Insurance Operations Dashboard
The Problem
Insurance operations teams discover client risk too late. A client who's likely to file a high-cost claim, cancel mid-term, or dispute coverage shows warning signs at intake — but those signals are buried across forms, call notes, and payment preferences that nobody synthesizes until there's already a problem.
Underwriting models handle pricing risk. What they don't handle is operational risk: which clients will consume the most ops resources, which will churn, and which need proactive intervention before they become a retention issue. Ops managers make these calls on gut feel, which means the quality of the decision depends entirely on who's working that day.
What We Built
A client risk scoring dashboard that evaluates every client at intake and assigns a risk score with a full breakdown of contributing factors — so ops teams know who needs attention before problems surface.
The system provides:
- •A risk score (0–100) and severity level for every client — Low, High, or Critical — visible in a single list view
- •Contributing factor breakdowns — not just a number, but the specific signals driving it. For example: "Immediate urgency correlates with higher risk: +15" or "Cash payment preference shows higher cancellation risk: +12" or "Prior insurance experience reduces risk: -12"
- •Actionable context — each factor comes with a direction (raises/lowers risk) and a magnitude, so an ops manager can see exactly what's driving a Critical score and decide on the appropriate intervention
- •A client list view — the full book sorted and scored, so managers can triage their day around the clients that actually need attention
The factor breakdown is the core value. A score of 84 means nothing on its own. A score of 84 driven by "cash payment preference +12, immediate urgency +15, no prior coverage +10" tells the ops team exactly what kind of risk this is and what to do about it.
How It Works
Client data flows in at intake — demographics, payment preferences, coverage history, urgency signals, inquiry behavior. The model scores the client in real time and surfaces the result in the dashboard with a full factor breakdown. Ops managers open the dashboard, see who's Critical, expand the row to understand why, and act.
See It in Action
A live client list with risk scores ranging from 10 (Low) to 93 (Critical). Expanding Brandon Smith's row (score 84, Critical) reveals the factor breakdown: immediate urgency +15, cash payment preference +12, prior experience -12.