UBS

Problem

Client conversations contain key pieces of information, but manually analyzing transcripts or meeting notes to extract actionable insights is time-consuming and prone to error. For this challenge, we invite participants to develop a solution that leverages Gen AI to automatically analyze conversation transcripts and extract key pieces of information. The goal is to empower client advisors with concise, accurate, and actionable insights, helping them save time and better serve their clients. The solution should be capable of: Extracting specific information, such as client requests, and agreed-upon actions. Ensuring accuracy and relevance, even in the presence of noisy or incomplete data.

Why hack?

This challenge offers a unique opportunity to work on cutting-edge Generative AI technologies in a domain with real-world impact. By participating, you will: Contribute to shaping the future of client interaction in banking. Gain valuable experience in NLP, information extraction, and working with financial-domain challenges. Explore the trade-offs between performance and cost in AI model selection.