How AI Helps MGA Aggregators Move Past Bordereau Data

For most MGA aggregators, auditing their MGA members is a persistent challenge. The data they receive is typically limited to bordereau reports, which provide only a snapshot of bound business—and often several weeks out of date. 

This lack of real-time insights makes it difficult to assess underwriting quality, identify growth opportunities, or proactively mitigate risk. With AI-based tools, however, MGA aggregators can access a much broader range of performance data in real time, unlocking numerous benefits for themselves and their MGA partners.

Traditional Performance Data: Delayed and Incomplete

Most MGA aggregators face significant limitations when it comes to auditing their members’ performance.

• Aggregators primarily receive bordereau data, which only contains information on policies bound by their MGA partners. While this information is useful, it lacks critical insights into how those policies were written, and how much of overall underwriting activity they represent.
• Key underwriting funnel metrics—such as submission volume, quote ratios, and bind percentages—are often missing, making it difficult to gauge underwriting efficiency.
• Without visibility into the decision-making process, it can be difficult for aggregators to identify opportunities to help MGAs optimize their operations or refine their risk selection.
• The issue isn’t just on the aggregator’s side—many MGAs themselves lack real-time access to their own underwriting performance, further compounding the problem.

The end result? MGA aggregators are left operating reactively, unable to provide strategic support when it matters most.

AI Delivers Real-Time Insurance Portfolio Data

Artificial intelligence is revolutionizing insurance portfolio management, making it possible for both MGA aggregators and their members to access real-time performance data that was previously out of reach.

• Traditional reporting systems require extensive manual data aggregation and BI tool customization to stitch together relevant insights.
• AI, on the other hand, automates data collection and analysis, allowing it to track portfolio changes more quickly and comprehensively than humans could accomplish
• Federato’s RiskOps approach enhances visibility across the portfolio, providing insights not only into overall performance but also into the underwriting decisions driving portfolio outcomes.
• This level of transparency enables MGA aggregators to see the whole portfolio picture, including submission volumes, risk selection, and goal progress, and eliminates reliance on outdated, static reports.

How Real-Time Portfolio Data Helps MGA Aggregators

By leveraging AI-driven portfolio insights, MGA aggregators gain a competitive edge in multiple ways:

• Stronger MGA Partnerships – Real-time data enables aggregators to support their members proactively, identifying areas for growth or helping them get ahead of potential issues.
• Reduced Reporting Burden – MGAs no longer need to manually compile and submit cumbersome reports, as AI-driven platforms provide visibility into their underwriting activities for both their internal leadership and their aggregator partners.
• More Informed Growth Strategies – Aggregators can pinpoint high-performing MGA partners and allocate resources accordingly, while also identifying partners that may need additional guidance or support.
• Strengthened Reinsurance Negotiations – Up-to-date performance metrics allow aggregators to present reinsurers with clear, data-backed evidence that their MGA partners are executing strategies effectively and delivering results, giving them a strong position in negotiations.

Conclusion

For too long, MGA aggregators have had to make do with limited, delayed bordereau data. But with AI-powered real-time portfolio insights, they can now gain full visibility into underwriting performance, make proactive decisions, and strengthen their partnerships with MGA members. The ability to track portfolio health in real time not only improves operational efficiency but also enhances negotiating power with reinsurers—ultimately leading to better business outcomes for all stakeholders.

Learn more on how Federato helps MGA aggregators, or connect with us for a live demo today.

FAQs

1. What is bordereau data, and why is it limiting for MGA aggregators?

Bordereau data provides a summary of bound policies but lacks insights into underwriting funnel metrics, such as submission volume, quote rates, and underwriting quality. This makes it difficult for MGA aggregators to assess member performance effectively.

2. How does AI improve data visibility for MGA aggregators?

AI automates data collection and analysis, providing real-time insights into the entire underwriting process, from submission intake to policy issuance. This eliminates reliance on outdated, static reports.

3. Can AI help MGA aggregators improve partnerships with their MGA members?

Yes. With real-time performance data, aggregators can offer targeted support, identify growth opportunities, and reduce the reporting burden on their MGA members.

4. How does real-time data impact reinsurance negotiations?

Aggregators can present up-to-date portfolio performance metrics to reinsurers, demonstrating the effectiveness of their MGA partners and securing better coverage terms.

5. How does Federato’s RiskOps approach enhance portfolio management for MGA aggregators?

‍Federato’s RiskOps platform integrates real-time underwriting insights into the workflow, ensuring that MGA aggregators and their members have continuous visibility into portfolio health and underwriting trends.