Leveraging AI and software engineering for ESG insights

Leveraging AI and software engineering for ESG insights

ClearPoint GM - Microsoft Engineering Malen Hurbuns presented on AI and ESG at the IBR 6th annual Fundtech Conference in Sydney last week. 

The 2023 Fundtech Conference focused on the future of super fund innovations – emerging and disruptive technologies. It aimed to highlight the latest developments and future trends in innovation and technology, relevant to Australian Superfunds as they face a challenging period of increased regulatory scrutiny, competition, investment complexity, and heightened member expectations. 

Malen's presentation centred on leveraging AI and software engineering for ESG insights, as he explored the topics below. 

  • Introduction to Large Language Models: The AI-ESG Nexus
  • Prompt Engineering: Fine-Tuning Conversations for ESG Objectives
  • Azure Open AI Services: A Platform for Scalable ESG Solutions
  • Enterprise ChatGPT for ESG Inquiry: From Questions to Actionable Insight


He took the audience through a live demo of an enterprise-grade GPT system tailored to respond to ESG queries extracted from PDFs. The system harnessed multiple Azure Services, including Azure Cognitive Search and Azure OpenAI models. It was deployed on Azure using a proprietary GPT-4 model, and he evaluated its performance against that of a GPT-3.5 model. 

"AI solutions are perfect for organisations looking to solve manual repetitive processes – while handling scale. When dealing with a larger number of files, the search services find the files in a short amount of time and then pass the summarisation to the model," says Malen. 

"LLMs are perfect for comparing data, and by utilising a private GPT model, organisations can ensure their data is secure and not shared with the public."

Get in touch to explore how we can help you find practical ways to leverage AI and use LLM in your business so you can make the most of the opportunities these new technologies offer and add real value to your business.

 

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