Actuarial Profession Finds Potential in Advanced Law Degrees
The Society of Actuaries Research Institute (SOA) recently convened a panel of experts to discuss the potential of generative AI, particularly Large Language Models (LLMs), in the insurance industry.
The SOA's AI Research landing page offers a wealth of resources for those interested in this cutting-edge technology, including the monthly Actuarial Intelligence Bulletin.
Implementing LLMs into insurance systems presents challenges, such as data privacy and security, regulation compliance, and ethical standards. To address these issues, deploying LLMs requires assistance from cloud engineers and software developers, as it falls outside typical actuarial training and expertise.
There are four basic variants of LLMs: foundational models, instruct models, code models, and multimodal models. The choice of an LLM for a specific task depends on factors like model size and computational requirements, task-specific performance, context window size, and cost vs. performance.
The cloud offers a simpler solution for LLM location compared to building an independent server. This is particularly beneficial for insurance companies looking to leverage the power of LLMs without the overhead of server maintenance.
The panel noted several applications of LLMs in insurance, including coding assistance, digital assistant, data summarization and categorization, testing and model validation assistance, translation, research source attribution, and claims integration.
When choosing an LLM provider, it's crucial to ensure they meet stringent security and privacy standards. Leading companies in this field include Google, Microsoft, IBM, Amazon Web Services, NVIDIA, and OpenAI, creator of ChatGPT.
Key provider considerations include privacy and protection, risk and compliance, technology and reliability, bias, fairness and discrimination, transparency and explainability, accountability and responsibility.
Using an LLM is often facilitated through an API from major developers like ChatGPT. However, deploying an LLM independently offers more control, although it can be more complex and costly.
Actuaries have key roles in the responsible and ethical use of AI and LLMs due to their expertise in risk management and governance. Risk and ethics considerations are essential in choosing LLMs for responsible actuarial use.
Current AI tools, such as LLMs, can boost productivity for some tasks, but they haven't evolved enough to replicate actuarial analysis and decision-making. The SOA Research Institute has published a detailed guide on deploying LLMs for actuarial use, titled "Operationalizing LLMs: A Guide for Actuaries".
In conclusion, while the integration of generative AI into the insurance industry presents challenges, it also offers exciting opportunities for improved efficiency and innovation. Actuaries play a crucial role in ensuring these technologies are used responsibly and ethically.
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