EY India Launches Customised LLM for BFSI Sector
EY India has developed a customised, fine-tuned LLM tailored for BFSI applications. This AI-powered solution promises enhanced customer service, improved operational efficiency and optimised risk management. The LLM is designed to address the unique needs of the BFSI sector by improving answer accuracy, intent recognition and contextual comprehension. It incorporates BFSI-specific vocabulary, ensuring precise and dependable AI-driven solutions. The model is also equipped with multilingual capabilities. Powered by the fine-tuned Llama 3.1-8B instruct model, the AI solution leverages advanced parameter-efficient finetuning with low-rank adaptation techniques. This allows for deeper contextual understanding and better alignment with India’s BFSI regulatory frameworks. According to EY India, the model delivers measurable business benefits, including up to 50% cost savings. Mahesh Makhija, partner and technology consulting leader at EY India, said, “EY’s customised AI models are tailored to meet the specific needs of the BFSI sector, empowering banks to optimise operations, enhance risk management and make data-driven decisions.” The model is designed for flexible deployment, allowing BFSI organisations to host it either on-premises or in cloud environments with limited GPU requirements, significantly reducing costs. It can be integrated into customer service applications through text-based platforms such as WhatsApp, SMS and website chatbots, as well as voice-calling AI call center frameworks. Unlike other models, EY’s fine-tuned LLM prioritises security and regulatory compliance by being securely hosted within enterprise networks. This approach mitigates risks such as AI hallucinations and data privacy concerns, ensuring that sensitive information remains protected within organisational boundaries. Early this year, the company launched the EY.ai Global AI Advisory Council, which aims to deliver key insights into AI advancements, societal impacts and innovative applications, enabling the global EY network and its clients to remain at the forefront of AI developments.
The model delivers measurable business benefits, including up to 50% cost savings.
The model delivers measurable business benefits, including up to 50% cost savings.
["EY", "LLM"]
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["AI", "Aim", "RAG", "chatbots", "R", "GAN", "data-driven", "llm_models:Llama", "programming_languages:R"]
Merin Susan John is a journalist at Analytics India Magazine, reporting on the intersection of AI and human capital. She can be reached  at merin.john@aimmediahouse.com