Scout's crime analytics are built entirely in-house. 

We start by collecting the raw crime data from all 18,000 law enforcement agencies in the United States. We then assign these reported crimes from each of these law enforcement agencies to the specific local communities the agency covers, and hence in which community the crimes have occurred, using a custom relational database that our team built from the ground up. 

This method provides a powerful, uniquely accurate accounting of the complete number and types of crimes that truly occur within any city or town, not just crimes reported by a single municipal agency.

Once we have this modified set, we build upon it, producing sub-zip code crime hazard data with risk indices for violent crime, property crime, motor vehicle theft, crime density, and more. We then develop algorithms to statistically estimate the incidences of both violent and property crimes for each neighborhood in America. 

The resultant formulae produce numbers of crimes and crime rates for neighborhoods with upwards of 90% accuracy. We deploy 80 proprietary formulas to increase the accuracy of our predictions, and apply them based on city or town characteristics to produce the best model fit in each case. This method produces the best crime risk information for every neighborhood in America. We also go extra lengths to produce address-specific crime risk data, available on with custom heat maps at 10-meter resolution.