The Transformation of Artificial Intelligence in the Financial Industry: An Opportunity for Developing Economies

Document Type : Policy Note

Author

Visiting Scholar at Stanford University, AIx2 Founder & CEO

Abstract

Artificial Intelligence can present a unique opportunity for developing economies, which often face capital shortages. On one hand, it can facilitate attracting investments, and on the other, it can increase investment returns. In the transformative landscape of venture capital, AI emerges not only as an investment opportunity but also as a transformative tool that redefines investment strategies and the operational efficiency of investment funds. Leading investment funds such as A16Z, Sequoia, and Capital Tiger leverage AI to not only improve their processes but also to discover hidden gems in the vast sea of investment opportunities. This novel approach to AI, using it to find investment opportunities for developing economies like Iran, presents an opportunity to attract foreign investment and invest in better positions. Therefore, macro-policies should be geared towards creating the necessary platforms for using AI to discover investment opportunities. This issue consists of four pillars: providing the necessary data, enabling data processing with AI to find suitable investment opportunities, upgrading the daily operations of funds, and providing effective signals to foreign investors to find a local partner. Additionally, the investor should provide the opportunity to use this technology for funds by defining appropriate rules for AI, including data privacy. The policymaker can actively participate in the formation of an investment database and the production of local software for fund operations to accelerate the use of AI for investment funds.

Keywords

Main Subjects


[1] McKinsey & Company. (2023). Private Markets Turn Down The Volume: Mckinsey Global Private Markets Review 2023. McKinsey & Company. https://www.mckinsey.com/industries/private-capital/our-insights/mckinseys-private-markets-annual-review-2023
 [2] Predin, J. M. (2024). Venture Capital’s New Era: AI’s Journey From Enhancing Operational Efficiency To Alpha Generation.
[3] Walker, D. (2023). Will AI Compromise Security For Institutional Investors? Chief Investment Officer. https://www.ai-cio.com/news/will-ai-compromise-security-for-institutional-investors/
[4] MacArthur, R. B. H., Rose, G., De Vusser, C., Yang, K., & Lamy, S. (2023). Private Equity Outlook In 2023: Anatomy Of A Slowdown. Bain & Company. https://www.bain.com/insights/private-equity-outlook-in-2023-anatomy-of-a-slowdown/
[5]           Savi, R. B. H., & Tsaig, Y. (2023). How AI Is Transforming Investing. BlackRock Systematic Investing. https://www.blackrock.com/us/individual/insights/ai-investing
[6]           Bi, S., & Lian, Y. (2024). Advanced Portfolio Management In Finance Using Deep Learning And Artificial Intelligence Techniques: Enhancing Investment Strategies Through Machine Learning Models. Journal of Artificial Intelligence Research, 4(1), 233-298. https://thesciencebrigade.com/JAIR/article/download/226/271/587?utm_source=chatgpt.com
[7] Nazareth, N., & Reddy, Y. V. R. (2023). Financial Applications Of Machine Learning: A Literature Review. Expert Systems with Applications, 219, 119640.
[8] Cheratian, I., Goltabar, S., Gholipour, H. F., & Farzanegan, M. R. (2024). Finance And Sales Growth At The Firm Level In Iran: Does Type Of Spending Matter? Research in International Business and Finance, 67, 102142. https://doi.org/10.1016/j.ribaf.2023.102142
[9]           Klein, K. (2020). Why the growth of impact investing depends on data. Knowledge at Wharton. [10]       Retterath, A. (2023). Data-driven VC Landscape. Earlybird Venture Capital. Retrieved from https://www.earlybird.com/insights/data-driven-vc-landscape
[11]         Hansen, K. B., & Souleles, D. (2023). Expectations, Competencies And Domain Knowledge In Data- And Machine-Driven Finance. Economy and Society, 52(3), 421–448. https://doi.org/10.1080/03085147.2023.2216601
[12]         Lusardi, A., & Mitchell, O. S. (2023). The Importance Of Financial Literacy: Opening A New Field. Journal of Economic Perspectives, 37(4), 137–154. https://doi.org/10.1257/jep.37.4.137
[13]         Asgari Fard, A. (2023). Foreign investment in Iran review 2022. Mondaq. https://www.mondaq.com/inward-foreign-investment/1290726/foreign-investment-in-iran-review-2022
[14] Dong, Z., Xin, Z., Liu, D., & Yu, F. (2024). The Impact Of Artificial Intelligence Application On Company Environmental Investment In Chinese Manufacturing Companies. International Review of Financial Analysis, 95, 103403. https://doi.org/10.1016/j.irfa.2023.103403
[15]         Lv, Z., Wang, N., Ma, X., Sun, Y., Meng, Y., & Tian, Y. (2022). Evaluation Standards Of Intelligent Technology Based On Financial Alternative Data. Journal of Innovation & Knowledge, 7(4), 100229. https://doi.org/10.1016/j.jik.2022.100229
[16]         Cheng, Y., & Tang, K. (2024). GPT's Idea Of Stock Factors. Quantitative Finance, 24, 1–26. https://doi.org/10.1080/14697688.2024.2318220
[17] Lutz, E. S. A. (2022). Motherbrain Will Be The Backbone Of The Investment Lifecycle. PE Hub Europe.
[18] Cao, L., von Ehrenheim, V., Berghult, A., Henje, C., Stahl, R. A., Wandborg, J., Stan, S., Catovic, A., Ferm, E., & Ingelhag, H. (2023). A Scalable And Adaptive System To Infer The Industry Sectors Of Companies: Prompt + Model Tuning Of Generative Language Models. arXiv preprint arXiv:2306.03313. https://doi.org/10.48550/arXiv.2306.03313
[19]         Mendoza, C. (2023). Are you ready for the private equity GPT revolution? Private Equity International. https://www.privateequityinternational.com/are-you-ready-for-the-private-equitygpt-revolution/
[20] Wu, A. (2024). Improving Realty Management Ability Based On Big Data And Artificial Intelligence Decision-Making. PLOS ONE, 19(8), e0307043. https://doi.org/10.1371/journal.pone.0307043
[21] Adjodah, D., Leng, Y., Chong, S. K., Krafft, P. M., Moro, E., & Pentland, A. (2021). Accuracy-Risk Trade-Off Due To Social Learning In Crowd-Sourced Financial Predictions. Entropy, 23(7), 801. https://doi.org/10.3390/e23070801
[22]         Nishant, R., Nguyen, T., Teo, T. S. H., & Hsu, P.-F. (2024). Role Of Substantive And Rhetorical Signals In The Market Reaction To Announcements On AI Adoption: A Configurational Study. European Journal of Information Systems, 33(5), 802–844. https://doi.org/10.1080/0960085X.2023.2243892
[23] Moss, S. H., Liberman, B., & Danenhauer, G. (2022). Alternative Data: The New Oil For The Digital Economy? Lowenstein Sandler. Retrieved from https://www.lowenstein.com/media/11867/2022-alternative-data-report-final.pdf
[24]         Rasouli, M., Chiruvolu, R., & Risheh, A. (2023). AI For Investment: A Platform Disruption. arXiv preprint arXiv:2311.06251. Retrieved from https://arxiv.org/abs/2311.06251