The dataset contained intricate relationships between policies, coverages, and product lines, which produced many-to-many relationship issues across the model.
These unresolved relationships caused incorrect aggregations, leaving the Risk Advisory team with unreliable renewal and coverage reporting they could not act on with confidence.
Bridge tables were created to properly resolve the many-to-many relationships between policies, coverages, and product lines, restoring correct aggregations across the model.
Drill-through functionality was implemented to let the team move from high-level renewal trends into detailed, policy-level coverage analysis.
Renewal trends and upcoming expirations were surfaced in a single, consolidated view, giving the team clear visibility to prioritize and act before policies lapsed.
Row-Level Security (RLS) was applied so that each user accessed only the data relevant to their role and region.
RLS rules were mapped to Active Directory groups, automating access control and keeping sensitive renewal data restricted to authorized users.
50% Reduction in Manual Reporting Effort through automated dashboards.
20% Lower Missed Renewal Expirations driven by real-time trend and expiration.
Zero Cross-Region Data Exposure using RLS mapped to Active Directories.
