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Introduction
Financial Technology (FinTech) is defined as applying digital technology in the financial business to provide innovative financial products and services (Yang et al. 2023). With the advancement of digital technology, the global FinTech market has been growing at a rate over the past few years (Liu et al. 2020). It highlights the potential of digital technology in the financial sector. There are many successful cases of fintech innovations. For example, Alipay and WeChat Pay have become popular in China and are the primary payment methods for daily consumption (Mombeuil and Uhde 2021). Additionally, offering clients diverse portfolios using intelligent investing platforms like Betterment and Wealthfront has altered conventional investment notions (Shanmuganathan 2020).
As a result, the financial industry has seen significant shifts because of digital technology. Exploring ways to use digital technology has emerged as a key study area to improve further financial services and products (Choi and Kim 2023; Feng et al. 2022). In this setting, ChatGPT and other intelligent interaction systems can promote financial inclusion, improve customer experience, and advance the FinTech industry (Singh and Joshi 2023).
The financial industry may use ChatGPT in a variety of ways (Ali and Aysan 2023). By automating client query responses, financial institutions may increase customer service effectiveness, save staff expenses, and improve user experience. It may also predict and analyze data to assist financial organizations in better understanding market trends and investment possibilities. Additionally, ChatGPT may provide clients with individualized financial advice, delivering exact direction depending on client preferences. Finally, ChatGPT is crucial to risk management since it offers information to assist financial professionals with risk analysis and evaluation.
However, care must be taken to ensure the confidentiality and safety of financial data while using ChatGPT in the financial sector (Khan and Umer 2023). Data encryption, access control, and authentication are necessary during model training to reduce the danger of information leakage and hacking. The interpretability of models is also an important issue. Interpretability helps financial practitioners understand the model’s decision-making process, reduce uncertainty, and increase trust in the model output. Furthermore, although ChatGPT performs well in numerical reasoning tasks, it still has limitations in sentiment analysis tasks (Li et al. 2023). Hence, ChatGPT needs to be used with an awareness of its strengths and...