Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

Research Article

Current Study and Method on Artificial Intelligent-based on Venture Capital Decision

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  • @INPROCEEDINGS{10.4108/eai.27-10-2023.2341962,
        author={Lanxi  Hu},
        title={Current Study and Method on Artificial Intelligent-based on Venture Capital Decision},
        proceedings={Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27--29, 2023, Tianjin, China},
        publisher={EAI},
        proceedings_a={ICEMBDA},
        year={2024},
        month={1},
        keywords={venture capital decision-making; artificial intelligence; evaluation of startups; optimization of investment portfolio},
        doi={10.4108/eai.27-10-2023.2341962}
    }
    
  • Lanxi Hu
    Year: 2024
    Current Study and Method on Artificial Intelligent-based on Venture Capital Decision
    ICEMBDA
    EAI
    DOI: 10.4108/eai.27-10-2023.2341962
Lanxi Hu1,*
  • 1: University of Southampton
*Contact email: lh6n22@soton.ac.uk

Abstract

Venture capital is an important driver of innovation and economic growth, however, the risks faced by investors cannot be ignored. This study aims to utilise artificial intelligence techniques to aid venture capital decision-making, introduces the definition and characteristics of venture capital, and discusses the challenges and difficulties faced by venture capital decision-making. An overview of the application of AI in venture capital decision-making is provided, with a focus on its specific application in startup evaluation. The application includes data collection and pre-processing, feature selection and modelling, model evaluation and optimisation, and provides an outlook on future research directions and trends. The results of the study show that AI technology has an important application prospect in venture capital decision-making, which can help investors better identify and evaluate high-risk projects and optimise their investment portfolios to reduce uncertainty and risk. However, there are limitations and shortcomings in this study, and future research can further explore other application areas of AI in venture capital decision-making.