"Instead of training models on internet-scale text with no regard for context, FinLLM is tuned specifically for the language, regulation, and products of financial services. That means when it analyses affordability, reviews a call for conduct, or drafts a suitability letter, it draws on a model designed to interpret the nuances of financial services, rather than offer a best guess."
"The bank has been testing FinLLM in its audit team where an audit chatbot virtual assistant developed by the group audit & conduct investigations (GA&CI) at Lloyds Banking Group is transforming how auditors access and interact with audit intelligence. The chatbot integrates generative AI with the group's internal documentation system, Atlas, making information retrieval faster, smarter, and more intuitive. Ranil Boteju, chief data and analytics officer at Lloyds Banking Group, says the bank effectively trained the chatbot using FinLLM"
FinLLM is a language model tuned specifically for financial services language, regulation, and products to produce explainable, context-aware outputs for tasks like affordability analysis and suitability letters. Aveni developed the model with support from Edinburgh Innovations and tailored training data to financial services rather than internet-scale text. Lloyds Banking Group has integrated FinLLM into an audit chatbot in its GA&CI team, connecting generative AI with the group's Atlas documentation to speed and improve information retrieval. The chatbot was trained on the bank's audit data to leverage domain knowledge. Strict explainability and error-free performance remain essential in regulated financial services.
Read at Computerweekly
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