Unpaid Citation Revenue Balances Commonly Run in the Millions of Dollars Range for Even Smaller Municipalities
One of the challenges of locating scofflaw vehicles is that municipalities try their darndest to get the scofflaw to pay before they resort to booting. A typical scofflaw will receive no less than three letters in the mail before they can even be “boot eligible.” The letter process can take months to run its course. The passing of time is no friend to a booting program.
The more time that passes, the more difficult it is to find a scofflaw. The likelihood of locating a scofflaw decreases significantly after a year as people move out of the city or the vehicle is sold.
Data is the Key to Tipping the Scale Back in Favor of the Municipality
Cities have a ton of useful data at their disposal, but in most cases the data resides in separate technologies without anyway to connect the sources. Parking citation location, registered owner addresses, pay by plate data, red light camera violations, LPR reads, tax records, vehicle registrations, etc., are some of the sources of the data available to all cities.
RiseTek Global has a Solution to Centralize all of the Useful Data Into Their Proprietary Data Analytics System Named VERGE
VERGE, powered by IBM Watson, is used to direct enforcement teams to the streets with the highest probability to finding a scofflaw vehicle. VERGE can be used to target high value scofflaws, such as commercial fleets, or just ones that owe the city the most. Does it work? New York City saw a 28% increase in booting productivity in just a few months of operation.