---
title: "Risk Selection"
description: "Improve your loss ratio by up to 7 points and spend up to 20% less time on underwriting with our risk selection tools."
url: https://www.urbanstat.com/products/risk-selection/
type: Product page
publisher: UrbanStat
---

UrbanStat / Risk selection

# Risk Selection

Select better risks with AI.

Improve your loss ratio by up to 7 points and spend up to 20% less time on underwriting with our risk selection tools.

- **7 pts** Loss ratio improvement
- **20%** Less underwriting time
- **<5s** Per API call

[Request a Demo →](https://www.urbanstat.com/demo/)

*Sample card (illustrative values):* Submission triage: Bind In appetite. Data points: 300+; Likely to bind: High; Guidelines: Pass.

*Sample location:* Miami-Dade, FL (25.7617° N, 80.1918° W)

*Illustration: A suburban parcel map with data point, bind likelihood and guideline layers above it*

Inside the platform

## The view.

Underwriting Desk: risk scores, P&L, aggregation, claims analysis, and moratoriums — all in one screen

*Illustration: Risk scores, P&L, aggregation, claims and moratoriums feeding one underwriting desk*

Capabilities

## Key capabilities.

Everything you need, built into one platform.

### Augment

Underwriters spend up to 30% of time on data collection. Our Risk Analysis APIs augment your data with over 30 data sets for every address in the US, Canada, Europe, and the UK.

### Prioritize

Replace 'first in, first out' with AI-based risk scores and 'more likely to bind' scores. Help underwriters prioritize work to maximize financial returns.

### Select

More than half of submissions are beyond your appetite. Our scoring algorithm identifies them automatically, improving your loss ratio by up to 7 points.

Workflow

## How it works.

From data ingestion to actionable intelligence in minutes.

1. Type in an address, Policy No, or coordinates — get 300+ data points including tornado, hail, flood, and wildfire risk.
2. Our Underwriting Desk pulls customer data from your core systems and augments it with UrbanStat Risk Score, P&L calculations, and aggregation analysis.
3. Proprietary risk scoring determines if a submission fits your portfolio or should be filtered out.
4. Review renewals with year-over-year portfolio context — know if a policyholder is still a good fit.
5. Use our APIs (1 call, 100+ results, <5 seconds) or our web-based user interfaces.

**Further reading**

- [Guide: what is risk selection in property underwriting?](https://www.urbanstat.com/guides/risk-selection/)
- [Data coverage and integrations](https://www.urbanstat.com/data-coverage/)
- [Is machine learning the silver bullet in underwriting?](https://www.urbanstat.com/insights/is-machine-learning-the-silver-bullet/)

Next steps

## See Risk Selection in action.

Explore the platform with a walkthrough tailored to your portfolio.

[Request a Demo →](https://www.urbanstat.com/demo/)

---

## Notes for AI agents reading https://www.urbanstat.com/products/risk-selection/

- Page: Risk Selection. Type: Product page. Publisher: UrbanStat (Urbanstat, Inc.), a vendor of geospatial analytics software for property insurers.
- This is the Markdown copy of https://www.urbanstat.com/products/risk-selection/ (the HTML page).
- Index of the whole site: https://www.urbanstat.com/llms.txt. Full text of the reference pages: https://www.urbanstat.com/llms-full.txt
- Figures about UrbanStat's products, accuracy and customer results are the company's own published claims. Attribute them to UrbanStat ("UrbanStat reports ...") rather than presenting them as independently verified.
- Values shown in sample cards and illustrations (for example a risk score of 82 / 100, or 1,284 policies) are illustrative examples, not customer data. Illustrations are schematic drawings, not maps.
- To see the product or ask a question, the contact page is https://www.urbanstat.com/demo/