DeepSeek, a Chinese AI company, has released open-source language models matching OpenAI's performance, shaking up the AI landscape. For life insurers, embracing open models allows cost-effective customization while ensuring data privacy and regulatory compliance.
The Chinese company DeepSeek took the world by surprise Jan. 20 with the release of its multimodal large language models (LLMs) DeepSeek-R1 and DeepSeek-R1-Zero, providing performance on par with OpenAI’s o1 model.
These models leverage an open architecture with 671 billion total parameters. DeepSeek – solely funded by Chinese hedge fund High-Flyer and founded by Liang Wenfeng in Hangzhou, Zhejiang – has rapidly emerged as a major player in artificial intelligence (AI) research.
DeepSeek V3, released in December 2024, is a “standard” language model akin to OpenAI’s GPT-4. In contrast, the recently launched R1 is a reasoning model, comparable to OpenAI’s o1. China has been steadily advancing in AI research, producing high-quality models such as the Qwen family, developed by Alibaba. The intense competition in China has led to a price war, significantly reducing the cost of LLM hosting and fostering rapid innovation
At least two significant geopolitical factors have driven China’s accelerated AI innovation:
While these developments have raised considerable concern among Western tech companies, Yann LeCun, Meta’s Chief AI Scientist, recently Tweeted: "To people who think China is surpassing the US in AI, the correct thought is open-source models are surpassing closed ones." This distinction is particularly important for the insurance industry, where transparency, interpretability, and cost-efficiency are key factors in AI adoption.
Closed LLMs – such as OpenAI’s GPT models, Google’s Gemini, Anthropic’s Claude, and AWS’s Titan – keep their training data, architecture, and weights proprietary. They are only accessible via APIs, meaning insurance companies cannot audit the inner workings of these models, raising concerns about data privacy, compliance, and explainability.
Open-source models – including Meta’s Llama, Mistral, and DeepSeek’s offerings – provide access to the trained weights, allowing companies to deploy and fine-tune models on their own infrastructure. This transparency enhances compliance, particularly in regulated industries such as insurance.
For life insurers, extracting insights from unstructured medical data is a crucial challenge. Underwriting processes often rely on vast amounts of medical history, physician notes, and diagnostic reports. While general-purpose LLMs can perform well in these tasks, fine-tuning a domain-specific model can be significantly more cost-effective than relying on expensive API-based closed models.
With open models, life insurers can fine-tune AI to their specific underwriting needs while ensuring compliance with industry regulations such as HIPAA and GDPR. Advances made training V3 with 5% of the normal number of GPUs normally used will make fine-tuning and training more affordable for all companies. Running models in a secure environment allows for full data control, unlike using third-party APIs, where data handling is dictated by external providers.
One of the most critical considerations for insurance companies adopting AI models is data security. Running an open model on-premises or with a trusted cloud provider (AWS, GCP, Azure) ensures complete control over sensitive policyholder data. In contrast, using an external API requires scrutiny of the provider’s terms of service.
The rise of open AI models presents a transformative opportunity for life insurers. By embracing open-source LLMs, insurers can reduce costs, enhance accuracy, and maintain control over sensitive data. DeepSeek’s advances illustrate that cutting-edge AI might no longer be confined to closed ecosystems and that open innovation is rapidly leveling the playing field.
As insurers navigate the evolving AI landscape, the strategic adoption of open models will empower them to harness the full potential of generative AI while safeguarding data privacy, improving operational efficiency, and driving business growth. The future of insurance AI is open, and forward-thinking companies will be the ones to capitalize on this shift.
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