Design and prototype an solution thatcombines web scraping, sentiment analysis, and machine learning.
In partnership with BSP and SEC Philippines, DTS (via the Cambridge SupTech Lab) developed a working prototype that enhances supervisory intelligence using data from public domains such as social media, news sites, and app-store reviews.
Key elements of the project included:
• SupTech design sprint and diagnostic: Identified supervisory challenges, manual bottlenecks, and priority use cases for consumer protection.
• Global vendor competition: Selected Winnow Technologies to co-develop an advanced analytics solution through a lean procurement process.
• AI-driven prototype: Delivered a system that automates data scraping, applies natural language processing and machine learning for sentiment analysis and topic modelling, and visualises results via interactive dashboards.
• Data integration: Connected public data streams with internal complaints management systems, improving early detection of misconduct and consumer risks.
• Future-proof architecture: Ensured flexible deployment (on-premises, cloud, or hybrid) with open data models, avoiding vendor lock-in and enabling future scalability.
This project demonstrates how SupTech innovation can move agencies from reactive to proactive supervision, helping them allocate resources more effectively, detect emerging risks early, and shape better-informed consumer protection policies.
