ML enabled Risk Identification & Assessment in Child Exploitation

This project aims to significantly advance risk assessment practices in public and private sector organisations by applying machine learning techniques to the analysis of big data.In collaboration with the police and wider agencies supporting the local safeguarding children's board, this project will create disruptive algorithms to power STRIAD, our cloud-based data-driven risk assessment platform.This project will address a use case that focuses on the computation of risk and vulnerability which is pivotal to protecting young people exposed to the threats of sexual and criminal exploitation and to identify those likely to reoffend.STRIAD will be easily accessible, adaptable and scalable and will boost inter-agency cooperation, allowing organisations to pool data in an ethical, secure and privacy-considerate manner, enabling ground-breaking analysis and rapid identification of risk.Advanced data-driven risk identification and risk assessment results in informed service budget planning, and optimized allocation of resources. Most of all, it empowers early intervention and reduces the likelihood of harm to the most vulnerable in society.