The news: Bloomberg has unveiled a generative artificial intelligence model aimed at using machine learning to carry out tasks in the finance industry.
Here’s how it works: The company claims that BloombergGPT outperforms rival models on financial natural language processing tasks by “significant margins.”
- The AI platform is trained on a wide range of financial data based on Bloomberg’s extensive proprietary data sources.
- BloombergGPT is aimed at helping with tasks including analysis, news classification, and answering questions. It will be built into Bloomberg Terminals, assisting users with searching for and understanding data.
- In an accompanying research paper, Bloomberg outlined how the platform was trained and expanded on its limitations and ethical considerations.
Why it could succeed: Self-proclaimed “financial data company” Bloomberg can harness the vast amount of proprietary information available on the Bloomberg Terminal to benefit the firm’s customers and to become an early leader of generative AI software in finance. The company’s exclusive access to this data gives it an advantage over competitors.
The brand’s reputation for innovation and relative market dominance also will likely inspire a level of consumer trust in its products that rival AI startups can’t match.
Finance is generative AI’s next frontier: The runaway success of ChatGPT has shown the wide range of impacts that AI can have for consumers and businesses. So far, finance has been less affected by the tech, but BloombergGPT could gain first-mover advantage in the finance sector before more companies launch platforms.
As AI improves and companies invest in the tech, expect its impact on financial services to grow. It could improve efficiency, strengthen customer service, and cut long-term costs across banking, accounting, and payments. A major focus for firms should be on what AI can’t do and where its use is limited, such as in decision making and for compliance.
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