Practical analysis from the Perilarc team on appetite modeling, risk scoring, submission operations, and the regulatory frameworks shaping commercial P&C underwriting.
Configuring a commercial property appetite matrix requires more than a list of acceptable territories. We walk through structuring ISO class codes, TIV bands, and CAT zone overlays into an appetite model that producers can actually work with.
NAIC SBS and SERFF filings are a constant operational overhead for commercial lines carriers. This guide covers the submission data requirements, common field mapping errors, and how automated ACORD-to-SBS translation reduces manual rekeying.
Setting the right auto-decline and auto-refer thresholds is one of the highest-leverage configuration decisions in a commercial UW workbench. We explain how to calibrate routing logic against your appetite rules and loss history data.
Commercial auto is one of the most data-intensive commercial lines to underwrite correctly. This piece covers the key ACORD fields, Verisk PolicyAnalytics signals, and fleet composition variables that drive meaningful risk differentiation.
Managing General Agents have accumulated a mix of legacy policy admin tools, spreadsheet-based appetite management, and point solutions. We map the current MGA tech landscape and where underwriting intelligence platforms fit.
Commercial property and GL rates have been hardening for three consecutive years in many territories. For carriers and MGAs, the hard market is an opportunity — if appetite rules are tight enough to capture premium without adverse selection.
Cyber insurance underwriting has changed more in the past three years than most commercial lines have in a decade. We look at how appetite rules are evolving, what external data signals are now available, and where the gaps remain.
ACORD 126 submissions contain significantly more GL-specific fields than most carriers systematically use in their appetite screening. We walk through a structured approach to refining GL class code appetite rules using submission data analysis.
AIR Worldwide, RMS, and CoreLogic probabilistic CAT models have historically lived in a separate workflow from the commercial UW submission review. Connecting CAT exposure signals to the workbench at submission time changes the economics of CAT-exposed risk selection.
For commercial mid-market risks — $250K to $5M TIV — external data signals are thinner than for large accounts. We describe how carriers can build a loss-cost pricing signal from their own submission history combined with ISO industry class benchmarks.
