How Traditional Financial Institutions have adapted to Artificial Intelligence, Machine Learning and FinTech?

Sharbek, Nermin

doi:10.2478/picbe-2022-0078

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…This transformation is not without its challenges, but the overall impact has been profoundly positive, reshaping the way financial institutions operate and make decisions. Sharbek (2022) explores the adaptation of traditional financial institutions to AI, Machine Learning (ML), and FinTech innovations, highlighting the dual impact of these technologies. On one hand, AI and ML have introduced significant advantages in terms of fraud protection, cost savings, and operational efficiency.…”

Section: Impact Assessment Of Ai In Financial Forecastingmentioning

confidence: 99%

Machine learning in financial forecasting: A U.S. review: Exploring the advancements, challenges, and implications of AI-driven predictions in financial markets

Odeyemi Olubusola,

Noluthando Zamanjomane Mhlongo,

Donald Obinna Daraojimba

et al. 2024

World J. Adv. Res. Rev.

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This study delves into the integration of Artificial Intelligence (AI) and Machine Learning (ML) in financial forecasting within the United States, aiming to uncover the advancements, challenges, and broader implications for stakeholders in the financial markets. Employing a systematic literature review and content analysis, the research meticulously examines peer-reviewed journals, conference proceedings, and reputable institutional reports from 2010 to 2024. The methodology focuses on identifying empirical evidence that highlights the role of AI and ML technologies in enhancing the accuracy and efficiency of financial predictions, while also considering the ethical and regulatory challenges posed by these advancements. Key findings indicate that AI and ML have significantly revolutionized financial forecasting, offering improved precision in market trend analysis and asset price predictions through innovations in deep learning, reinforcement learning, and hybrid models. Despite these advancements, challenges related to data quality, model interpretability, and ethical considerations persist, underscoring the need for robust regulatory frameworks to ensure the responsible use of AI in finance. The study concludes that while AI and ML present substantial opportunities for transforming financial forecasting and decision-making processes, addressing the associated challenges is crucial for their ethical and effective integration. Strategic recommendations for financial leaders and policymakers emphasize the importance of fostering innovation, enhancing AI literacy, and developing international standards for AI use in finance. Future research directions include exploring the impact of emerging technologies on financial forecasting and developing adaptive regulatory frameworks to accommodate technological advancements.

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Section: Impact Assessment Of Ai In Financial Forecastingmentioning

confidence: 99%

Machine learning in financial forecasting: A U.S. review: Exploring the advancements, challenges, and implications of AI-driven predictions in financial markets

Odeyemi Olubusola,

Noluthando Zamanjomane Mhlongo,

Donald Obinna Daraojimba

et al. 2024

World J. Adv. Res. Rev.

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“…The term is used to denote those companies that provide innovative financial products and services, through the use of technology (Dorfleitner et al, 2017). These companies use cutting-edge technologies to increase efficiency and quality of work (Sharbek, 2022). In addition, they are associated with innovation where companies develop new products, business models and processes (Puschmann, 2017).…”

Section: Km Practices For Acap In Fintechmentioning

confidence: 99%

Knowledge Absorptive capacity in Fintechs: Evidence from Latin America

Pimentel Bernal,

Davila,

Cuenca-Jiménez

et al. 2023

ECKM

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Fintechs use technologies to offer financial services in a different way than traditional ones. The Fintech sector has seen rapid growth in the global economy and has expanded access to financial services to a wide variety of users; consequently, it has drawn the attention of academics around the world. Being knowledge-intensive organisations, Fintechs can absorb knowledge as a key competence. Absorptive capacity – which includes practices to acquire, assimilate, transform, and apply knowledge - has been analysed in previous studies as a factor that can influence organisational performance. However, most studies have used data from developed countries. The objective of this ongoing study is to analyse the knowledge management (KM) practices used by a Latin American Fintech to absorb knowledge. For this, a case study with a qualitative approach will be presented, using data from an international company of Peruvian origin, specializing in leasing. Data was collected through interviews. The information collected was transcribed and categorized for analysis. The analysis will include content analysis and narrative analysis techniques, supported by Atlas.ti software. The results contribute to the KM literature in two ways: First, by describing how knowledge absorption occurs in Fintechs. Second, by systematizing evidence on how KM practices act in organisations in emerging contexts, to support absorption capacity, and consequently, contribute to organisational results. On the empirical side, this study provides specific insights to managers of companies in the financial and technological sectors in emerging contexts, on how and which practices implementing to improve KM in their organisations.

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“…Examining the emergence and evolution of codes of conduct, this review unveils the ongoing dialogue between regulatory bodies, financial institutions, and stakeholders as they navigate the intricate balance between financial innovation and ethical preservation. In the contemporary context, the advent of transformative technologies such as artificial intelligence, blockchain, and fintech has redefined the landscape of financial services (Sharbek, 2022, Hussain, and Hameed, 2023, Sheela et al, 2024. The paper scrutinizes the ethical implications of these technological advancements, dissecting the challenges and opportunities they present for ethical decision-making within the industry.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Ethical Practices in Banking and Finance

Ejuma Martha Adaga,

Zainab Efe Egieya,

Sarah Kuzankah Ewuga

et al. 2024

Financ. account. res. j.

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This paper presents a thorough examination of ethical practices within the dynamic landscape of banking and finance. As the financial industry plays a pivotal role in global economic systems, the need for stringent ethical standards becomes increasingly apparent. This comprehensive review encompasses various dimensions of ethical considerations, ranging from corporate governance and risk management to customer relations and social responsibility. The banking and finance industry occupies a vital role in society, wielding immense power over financial stability, development, and individual well-being. However, its ethical practices have consistently faced scrutiny and criticism. This review aims to provide a comprehensive understanding of the current landscape of ethical practices in banking and finance, analyzing both shortcomings and advancements. The study delves into the historical evolution of ethical norms in banking and finance, tracing the development of codes of conduct and regulatory frameworks that shape the industry's ethical landscape. It analyzes the impact of technological advancements on ethical considerations, exploring the challenges and opportunities presented by digitalization, fintech, and blockchain technologies. Furthermore, the review evaluates the role of leadership and organizational culture in fostering ethical behavior within financial institutions. It examines case studies of ethical lapses and their repercussions, shedding light on the importance of accountability and transparency in maintaining public trust. The paper also discusses the ethical implications of financial decision-making, considering issues such as fair lending practices, responsible investing, and the ethical dimensions of risk assessment. It scrutinizes the role of financial education in promoting ethical awareness among stakeholders and addresses the ethical considerations associated with emerging financial products and services. This comprehensive review synthesizes key insights into the ethical practices within banking and finance, offering a holistic perspective on the challenges and opportunities faced by the industry. By understanding and addressing ethical concerns, financial institutions can contribute to the development of a sustainable and responsible financial ecosystem that benefits both the industry and society at large. Keywords: Ethical, Banking, Cybersecurity, Big Data, Banking Regulation.

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How Traditional Financial Institutions have adapted to Artificial Intelligence, Machine Learning and FinTech?

Cited by 6 publications

References 24 publications

Machine learning in financial forecasting: A U.S. review: Exploring the advancements, challenges, and implications of AI-driven predictions in financial markets

Machine learning in financial forecasting: A U.S. review: Exploring the advancements, challenges, and implications of AI-driven predictions in financial markets

Knowledge Absorptive capacity in Fintechs: Evidence from Latin America

A Comprehensive Review of Ethical Practices in Banking and Finance

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