In March 2025, Utku Dinc developed two core risk analytics features for the Julek-AK/AE2224-I-B04 repository, focusing on scalable risk interpretation and event-level review. Using Python and Pandas, Utku implemented threshold-based binary encoding to categorize risk levels, enabling rapid binary risk analysis and supporting faster decision-making for risk managers. He also engineered event-level risk aggregation by grouping data on event identifiers and compiling risk values into per-event lists, facilitating targeted analysis. The work emphasized performance optimization and robust data processing, laying a foundation for scalable risk monitoring. No bugs were fixed, as the month’s focus remained on feature delivery and workflow improvements.