Purpose The relatively new technology of generative artificial intelligence (Gen AI) is transformative and revolutionary across a variety of sectors, including financial technology (FinTech) industry. Gen AI can completely change the key areas of FinTech fundamentally that include risk management, fraud detection, customization of services and investment research. In addition to helping FinTech firms to automate and streamline their business operations, this integration has also enabled the start-ups to offer better products that are not only innovative but also more individualized, effective, and efficient than before. While generative AI has numerous applications in the FinTech industry, it's also important to consider whether the ethical dilemmas, data privacy difficulties, and possible accountability and transparency issues have been adequately handled. To ensure the compliance of legal standards, data privacy, and transparency in the application of Gen AI in the financial sector, the enactment of robust regulatory frameworks, data safety protocols, and the ethical and responsible use of generative AI to minimize security risks is the need of the hour. Methodology The present study is primarily theoretical in nature and is based upon an extensive analysis of existing resources. Various academic papers, industry reports, case studies and other relevant sources have been reviewed comprehensively to explore various challenges related to responsible implementation of Generative AI in the context of Fintech. The study delves into the intricacies of generative AI, understanding its challenges in the realm of Financial Industry. Research Implications In order to avoid misuse and risky propositions of generative AI technologies, it is important to follow some best practices to ensure transparency, strong ethical framework, ease of use and success. This study delves into harnessing the benefits of generative AI while mitigating its challenges, ensuring fairness, inclusivity and enhancing accountability. The results of this study will help everyone involved in Fintech from Big technology companies to Policymakers to make better decisions while introducing generative AI into their workflows. An attempt has been made in this study to create awareness among its users to be careful and make good rules in order to ensure that AI in finance is fair and safe for everyone. Social Implications Responsible generative AI can help ensure that outcomes/results of AI driven innovations and products are transparent, risk free and secure, associated with societal values and thus promote trust and accountability towards the society and also avoids unintended negative outcomes. Findings Whether Gen AI driven outcomes are trustworthy in real world applications has become bottom line for the successful and responsible use of Generative AI technologies. Due to the complexity of AI decision making processes, it becomes difficult to completely trust its outcomes. For better tracking of the source and trustworthiness of data that is fed into AI models and processes, more dependable outcomes will require improved tools and procedures. The accuracy of Gen AI system highly depends upon the quality of data and can lead to incorrect results especially when analysis is imperfect. So as to accelerate the responsible use of Gen AI, the developers and researchers should prioritize fairness, transparency, accuracy and truthfulness in its use. Although Gen AI is a revolutionary tool in financial market data analysis, addressing the concerned obstacles in its use, is essential to safeguard the interest of all stakeholders. Originality The problems and benefits associated with the usage and implementation of Gen AI in the realm of Fin Tech industry are discussed in detail in this article. This article aims to address the concerns of Gen AI while offering comprehensive and profound insights and recommendations for handling this technology in a meaningful way. This paper offers stakeholders a comprehensive plan of action that will direct them towards the moral and practical uses of generative AI in the Fintech industry.

Balancing Innovation and Responsibility: Tackling Challenges in Generative AI for FinTech

章节
发表日期：

2025年

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Manpreet Kaur,
Kiran Jindal,
Arshdeep

摘要

Purpose The relatively new technology of generative artificial intelligence (Gen AI) is transformative and revolutionary across a variety of sectors, including financial technology (FinTech) industry. Gen AI can completely change the key areas of FinTech fundamentally that include risk management, fraud detection, customization of services and investment research. In addition to helping FinTech firms to automate and streamline their business operations, this integration has also enabled the start-ups to offer better products that are not only innovative but also more individualized, effective, and efficient than before. While generative AI has numerous applications in the FinTech industry, it's also important to consider whether the ethical dilemmas, data privacy difficulties, and possible accountability and transparency issues have been adequately handled. To ensure the compliance of legal standards, data privacy, and transparency in the application of Gen AI in the financial sector, the enactment of robust regulatory frameworks, data safety protocols, and the ethical and responsible use of generative AI to minimize security risks is the need of the hour. Methodology The present study is primarily theoretical in nature and is based upon an extensive analysis of existing resources. Various academic papers, industry reports, case studies and other relevant sources have been reviewed comprehensively to explore various challenges related to responsible implementation of Generative AI in the context of Fintech. The study delves into the intricacies of generative AI, understanding its challenges in the realm of Financial Industry. Research Implications In order to avoid misuse and risky propositions of generative AI technologies, it is important to follow some best practices to ensure transparency, strong ethical framework, ease of use and success. This study delves into harnessing the benefits of generative AI while mitigating its challenges, ensuring fairness, inclusivity and enhancing accountability. The results of this study will help everyone involved in Fintech from Big technology companies to Policymakers to make better decisions while introducing generative AI into their workflows. An attempt has been made in this study to create awareness among its users to be careful and make good rules in order to ensure that AI in finance is fair and safe for everyone. Social Implications Responsible generative AI can help ensure that outcomes/results of AI driven innovations and products are transparent, risk free and secure, associated with societal values and thus promote trust and accountability towards the society and also avoids unintended negative outcomes. Findings Whether Gen AI driven outcomes are trustworthy in real world applications has become bottom line for the successful and responsible use of Generative AI technologies. Due to the complexity of AI decision making processes, it becomes difficult to completely trust its outcomes. For better tracking of the source and trustworthiness of data that is fed into AI models and processes, more dependable outcomes will require improved tools and procedures. The accuracy of Gen AI system highly depends upon the quality of data and can lead to incorrect results especially when analysis is imperfect. So as to accelerate the responsible use of Gen AI, the developers and researchers should prioritize fairness, transparency, accuracy and truthfulness in its use. Although Gen AI is a revolutionary tool in financial market data analysis, addressing the concerned obstacles in its use, is essential to safeguard the interest of all stakeholders. Originality The problems and benefits associated with the usage and implementation of Gen AI in the realm of Fin Tech industry are discussed in detail in this article. This article aims to address the concerns of Gen AI while offering comprehensive and profound insights and recommendations for handling this technology in a meaningful way. This paper offers stakeholders a comprehensive plan of action that will direct them towards the moral and practical uses of generative AI in the Fintech industry.