An RSI Understanding Risk method
Data science
Broadly
Data science combines statistical analysis, machine learning, and domain knowledge to extract actionable insights from structured and unstructured data. In the context of risk understanding, it enables real-time surveillance, predictive modeling, and decision-support tool development. Key advantages include scalability, automation, and advanced pattern recognition. However, challenges include data governance, explainability, and risk of algorithmic bias.
More specifically
RSI applies data science to enhance its modeling, surveillance, and synthesis capabilities. The firm integrates open-source tools, custom scripts, and commercial platforms to analyze diverse datasets—including textual, geospatial, and time series data. RSI’s approach emphasizes transparency, reproducibility, and integration with domain knowledge to ensure data science outputs are not only innovative, but also responsible and relevant in high-stakes decision-making.