With 15+ years of accumulative national cargo theft data, that is updated daily, Verisk data scientists developed a machine learning solution that powers risk scoring before a trip starts based on various factors such as: type of commodity hauled, value, origin and destination, travel distance, day of the week, truck stop risk, holidays, seasonality, etc.
The RouteScore model assesses risks related to theft along a specific route. The risk score has a range of 0-100, with 100 being the highest risk. It is designed to help supply chain and insurance companies better understand their risk of cargo theft and provide them decision making support to better protect cargo from being stolen.
Provides tangible insight from historical theft trends
Allows you to make data-driven decisions
Illustrates best practices and give you and your customers a comfort level
Mitigate cargo theft insurance claims and stabilize your premium
The scoring algorithm evaluates over 15 critical data points to provide accurate cargo theft risk assessments, seamlessly integrated into your platform. Key factors include commodity type, cargo value, origin, destination, length of haul, day of the week, time of year, risky truck stops along the route and more.
The RouteScore solution offers two tailored solutions to assess cargo theft risk: an API version and a standalone user interface.
Designed for large organizations managing high shipment volumes, the API integrates seamlessly into existing systems, providing automated, real-time cargo theft risk score before tendering to carriers or drivers. This integration enables companies to proactively implement security measures, optimize routing, and make informed decisions to mitigate potential losses.
Ideal for smaller companies needing occasional route risk analyses, this user-friendly tool provides visual insights into cargo theft risks. Users input shipment details to receive a risk score and a map of potential threats. It's beneficial for organizations that don't need daily assessments but seek detailed analyses for select shipments, aiding strategic planning without extensive system integration.
In summary, the API version is suited for large-scale operations requiring automated, high-frequency risk assessments, while the standalone interface caters to organizations needing detailed, visual analyses on a less frequent basis.
Both versions empower companies to determine and deploy appropriate security measures for high-risk loads, enhancing overall supply chain security.