AI-Powered Search Tool Reduces Recommendation Time by 90% and Improves Search Relevance for Financial Platform
Before
An advanced technology platform that provides critical data for capital raising and M&A transactions needed to enhance its information delivery to banks and investors. The existing search tool struggled with processing large volumes of data efficiently, leading to slower recommendation times and lower relevance in search results, which impacted user experience.
Solution
Our team developed a sophisticated search tool by fine-tuning BERT models on a specialized financial and investment-related corpus. The solution included:
- Domain-Specific Named Entity Recognition (NER) Model: The fine-tuned BERT models were trained to identify relevant entities such as company names, financial figures, dates, and key individuals from a variety of sources including news articles, social media, and financial documents.
- Automated Data Processing: The identified entities were automatically piped into a structured database, ensuring that accurate and up-to-date information was delivered at scale to thousands of users without any manual intervention.
- GenAI Search Tool: The search tool leveraged the NER model to provide faster, more relevant search results, drastically reducing the recommendation time and improving user satisfaction.
This AI-powered solution enabled the Company to deliver high-quality, accurate information more efficiently, solidifying their platform as a go-to resource for banks and investors engaged in capital raising and M&A transactions.
Outcome
By integrating an AI-powered search tool, the platform dramatically improved the speed and relevance of its information delivery. The recommendation time was reduced from 30 seconds to just 3 seconds, with a 10% improvement in the relevance of search results, thereby enhancing the platform’s value to its users.
