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Abstract

Generative Artificial Intelligence (GAI) telah memberikan kemudahan dalam membantu pekerjaan manusia, khususnya di bidang keuangan. GAI dapat dimanfaatkan Masyarakat sebagai penasihat keuangan pribadi, memungkinkan mereka untuk mendapatkan saran investasi yang disesuaikan dengan profil keuangan dan tujuan pribadi mereka, sehingga meningkatkan pengelolaan keuangan dan potensi keuntungan. Penelitian ini bertujuan untuk mengetahui seberapa efektif dan bagaimana kredibilitas GAI dalam perannya sebagai financial advisor. Penelitian ini menggunakan pendekatan kualitatif melalui studi literatur dengan data yang dikumpulkan melalui teori-teori dari berbagai literatur yang relevan dengan topik penelitian. Hasil penelitian menunjukkan bahwa GAI tidak dapat sepenuhnya digunakan sebagai penasihat keuangan pribadi karena hasil yang ditampilkan cenderung bias dan tidak akurat, sehingga harus disertai dengan pengawasan manusia yang salah satunya adalah dengan mengintegariskan pengetahuan dasar seperti literasi keuangan yang dengan GAI agar dapat meningkatkan pemahaman dan efisiensi pengguna terkait informasi mengenai risiko untuk memastikan bahwa keputusan yang diambil adalah yang paling sesuai dan bertanggung jawab bagi masing-masing individu.


Kata kunci: artificial intelligence, penasihat keuangan, generative artificial intelligence

Article Details

References

  1. Amoozadeh, M., Daniels, D., Nam, D., Kumar, A., Chen, S., Hilton, M., Srinivasa Ragavan, S., & Alipour, M. A. (2024). Trust in Generative AI among Students: An exploratory study. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, 1, 67–73. https://doi.org/10.1145/3626252.3630842
  2. Bahoo, S., Cucculelli, M., Goga, X., & Mondolo, J. (2024). Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis. SN Business & Economics, 4(2), 23. https://doi.org/10.1007/s43546-023-00618-x
  3. Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2024). Generative AI Can Harm Learning. SSRN, 1–59. https://doi.org/10.2139/ssrn.4895486
  4. Byrum, J. (2022). AI in Financial Portfolio Management: Practical Considerations and Use Cases. In Innovative Technology at the Interface of Finance and Operations (pp. 249–270). https://doi.org/10.1007/978-3-030-75729-8_9
  5. Cao, Y., & Zhai, J. (2022). A survey of AI in finance. Journal of Chinese Economic and Business Studies, 20(2), 125–137. https://doi.org/10.1080/14765284.2022.2077632
  6. Černevičienė, J., & Kabašinskas, A. (2024). Explainable artificial intelligence (XAI) in finance: a systematic literature review. Artificial Intelligence Review, 57(8), 216. https://doi.org/10.1007/s10462-024-10854-8
  7. Chan, G. K. Y. (2024). AI employment decision-making: integrating the equal opportunity merit principle and explainable AI. AI & SOCIETY, 39(3), 1027–1038. https://doi.org/10.1007/s00146-022-01532-w
  8. Chui, M., Roberts, R., & Yee, L. (2022). Generative AI is here: How tools like ChatGPT could change your business. McKinsey. https://www.mckinsey.com/capabilities/quantumblack/our-insights/generative-ai-is-here-how-tools-like-chatgpt-could-change-your-business#/
  9. Dobbe, R., Gilbert, T. K., & Mintz, Y. (2021). Hard choices in artificial intelligence. Artificial Intelligence, 300, 103555. https://doi.org/10.1016/j.artint.2021.103555
  10. Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71(March), 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
  11. Eluwole, O. T., & Akande, S. (2022). Artificial Intelligence in Finance: Possibilities and Threats. 2022 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT), 268–273. https://doi.org/10.1109/IAICT55358.2022.9887488
  12. Feinstein, M. (2023). 3 Ways AI Can Help Financial Advisors Grow Their Client Base. Salesforce. https://www.salesforce.com/blog/ai-for-wealth-management/
  13. Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, 25(3), 277–304. https://doi.org/10.1080/15228053.2023.2233814
  14. Ghandar, A., & Michalewicz, Z. (2011). An experimental study of Multi-Objective Evolutionary Algorithms for balancing interpretability and accuracy in fuzzy rulebase classifiers for financial prediction. 2011 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), 1–6. https://doi.org/10.1109/CIFER.2011.5953570
  15. Guan, C., Ding, D., Gupta, P., Hung, Y.-C., & Jiang, Z. (2023). A Systematic Review of Research on ChatGPT. In Exploring Cyber Criminals and Data Privacy Measures (pp. 124–150). https://doi.org/10.4018/978-1-6684-8422-7.ch007
  16. Gupta, P., Ding, B., Guan, C., & Ding, D. (2024). Generative AI: A systematic review using topic modelling techniques. Data and Information Management, 8(2), 100066. https://doi.org/10.1016/j.dim.2024.100066
  17. Halloran, L. J. S., Mhanna, S., & Brunner, P. (2023). AI tools such as ChatGPT will disrupt hydrology, too. Hydrological Processes, 37(3). https://doi.org/10.1002/hyp.14843
  18. Harrer, S. (2023). Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine. EBioMedicine, 90, 104512. https://doi.org/10.1016/j.ebiom.2023.104512
  19. How AI Investment Advisors are Transforming Financial Advice. (n.d.). Quadra Wealth. Retrieved August 11, 2024, from https://quadrawealth.com/articles/the-rise-of-ai-investment-advisors/
  20. Hutson, M. (2020). Core progress in AI has stalled in some fields. Science, 368(6494), 927–927. https://doi.org/10.1126/science.368.6494.927
  21. Kim, S., & Kim, S. (2020). Index tracking through deep latent representation learning. Quantitative Finance, 20(4), 639–652. https://doi.org/10.1080/14697688.2019.1683599
  22. Li, X., Sigov, A., Ratkin, L., Ivanov, L. A., & Li, L. (2023). Artificial intelligence applications in finance: a survey. Journal of Management Analytics, 10(4), 676–692. https://doi.org/10.1080/23270012.2023.2244503
  23. Loukeris, N., & Eleftheriadis, I. (2015). Further Higher Moments in Portfolio Selection and A Priori Detection of Bankruptcy, Under Multi‐layer Perceptron Neural Networks, Hybrid Neuro‐genetic MLPs, and the Voted Perceptron. International Journal of Finance & Economics, 20(4), 341–361. https://doi.org/10.1002/ijfe.1521
  24. Lv, Z. (2023). Generative artificial intelligence in the metaverse era. Cognitive Robotics, 3, 208–217. https://doi.org/10.1016/j.cogr.2023.06.001
  25. Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. https://doi.org/10.1016/j.futures.2017.03.006
  26. Maruyama, Y. (2020). The Conditions of Artificial General Intelligence: Logic, Autonomy, Resilience, Integrity, Morality, Emotion, Embodiment, and Embeddedness. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 12177 LNAI (Issue Section 2, pp. 242–251). https://doi.org/10.1007/978-3-030-52152-3_25
  27. Mezzanotte, F. E. (2020). An examination into the investor protection properties of robo-advisory services in Switzerland. Capital Markets Law Journal, 15(4), 489–508. https://doi.org/10.1093/cmlj/kmaa024
  28. Oh, E. Y. (2023). ChatGPT: how to use AI as a virtual financial adviser. The Conversation. https://theconversation.com/chatgpt-how-to-use-ai-as-a-virtual-financial-adviser-204207
  29. Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121–154. https://doi.org/10.1016/j.iotcps.2023.04.003
  30. Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1), 21. https://doi.org/10.1186/s41239-024-00453-6
  31. Zhou, J., Zhang, Y., Luo, Q., Parker, A. G., & De Choudhury, M. (2023). Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–20. https://doi.org/10.1145/3544548.3581318
  32. Zhu, H., Vigren, O., & Söderberg, I.-L. (2024). Implementing artificial intelligence empowered financial advisory services: A literature review and critical research agenda. Journal of Business Research, 174(December 2023), 114494. https://doi.org/10.1016/j.jbusres.2023.114494