Log in / My SOA

Artifical Intelligence in Investment and Retirement

July 2025

Author
Kailan Shang, FSA, MAAA, ACIA, CFA, PRM

Executive Summary

Artificial intelligence (AI) is increasingly shaping the fields of investment and retirement planning by enhancing data-driven decision-making, improving efficiency, and automating complex processes. With advancements in reinforcement learning and large language models, AI applications are expanding in portfolio management, sentiment analysis, risk assessment, and personalized financial planning. However, as AI adoption grows, it is important to consider both its benefits and challenges to support responsible and effective implementation. This report provides an overview of AI applications in the investment and retirement sectors, offering insights for professionals exploring ways to leverage AI while managing associated risks.

Insights and Benefits of This Report

This report serves as a resource for financial professionals and technology experts interested in AI’s role in investment and retirement planning. It is intended to provide an understanding of the following:

  • How AI may be applied in investment and retirement planning, including portfolio optimization, sentiment analysis, risk management, and personalized financial guidance.
  • The fundamental principles of AI technologies such as large language models and reinforcement learning, with a focus on their relevance to financial decision-making.
  • The risks that may arise from AI applications, including biases, cybersecurity threats, ethical considerations, and regulatory compliance, along with potential strategies for mitigating them.
  • Real-world examples illustrating AI-driven solutions in financial services, such as reinforcement learning for retirement savings, chatbot development, and AI-assisted portfolio management.
  • Considerations for integrating AI while promoting transparency, fairness, and accountability.

The report is structured to accommodate readers with different interests and varying levels of technical expertise. Those seeking a broad understanding of AI’s role in investment and retirement planning may focus on Section 2, which discusses AI applications in financial decision-making, risk management, customer services, and portfolio optimization. Readers concerned about the risks of AI implementation may refer to Section 4, which outlines AI risk management and mitigation strategies.

For those with a more technical background, Section 3 provides an overview of AI methodologies, including data processing, model training, and reinforcement learning, and involves some technical discussions. Section 5 is also intended for technical readers, as it explores AI-driven solutions with practical case studies, including reinforcement learning for retirement savings, chatbot development for financial insights, and AI-assisted portfolio management. In addition, most of the appendices are designed strictly for technical readers, offering in-depth discussions on advanced AI methodologies and implementation details.

Material

Artificial Intelligence in Investment and Retirement

Acknowledgements

The author would like to thank all members of the Project Oversight Group (POG) tasked with providing governance on this research project. This paper would not have attained its current level of relevance to practitioners without the POG’s guidance, feedback, and insightful input.

Project Oversight Group Members:

  • Gavin Benjamin, FSA, FCIA
  • Alfred Chong, ASA
  • Nancy Ning, FSA, CERA, FCIA
  • Eloise Page, FSA, EA
  • Shisheng Qian, FSA, CERA
  • Anna Rappaport, FSA, MAAA
  • Andrew Samuels, FSA, MAAA
  • David Schraub, FSA, MAAA, CERA, ACA, AQ
  • Andrea Sellars, FSA, MAAA
  • Matthew Smith, FSA, MAAA
  • Cavan Stackpool, FSA, MAAA, CERA
  • Peik Hong Tan, FSA
  • Pierre Tournier, FSA, CERA

At the Society of Actuaries Research Institute:

  • Steven Siegel, ASA, MAAA, Senior Practice Research Actuary
  • Barbara Scott, Senior Research Administrator

Questions or Comments?

Give us your feedback! Take a short survey on this report. Take Survey

If you have comments or questions, please send an email to Research@soa.org