Insurance quoting software: property intelligence at every quote
Replace ZIP code assumptions with parcel-level property data. Nearmap insurance quoting software helps P&C carriers quote accurately with better loss ratios.
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Insurance quoting software is the system a property and casualty (P&C) carrier, managing general agent (MGA), or broker uses to rate a property risk and return a premium at the point of inquiry. The accuracy of that premium depends less on the rating engine than on the property data feeding it, because a quote priced from a declared roof age and a ZIP code average describes a property that may not exist.
This article covers what separates modern insurance quoting software from legacy rating workflows, how property intelligence reaches the quote through Betterview and core system integrations, what remote property evidence changes for brokers, and how state regulation governs the imagery behind a quoted price.
What makes modern insurance quoting software different?
Quoting software has performed the same core function for decades, taking an address and a set of coverages, applying a filed rating plan, and returning a premium. The change sits in the property information available at that moment of decision, which now includes measured attributes rather than declared ones.
Prefilled property attributes replace applicant-declared ones, so quoting software retrieves measured roof and structure data from a property intelligence provider and populates the submission for validation. Angela Orbann, National Property Lead and VP of Personal Insurance at Travelers, says the approach “brings ease of quoting”, letting teams prefill information for quick validation “instead of a lot of manual entry during the quoting process”.
ZIP code vs. property-level risk data
ZIP code-based rating assigns every property inside a geographic boundary the same hazard exposure, which is defensible for perils that behave geographically and unreliable for the condition of an individual structure. Roof condition, vegetation overhang, and outbuilding exposure vary house by house within a single territory.
Two homes on the same street can carry a four-year-old architectural shingle roof in sound condition and a 22-year-old roof with staining and missing shingles. Territory-average rating prices both identically, which produces premium leakage on the deteriorated risk and an uncompetitive quote on the sound one.
The Nearmap insurance quoting solution changes what the rating plan can see at first quote, supplying pre-processed AI detections, a Roof Spotlight Index, and internal policy data in a single response. Pricing then reflects the condition of the specific parcel rather than the average of its neighbors.
AI-powered property attributes at the point of quote
AI-derived property attributes are measurements that computer vision models extract from aerial imagery, covering roof material, roof shape, roof condition, building footprint, pool presence, solar panels, debris, and vegetation proximity. Nearmap AI produces more than 130 detections and scores from imagery captured at 1.57-2.95 in/4.4-7.5 cm or better ground sample distance (GSD), refreshed up to three times a year across 88.5% of the US population.
Betterview analyzes imagery and returns property insights in under a second, which is inside the tolerance of a real-time rating call. Once a quote is bound, any subsequent attributes are handled during renewal rather than pricing. That’s the practical distinction between property intelligence at quote and AI underwriting applied later in the policy lifecycle.
Nearmap for insurance quoting: how it works
Betterview integration for carrier quoting workflows
Betterview property intelligence is the Nearmap risk application for P&C insurers, combining high-resolution aerial imagery, AI detections, and third-party datasets in one interface. Underwriters see the imagery, the detections that generated a score, and the reason a property was flagged, which supports a defensible pricing decision rather than an unexplained output.
Automated flagging applies custom rules to AI attributes, Roof Spotlight Index scores, peril scores, and internal policy data to identify which submissions need review. Continuous Monitoring reports detected change on an insured property, and Partner Connect adds more than 2,500 third-party data points per property, covering replacement cost, permit data, and property-specific perils.
Eric W. Neely, Vice President of Commercial Lines at Stillwater, reports that the quoting process now includes a fully remote view of property risk in Betterview rather than relying on physical inspections, and describes the resulting transparency as a benefit shared with agents and policyholders.
COPE data for residential and commercial properties
COPE data refers to construction, occupancy, protection, and exposure, the four characteristics that underpin commercial and residential property risk evaluation. Gathering it traditionally required physical inspections and fragmented data sources, and property intelligence now supplies a substantial portion of it from imagery and AI analysis:
- Construction — roof material, condition, and geometry, verified building footprint for replacement cost, and unpermitted outbuildings or additions
- Occupancy — commercial or residential use inferred from zoning layout, parking, and signage, plus vacancy indicators such as overgrown vegetation
- Protection — defensible space for wildfire resilience, proximity to fire stations and hydrants, and access routes that could obstruct emergency vehicles
- Exposure — elevation and drainage for flood, vegetation and slope for wildfire, materials vulnerable to hail and wind, and property clustering
Full detail on each element appears in the Nearmap account of COPE insights with property intelligence. Consistent COPE attributes across a book also make quoted premiums comparable, which reduces the variation that arises when different inspectors assess similar properties differently.
Property risk assessment in real time
Property risk assessment at the point of quote combines measured attributes with modeled peril scores to produce a single view of expected loss. The Roof Spotlight Index (RSI) scores each roof on a property from 1 to 100, and pre-filed Vulnerability Scores and claims predictors grade survivability for hail, hurricane, wind, and wildfire.
Roof Age Gen2 identifies replacement dates to within one year at 95% accuracy, which matters for the states that restrict how roof age alone can be used in an underwriting decision. Nearmap maintains more than 60 ready-to-use rate filings across 37 states, so carriers referencing those filings shorten their own approval process when they introduce a new attribute into a rating plan.
Quoting software for insurance brokers
Faster quote turnaround without physical site visits
Brokers and MGAs quote against carrier appetite, and a submission that stalls pending an inspection usually loses to one that does not. Remote property evidence removes the inspection from the front of the process, leaving it available for the minority of risks where imagery is inconclusive.
Arden Insurance Services minimized physical inspections at quoting and reduced the average time spent underwriting a property by 9%, adding more than three underwriting submissions per week. Each of those submissions covers upwards of 20 buildings in a homeowners association community.
Binding decisions backed by aerial evidence
Aerial evidence attached to a submission gives a broker something to show rather than something to assert, which shortens the exchange with both the carrier and the applicant. Imagery and detections travel with the file, so the basis of the quoted price remains visible at bind and at first renewal.
An Insurance Research Council survey of US homeowners found that 60% have some awareness that insurers use aerial imagery while 40% know little or nothing about it, and that homeowners familiar with underwriting applications are nearly twice as likely to consider the resulting pricing fairer. Accuracy was the single largest concern at 31%, ahead of privacy at 24%, which places the recency and resolution of the underlying imagery at the center of the conversation an agent has at quote.
Guidewire PolicyCenter integration
Property data flow into PolicyCenter
Nearmap joined Guidewire PartnerConnect as a Solution Partner in 2021, and Guidewire systems now provide direct access to Betterview property intelligence from PolicyCenter (cloud and v10) and InsuranceNow. Underwriters open the full Betterview platform inside PolicyCenter through an iFrame served by the cloud-native Nearmap Accelerator, without leaving the policy workspace.
Betterview flags synchronize automatically with Guidewire Underwriting Issues for routing and decisioning, and Betterview PDF reports save directly to the Guidewire File portal. The accelerators are Guidewire-validated and pre-built, which removes development work and keeps compatibility through Guidewire updates. Home, commercial, and farm and agriculture lines are supported across North America and Australia.
API access for custom carrier platforms
Carriers running proprietary or in-house rating platforms consume the same intelligence through the Nearmap data API, which returns imagery and AI attributes on demand inside an existing policy workflow. Single sign-on, an analytics interface, external data warehouse delivery, and downloadable PDF reports cover the surrounding requirements, and the integrations and APIs documentation sets out the available methods.
Integration depth is worth treating as the deciding criterion when a carrier compares property data providers, because intelligence delivered inside the quoting workflow gets applied to every submission while intelligence held in a separate application gets applied unevenly.
Improving quote accuracy and loss ratios
US homeowners insurance recorded a net combined ratio of 88.1 in 2025, the lowest in more than a decade, aided by easing replacement cost pressure and earlier pricing discipline. The Insurance Information Institute (Triple-I) forecasts replacement costs re-accelerating through 2028 and eventually outpacing overall US inflation, which returns pressure to the accuracy of the insured values and property attributes set at quote.
Arden Insurance Services: reduced underwriting time
Arden Insurance Services is an MGA insuring residential condominium associations across the Western United States and parts of the Midwest, and it relied on post-bind physical inspections to confirm underwriting decisions during a period of rapid growth. Betterview replaced that sequence with a granular view of property condition available before the quote, drawn from computer vision models, the Roof Spotlight Index, and Partner Connect datasets.
Results within several months included a 5.5% loss ratio improvement, a 9% reduction in the average time spent underwriting a property, and more than three additional underwriting submissions per week. Louise Tebelekian, Chief Underwriter at Arden, attributes part of the gain to seeing the specific reasons, sizes, and locations behind each score, which improved communication between underwriters, agents, and the insured. The Arden Insurance Services case study documents the deployment.
Utica First: 77% reduction in inspection costs
Utica First cut average inspection costs by 77% per location after adopting Betterview for underwriting and claims, alongside a 42% reduction in its average inspection budget. Average inspection time fell from more than a month to 30 seconds, and the carrier identified damage predating first notice of loss using historical imagery and computer vision detections.
Shawn Kain, Chief Underwriting Officer at Utica First, reports that the platform is returning the investment within a year, which he describes as unusual for an insurtech partner.
Insurance regulations by state
State regulators increasingly specify how current imagery should be before it supports an underwriting or rating decision, which makes capture frequency a compliance input rather than a preference:
- The Colorado Division of Insurance holds that aerial imagery used for general underwriting and rating should be no more than 12 months old
- Georgia and Kentucky apply a 12-month limit to imagery supporting a nonrenewal, Kentucky extends that limit to cancellations and claim denials
- Rhode Island sets 15 months
- Indiana, Louisiana, and Vermont set 24 months
- California AB-1559 would bar an adverse decision based on an aerial image captured more than 180 days earlier, taking effect on July 1, 2027 if adopted
- A Massachusetts petition proposes a 12-month limit
Carriers quoting across multiple states therefore price against the strictest recency requirement in their footprint rather than a national standard.
As of September 14, 2026, 25 jurisdictions had adopted the National Association of Insurance Commissioners (NAIC) Model Bulletin on the Use of Artificial Intelligence Systems by Insurers, which governs AI use alongside the imagery rules. The bulletin requires a written artificial intelligence systems (AIS) program, ongoing validation and testing, and due diligence on third-party AI systems and data. Nearmap pre-files peril models and AI detections with state Departments of Insurance, and the current position for each state is tracked on the Nearmap summary of insurance regulations by state.