What is DAFT?
The Data Analysis for Fraud and Theft (DAFT) process combines data from several sources to focus auto theft investigations on high probability targets and make efficient use of law enforcement resources. The FBI’s Uniform Crime Report shows that about 1.3 million vehicles were stolen within the United States in 2002, with only 14 percent of those resulting in identification of the criminal and/or arrest. Stolen vehicles can be successfully, and profitably, reintroduced into the market if they are renumbered and obtain valid title documentation. Obtaining the valid title document in the United States is key to the ability of the criminal to profit from the crime. The estimated total value of all vehicles stolen in the United States is $8.4 billion per year.
How does DAFT work?
What are the results?
Give us your feedback on the best practice!
The NMVTIS Law Enforcement Committee has created a DAFT Best Practice document and would like feedback from the state titling and law enforcement agencies. The document aims to provide enough information and direction so that experienced theft investigators can follow the guidelines in the best practice and successfully organize a sweep and recover for vehicles. AAMVA would like to receive your comments in the following areas:
- Is the information in the document useful?
- Have we included information that is not needed?
- Have we omitted information that is needed?
- Is the format easy to follow for a new user?
- Are there changes that would make the process more clear or the document easier to use?
- Are you willing to beta test the process? As a beta tester, your organization would follow the procedure and give us feedback on whether the best practice provides enough information to allow an experienced investigator to get the data, analyze it, prepare a sweep team, and recover property.
Please send comments to AAMVA’s Vehicle Systems department.