The Growing Importance of AI/ML in Actuarial Work

In the rapidly evolving field of actuarial work, the use of artificial intelligence and machine learning (AI/ML) is gaining significant importance. This article delves into the findings of a research survey and interviews conducted by the Government Actuary’s Department (GAD) on behalf of the Financial Reporting Council (FRC). It explores the various applications of AI/ML techniques in actuarial work and highlights the risks and benefits associated with their use.

Applications of AI/ML in Actuarial Work

Explore the diverse applications of artificial intelligence and machine learning techniques in actuarial work.

Artificial intelligence and machine learning techniques are revolutionizing actuarial work across various fields. In the realm of General Insurance pricing, these techniques are used to determine claims risk for policyholders, forecast price-elasticity of demand for different policyholder groups, and inform the 'front-end' process for customers and policyholders. Additionally, AI/ML is being employed in other areas such as analyzing the impact of public health interventions, assisting pharmaceutical companies with patient profiling, and developing long-term economic projections.

Actuaries are applying more advanced AI/ML techniques to a wide range of use cases, expanding beyond the traditional fields of Pensions, General Insurance, Life Insurance, and Finance & Investment. This growing adoption of AI/ML in actuarial work is driven by the need for more accurate and efficient data analysis, enabling actuaries to make informed decisions and predictions.

The Growth of AI/ML in Actuarial Work

Examine the rapid growth and increasing awareness of artificial intelligence and machine learning in actuarial work.

The use of AI/ML techniques in actuarial work has witnessed significant growth in recent years. The survey conducted by the Government Actuary’s Department (GAD) revealed that awareness of ChatGPT, a Large Language Model developed by OpenAI, grew substantially during the research period. Interviewees highlighted the various ways organizations are utilizing AI/ML, including aiding process efficiency, assisting programming tasks, horizon-scanning, summarizing large volumes of text, and even developing bespoke in-house AI models for financial modeling.

As the adoption of AI/ML techniques continues to increase, actuaries are becoming more cognizant of the risks and benefits associated with these technologies. It is crucial for the actuarial profession to implement appropriate mitigations to ensure the responsible and ethical use of AI/ML in actuarial work.

Conclusion

The use of artificial intelligence and machine learning (AI/ML) techniques in actuarial work is rapidly growing and becoming increasingly important. From General Insurance pricing to analyzing public health interventions, AI/ML is being applied in diverse areas, revolutionizing the field of actuarial work. Actuaries are leveraging advanced AI/ML techniques to enhance data analysis and make more accurate predictions.

However, with the growth of AI/ML in actuarial work, it is crucial to be aware of the associated risks and implement appropriate mitigations. Actuaries must ensure the responsible and ethical use of AI/ML to maintain the integrity of their work and protect the interests of policyholders and customers.