A data-driven look at how manual intake workflows drive adverse risk selection in a softening market, and why Agentic AI is the operational imperative for MGA leaders.
Underwriters spend 30–40% of their time on manual intake tasks, not underwriting.
Slow response time leads directly to adverse risk selection (“submission decay”).
MGAs that quote within 1 hour capture the best risks and grow faster.
Agentic AI removes the bottleneck by turning unstructured data into quote-ready packets in <60 seconds.
Following four years of double-digit growth that saw the sector surpass $100 billion in direct premiums written (DPW), the US MGA market is transitioning into a decisive phase of operational scrutiny.
While some specialty niches remain hard, the broader commercial lines sector is softening, with rates falling by 3% to 4% in the first half of 2025. This shift means MGAs can no longer rely solely on rate increases for revenue growth; they must increase submission volume. This pressure is exposing critical weaknesses in traditional, manual operational models.
The "Submission Bottleneck" is an operational crisis where an MGA’s inability to manually process incoming submissions caps revenue growth.
Despite digitalization efforts, commercial insurance relies on unstructured data—messy PDFs, inconsistently formatted Excel loss runs, and emails. When an MGA's intake process relies on humans to read, triage, and re-key this data, they cannot scale volume without linearly increasing headcount. In a softening market demanding higher volume, this bottleneck becomes the primary constraint on profitability.
Industry analysis indicates that skilled underwriters currently spend between 30% and 40% of their productive time on non-revenue-generating administrative tasks, primarily data entry and file preparation.
We classify this as the "Admin Tax." For an MGA with a team of 20 high-salaried underwriters, this statistic implies that eight full-time equivalents (FTEs) are effectively dedicated to data entry rather than risk analysis and broker negotiation.
In a crowded market of over 1,000 active MGAs, brokers prioritize partners who minimize friction. J.D. Power’s assessments consistently highlight that "quote turnaround time" is a paramount driver of carrier selection.
Speed is not just an operational metric; it is a risk selection strategy.
Slow operations directly lead to adverse selection in an MGA’s book of business.
Unlike previous generations of automation (like OCR) that required rigid templates, Agentic AI acts as an autonomous teammate that executes end-to-end workflows.
In the context of MGA operations, an AI Agent doesn't just transcribe text; it performs the cognitive duties of a junior underwriter without human intervention:
Modern Agentic AI solutions, such as those provided by Brisc, can reduce the entire intake workflow—from email receipt to quote-ready data in the workbench—to under 60 seconds.
No. The latest "Zero Disruption" Agentic AI models are designed to deploy without complex PAS migrations or API integrations.
Because the AI intercepts existing email workflows, it requires no behavioral change from brokers and minimal IT lift from the MGA. This allows organizations to shift from manual triage to automated, 60-second intake in a matter of weeks, rather than the 12-18 month timelines typical of traditional insurance software implementations.
See Brisc in Action
If you want to see how the Brisc Submissions Agent processes real broker submissions in under 60 seconds, explore the full workflow here.