Bordereaux Data Is Your Competitive Advantage
Stop leaving 50-75 basis points on the table to carrier data intelligence
Bordereaux is where premium, limits, loss experience, and policy-level economics live. It's the most granular picture of portfolio health. But most MGAs treat bordereaux as a compliance requirement—a file to send carriers quarterly. Pricing decisions get made without this data. Product strategy gets questioned without supporting analytics. Portfolio optimization happens ad hoc, missing systematic margin opportunities.
MGAs have competitive data advantage but use it only for reporting.
Where capacity bleeds today
The bottlenecks AI removes
Portfolio Health Signals Hide in Spreadsheets
Bordereaux lives in spreadsheets or carrier portals. Portfolio underperformance signals—specific classes underwriting poorly, geographies showing claim frequency creep, line-of-business margin erosion—stay invisible until someone manually compares year-over-year summaries. By then, margin damage is baked in. Real-time portfolio monitoring requires querying data faster than manual analysis allows.
Pricing Decisions Get Made in a Vacuum
Underwriters price new placements based on individual risk data, not portfolio context. They don't know if the class they're pricing has already deteriorated, if the geography is showing frequency trends, or if similar risks have claimed heavily. Pricing should reflect portfolio experience, not just the current risk profile. Without that context, MGAs under-price and over-retain simultaneously.
Product Strategy Stays Hard to Justify
Product decisions—which classes to write, which geographies to expand, which lines to exit—get made on intuition or carrier feedback, not MGA portfolio data. Can you justify your current class mix to your carrier using your own bordereaux analysis? Most MGAs can't. That lack of data costs them negotiating power and rate leverage.
AI Bordereaux Analytics MGA Surfaces Portfolio Performance Patterns
Bastion's Vault queries bordereaux in real-time, surfacing class-level margins, geographic performance trends, and line-of-business profitability. Portfolio underwriting summary updates monthly, showing where losses are concentrating. Pricing analytics surface class and geography risk profiles, feeding into new business underwriting. Product strategy gains quantified trade-offs (margin vs. volume). Data-driven decisions replace guesswork.
AI bordereaux analytics turns portfolio data into pricing advantage.
| Dimension | Before AI | After AI |
|---|---|---|
| Portfolio Data Accessibility | Bordereaux in spreadsheets; quarterly summaries only | Real-time portfolio queries; daily performance updates |
| Class-Level Profitability Visibility | Annual summaries; margin trends hidden | Monthly class profitability; trend alerts when deteriorating |
| Geographic Performance Tracking | Premium aggregated; loss concentration invisible | Geographic loss ratios and frequency trends visible |
| Pricing Decision Context | Individual risk data only; portfolio trends ignored | Class and geography performance guides pricing decisions |
| Product Strategy Justification | Intuition; carrier feedback only; no MGA data analysis | Portfolio trade-off analysis; margin vs. volume quantified |
Portfolio analytics visibility eliminates margin leakage and improves strategic pricing. Margin floor improves from 45% ceiling to 38% realized floor.
Where this sits in the $84B pool
$30.8B of MGA revenue is AI-compressible. Each bar is an activity — width is revenue share, height is operating margin. This workflow sits where the bar lands. Click any other to explore it.
Co-operate, not consult
We take position in the workflows we automate.
MGA margin sits in intake velocity, underwriting triage, and claims throughput. We run these — not map them. Our economics are equity in the margin you recover, not retainer on the analysis.
Talk to a principalThe full $84B pool
See where the MGA margin moves.
Map every activity — width is revenue share, height is operating margin. Click any bar to explore that workflow.
View the profit poolHow often do MGAs analyze portfolio performance by program and line today?
Most MGAs analyze portfolio performance annually, with quarterly carrier reporting. That's 4 snapshots per year to detect margin deterioration. By the time a problem emerges in quarterly data, the damage is already 2–3 months old. Real-time analysis would catch deterioration within days, allowing course correction before margin erodes. Current cadence means MGAs leave 50–75 basis points on the table.
What portfolio optimization opportunities does bordereaux analytics reveal?
AI bordereaux analytics reveals classes with margin upside (low-frequency, high-premium subsets worth pursuing), geographies with frequency trends (concentrate or exit decisions), and line-of-business trade-offs (premium growth vs. margin preservation). It also surfaces pricing opportunities—identifying which classes can support higher rates based on portfolio experience. Most MGAs discover these opportunities late or not at all.
How does real-time portfolio analytics drive quarterly pricing and product strategy?
Real-time analytics feed quarterly business reviews with quantified data: class profitability, geographic trends, and loss patterns. Underwriting guidance becomes data-driven rather than anecdotal. Pricing decisions get validated against portfolio experience. Product strategy gains trade-off analysis—if you exit a low-margin class, what happens to portfolio diversification? Analytics make those conversations concrete instead of theoretical.