Time Machine for Business and Finance: A New Suite of LLMs Unveiled at AMBS
A new suite of Large Language Models (LLMs) developed by researchers at Alliance ¼â½ÐÊÓƵapp Business School (AMBS) offers powerful tools for modelling historical business information.
The release of marks an exciting development, introducing the first suite of 68 historical pre-trained Large Language Models (LLMs) specifically designed for business studies. These models function like a time machine, allowing researchers to go back as far as 2007 to analyse historical information.
Developed over more than three years at Alliance ¼â½ÐÊÓƵapp Business School (AMBS) and the Centre for Financial Technology (FinTech) Studies, these models tackle complex challenges such as look-ahead bias and information leakage, setting a new standard for precision in accounting, finance, and related fields.
This release represents the largest specialised LLM suite to date in terms of the number of models developed. The pre-training process, which spanned a total of three months, underscores the level of effort invested in creating models that offer enhanced reliability for business studies.
Sustainability was a key priority throughout the development of FinText. In alignment with The ¼â½ÐÊÓƵapp's broader commitment to sustainability, all electricity used during the pre-training process was fully traceable and sourced exclusively from renewable energy, reinforcing our dedication to environmental responsibility.