The decline of trust across the U.S. finance industry

Limbach, Peter; Rau, P. Raghavendra; Schürmann, Henrik

doi:10.1016/j.jebo.2023.07.006

Cited by 3 publications

(1 citation statement)

References 55 publications

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“…Recent research by Popa et al (2022) suggests that the work quality of bank employees has suffered due to excessive expectations placed on them. Over the years, the industry's traditionally demanding working conditions and elevated stress levels may have contributed to reduced employee efficiency, a lack of creativity, diminishing commitment, and an increasing dissatisfaction rate (Limbach et al, 2023;Lin et al, 2018;Noorazem et al, 2021;Ward, 2019).…”

Section: Introductionmentioning

confidence: 99%

Enhancing Employee Efficiency Through Deep-Level Workforce Diversity: A Study of Selected Deposit Money Banks in Lagos State

2024

strategicjournals.com

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Deposit Money Banks (DMBs) play a vital role in a country's financial stability and economic growth by facilitating fund flows and offering crucial financial services. Despite efforts to improve employee efficiency within DMBs, the desired outcomes may not have been achieved due to a lack of emphasis on deep-level diversity. Understanding deep-level diversity is crucial for comprehending individual employees' complexities and their impact on performance. Unfortunately, many organizations, including DMBs, tend to prioritize surface-level characteristics, overlooking the nuanced qualities that define employees. This oversight contributes to challenges in optimizing employee performance, resulting in reduced efficiency within certain DMBs. Acknowledging and addressing deep-level diversity is imperative for organizations aiming to succeed in today's intricate global business environment. Hence, this study examined deep-level workforce diversity and employee efficiency in selected deposit money banks in Lagos State, Nigeria. The research employed a survey methodology, targeting a population of 4,871 employees from five chosen deposit money banks in Lagos State, Nigeria. A sample size of 464 was determined based on a sample size table provided by the research advisor. Data collection utilized a validated questionnaire with structured format. The reliability of constructs, measured through Cronbach's alpha coefficients, ranged from 0.70 to 0.94. A response rate of 78.9% was achieved. Data analysis encompassed descriptive techniques along with inferential statistics such as multiple linear regression. The findings revealed that deep-level workforce diversity had significant effect on employee efficiency in selected deposit money banks in Lagos, Nigeria (Adj. R 2 = 0.333; F (4,361) = 46.558, p < 0.05). The study concluded that deep-level workforce diversity enhanced employee efficiency in selected deposit money banks in Lagos, Nigeria. The study therefore recommended that management of deposit money banks should implement strategies to embrace and leverage deep-level workforce diversity to enhance employee efficiency and overall organizational performance.

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Section: Introductionmentioning

confidence: 99%

Enhancing Employee Efficiency Through Deep-Level Workforce Diversity: A Study of Selected Deposit Money Banks in Lagos State

2024

strategicjournals.com

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Scoring the Ethics of AI Robo-Advice: Why We Need Gateways and Ratings

Kofman

2024

J Bus Ethics

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Unlike the many services already transformed by artificial intelligence (AI), the financial advice sector remains committed to a human interface. That is surprising as an AI-powered financial advisor (a robo-advisor) can offer personalised financial advice at much lower cost than traditional human advice. This is particularly important for those who need but cannot afford or access traditional financial advice. Robo-advice is easily accessible, available on-demand, and pools all relevant information in finding and implementing an optimal financial plan. In a perfectly competitive market for financial advice, robo-advice should prevail. Unfortunately, this market is imperfect with asymmetric information causing generalised advice aversion with a disproportionate lack of trust in robo-advice. Initial distrust makes advice clients reluctant to use, or switch to, robo-advice. This paper investigates the ethical concerns specific to robo-advice underpinning this lack of trust. We propose a regulatory framework addressing these concerns to ensure robo-advice can be an ethical resource for good, resolving the increasing complexity of financial decision-making. Fit for purpose regulation augments initial trust in robo-advice and supports advice clients in discriminating between high-trust and low-trust robo-advisors. Aspiring robo-advisors need to clear four licensing gateways to qualify for an AI Robo-Advice License (AIRAL). Licensed robo-advisors should then be monitored for ethical compliance. Using a balanced score card for ethical performance generates an ethics rating. This gateways-and-ratings methodology builds trust in the robo-advisory market through improved transparency, reduced information asymmetry, and lower risk of adverse selection.

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The Importance of Trust to Financial Markets and Institutions: Exploring the Current Literature

Gurun,

Booth

2024

TEL

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The decline of trust across the U.S. finance industry

Cited by 3 publications

References 55 publications

Enhancing Employee Efficiency Through Deep-Level Workforce Diversity: A Study of Selected Deposit Money Banks in Lagos State

Enhancing Employee Efficiency Through Deep-Level Workforce Diversity: A Study of Selected Deposit Money Banks in Lagos State

Scoring the Ethics of AI Robo-Advice: Why We Need Gateways and Ratings

The Importance of Trust to Financial Markets and Institutions: Exploring the Current Literature

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