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<p>Institutional investors are looking for opportunities that will have a positive social and environmental impact as well as positive returns. Compared to the largely speculative trading in equity markets and financial markets, this is a significant change. Investing with impact requires a long-term perspective. Impact investments are becoming increasingly popular as governments expect institutional investors to contribute to the achievement of UN sustainable development goals by 2030. Several characteristics are included in these goals, including environmental sustainability, social inclusion, integration, competitiveness, and resilience. In this paper, new AI methods are presented that utilize network theory, complex fitness dynamics of networks, and machine learning techniques for sourcing investments more effectively and forecasting their likely impact more accurately. The paper discusses ethical considerations and safeguards that should be observed when deploying artificial intelligence for impact investment.</p>

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Beyond arbitrage: machine learning for financing impactful economic activity

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月12日

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  • Dalila Benachenhou,
  • Masud Cader,
  • Dario Mazzilli,
  • Andrea Tacchella

摘要

Institutional investors are looking for opportunities that will have a positive social and environmental impact as well as positive returns. Compared to the largely speculative trading in equity markets and financial markets, this is a significant change. Investing with impact requires a long-term perspective. Impact investments are becoming increasingly popular as governments expect institutional investors to contribute to the achievement of UN sustainable development goals by 2030. Several characteristics are included in these goals, including environmental sustainability, social inclusion, integration, competitiveness, and resilience. In this paper, new AI methods are presented that utilize network theory, complex fitness dynamics of networks, and machine learning techniques for sourcing investments more effectively and forecasting their likely impact more accurately. The paper discusses ethical considerations and safeguards that should be observed when deploying artificial intelligence for impact investment.