ContributedThis content is contributed or sourced from third parties but has been subject to Finextra editorial review.Chinese LLM developer DeepSeek has the potential to forge more efficient, secure and personalised financial services at a fraction of
their current costs. Reuters reported this week that while
Europe has struggled to keep pace with the US in regards to AI, a low-cost LLM alternative could help democratise this technology.Bernstein analysts have estimated that DeepSeek’s pricing is 20 to 40 times cheaper than equivalent models from
OpenAI. “OpenAI charges $2.5 for 1 million input tokens, or units of data processed by the AI model, while DeepSeek is currently charging $0.014 for the
same number of tokens,” the article read.While these cost savings are substantial, and innovative engineering techniques are leveraged rather than relying on large computational resources, fintech startups now have a new avenue to compete with larger firms. Here’s everything you need to know about
DeepSeek and its impact on fintech.Why is DeepSeek in the news?DeepSeek is currently being investigated for replicating OpenAI data and censoring negativity against China by a number of European countries, while at the same time, US President Donald Trump unveiled
Stargate, a $500 billion AI project in collaboration with OpenAI, Softbank and Oracle.The Chinese organisation, although having launched in 2023, has recently dominated headlines after it revealed that DeepSeek’s V3 required under $6 million worth of computing power from
Nvidia H800 chips
– not their most advanced chips. Since then, DeepSeek has overtaken ChatGPT as the most popular productivity application.Benefits of DeepSeek on the fintech industryDavid Krause, emeritus professor, finance department, Marquette University in Wisconsin, published a
paper
last week on the democratisation of AI and its global implications. He highlights that these new developments have welcomed a “new paradigm in fintech by making high-performing AI models accessible at significantly lower costs.”Krause lists the key aspects of DeepSeek’s potential:Cost-Effectiveness: “DeepSeek-R1 delivers performance comparable to GPT-4 but at a fraction of the cost, developed for just $6 million compared to GPT-4’s $100 million.”
Open-Source Collaboration: “DeepSeek fosters wider access to advanced AI tools, encouraging collaboration and innovation within the global AI community.”
Efficient Engineering: “DeepSeek’s innovative design, including multi-head latent attention (MLA) and mixture of experts (MoE) architectures, minimises computational requirements while maintaining high performance.”
Strategic Research Focus: “DeepSeek’s ‘reasoning’ model, designed to compete with a state-of-the-art offering by OpenAI, engages in self-dialogue before answering a query, a process that enhances the quality of its responses but also incr
