LLM / NLP in Banking & Payments
9 companies using llm / nlp technology in the banking & payments sector. Large language models for NLP, chat, document understanding, and text generation
Directory
Companies by Funding
OpenAI
ChatGPT powers many fintech applications
Anthropic
Claude used in finance applications
Highradius
AI treasury and receivables platform
Glia
AI-powered digital customer service
Kasisto
KAI-GPT banking-specific LLM
Google DeepMind
AlphaFold methodology applied to finance
Posh Technologies
AI assistants for credit unions
Abe AI
AI voice assistant for finance
Related
Other AI Technologies in Banking & Payments
Related
LLM / NLP in Other Segments
Frequently Asked Questions
How is LLM / NLP used in banking & payments?
Large language models for NLP, chat, document understanding, and text generation In the banking & payments sector, LLM / NLP is applied by 9 companies tracked by AIFI Map, with $86.0B in combined funding. Leading companies include OpenAI (ChatGPT powers many fintech applications); Anthropic (Claude used in finance applications); Highradius (AI treasury and receivables platform).
Which banking & payments companies use LLM / NLP?
The AIFI directory tracks 9 banking & payments companies using LLM / NLP, with a combined $86.0B in funding. OpenAI, Anthropic, Highradius, Glia, Kasisto, and 3 more. (Source: AIFI Map directory.)
What is the most funded LLM / NLP banking & payments company?
OpenAI is the most funded company using LLM / NLP in banking & payments, with $57.9B raised. ChatGPT powers many fintech applications Followed by Anthropic ($27.3B).
How does LLM / NLP compare to other AI technologies in banking & payments?
In the Banking & Payments segment, LLM / NLP ranks #2 out of 6 AI technologies by adoption, with 9 companies and $86.0B in combined funding. The most widely adopted technologies in banking & payments are Predictive ML (19 companies, $17.2B funded); LLM / NLP (9 companies, $86.0B funded); Computer Vision (7 companies, $59.1B funded). While LLM / NLP focuses on large language models for nlp, chat, document understanding, and text generation, alternative approaches include Predictive ML, which traditional ml algorithms for classification, regression, and scoring models, and Computer Vision, which image and video processing, ocr, and document extraction.