed-method approach, estimating risk variables and their impacts on bank performance through panel data regression models (random-effects and generalized method of moments) and conducting case studies to contribute to knowledge in theory and practice. This research investigates the relationship between five main types of risks (credit risk, market risk, liquidity and capital risk, reputational risk, and operational risk) and bank performance measured by three variables (ROA, ROE and EPS). This study confirms the importance of risk management in bank performance. For example, credit risk variables show negative impacts on all banks, which suggests that reducing credit risks could increase bank performance. Market risk variables are complex with both positive and negative effects on bank performance. Thus, banks should keep market risk at a balanced level to receive better performance. Moreover, bank performance could be increased by increasing liquidity, capital and reputation as well as reducing debt, operational issues and costs.The contributions of this research include the enhancement of literature on the relationship between bank performance and risk management. Also, this research creates a greater awareness of risk management for challenger banks and fintechs. Moreover, it fills gaps in the literature by comparing results for traditional banks with those for challenger banks and fintechs. The results of this research offer new insights into risk management for both traditional banks and challenger banks and fintechs for iii academics and have the potential to assist traditional banks and challenger banks and fintechs in managing their risks and improving their efficiency in practice.
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