AI-Enhanced Due Diligence in Private Market Investments: Redefining Risk Assessment Frameworks
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V6I2P105Keywords:
Artificial Intelligence, Due Diligence, Private Markets, Risk Assessment, Machine Learning, Venture Capital, Private Equity, NLPAbstract
Traditional private market investment due diligence has been more of a conventional approach, which mainly involved a lot of analysis, estimations and discretionary work. Sometimes, the process was incomplete due to unreliable and scarce information. This interesting shift of focus in investing has been made possible by Artificial Intelligence (AI) and the subsequent changes it brings to the risk assessment of potential investments. This paper aims to provide a detailed analysis of how AI integration modifies the conventional approaches to risk assessment in private market investment. To start with, we discuss traditional models and their limitations and, thereafter, elaborate on the potential use and application of ML, NLP, and predictive analytics in due diligence. By adopting an AI-based multidimensional risk matrix model, this study stresses the prospects of better enhancement, effectiveness, and clarity in assessing startups, venture capital and private equity investments. This paper uses literature analysis, a sound research approach, various case studies, and metrics to evaluate the efficiency of the AI system compared to the previous approaches. The paper ends with such areas of future work and policy implications related to integrating AI into private investment strategies. The role of AI in changing due diligence further shows that it has a high economic and strategic value and improves investment fairness
References
[1] Board, F. S. (2010). The Basel Committee on Banking Supervision. Macroeconomic Assessment Group.
[2] Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future (Vol. 4, No. 1, pp. 1448-1476). New York: WW Norton & Company.
[3] Chen, M. A., Wu, Q., & Yang, B. (2019). How valuable is FinTech innovation? The Review of Financial Studies, 32(5), 2062-2106.
[4] Fang, L., Ivashina, V., & Lerner, J. (2015). The disintermediation of financial markets: Direct investing in private equity. Journal of Financial Economics, 116(1), 160-178.
[5] Gomber, P., Kauffman, R. J., Parker, C., & Weber, B. W. (2018). On the fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35(1), 220-265.
[6] Kelleher, J. D., Mac Namee, B., & D'arcy, A. (2020). Fundamentals of machine learning for predictive data analytics: algorithms, worked examples, and case studies. MIT Press.
[7] Lee, I., & Shin, Y. J. (2018). Fintech: Ecosystem, business models, investment decisions, and challenges. Business Horizons, 61(1), 35-46.
[8] Sironi, P. (2016). FinTech innovation: from robo-advisors to goal-based investing and gamification. John Wiley & Sons.
[9] Strusanis, D., & Houngbonon, G. V. (2019). The role of artificial intelligence in supporting development in emerging markets. International Finance Corporation, Washington, DC.
[10] Vianny, M. M., Ayyaswamy, K., Rithik, G., & Kathirvel, N. (2025). Private AI: An Overview. AI-Driven Breakthroughs in Antimicrobial Resistance, 299-324.
[11] Naim, A., Alahmari, F., & Rahim, A. (2021). Role of artificial intelligence in market development and vehicular communication. In Smart Antennas: Recent Trends in Design and Applications (pp. 28-39). Bentham Science Publishers.
[12] Owolabi, O. S., Uche, P. C., Adeniken, N. T., Ihejirika, C., Islam, R. B., Chhetri, B. J. T., & Jung, B. (2024). Ethical implication of artificial intelligence (AI) adoption in financial decision making. Comput. Inf. Sci, 17, 49-56.
[13] Kavitha, M., Hanumanthu, K. D., Sai, O. N., Chandrashekhar, G., & Sugandha, S. (2025). The Role of Artificial Intelligence in Financial Decision-Making. Journal of Marketing & Social Research, 2, 189-198.
[14] Huang, A. H., & You, H. (2023). Artificial intelligence in financial decision-making. In Handbook of Financial Decision Making (pp. 315-335). Edward Elgar Publishing.
[15] Qatawneh, A. M., Lutfi, A., & Al Barrak, T. (2024). Effect of Artificial Intelligence (AI) on Financial Decision-Making: Mediating Role of Financial Technologies (Fin-Tech). HighTech and Innovation Journal, 5(3), 759-773.
[16] Cao, L., Yang, Q., & Yu, P. S. (2021). Data science and AI in FinTech: An overview. International Journal of Data Science and Analytics, 12(2), 81-99.
[17] Dakalbab, F., Talib, M. A., Nasir, Q., & Saroufil, T. (2024). Artificial intelligence techniques in financial trading: A systematic literature review. Journal of King Saud University-Computer and Information Sciences, 36(3), 102015.
[18] 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.
[19] Lakhchini, W., Wahabi, R., & El Kabbouri, M. (2022). Artificial Intelligence & Machine Learning in Finance: A literature review. International Journal of Accounting, Finance, Auditing, Management and Economics.
[20] Baek, C. H., Kim, S. Y., Lim, S. U., & Xiong, J. (2023). Quality evaluation model of artificial intelligence service for startups. International Journal of Entrepreneurial Behavior & Research, 29(4), 913-940.
[21] Davalas, A., Charalabidis, Y., & Fenekoy, P. (2022). Startup Valuation with Artificial Intelligence: A SWOT Analysis. European Journal of Economics, 2(2), 13-20.
[22] Moro-Visconti, R. (2024). The Valuation of Artificial Intelligence-Driven Startups. In Artificial Intelligence Valuation: The Impact on Automation, BioTech, ChatBots, FinTech, B2B2C, and Other Industries (pp. 293-344). Cham: Springer Nature Switzerland.
