Annual Odometer Fraud Cases in States


Carfax reports that odometer fraud cases reach up to 200,000 annually in the United States. This announcement is done by the company that specializes in vehicle history reports. It runs huge number of Vehicle Identification Numbers (VINs). It also operates over 12 billion pieces of information in its database.

Recently Carfax researchers have found that there are nearly 1 million vehicles on the road which have rolled-back odometers. It’s the type of a fraud when the vehicle has got much lower mileage than the dealer actually informs. In the United States Odometer Fraud Cases also referred to busting miles.

 The buyers typically spend a huge amount of money on vehicle repairs and other related technical problems. Therefore, a new car costs much cheaper.

According to Carfax, rolled-back vehicle odometers cost consumers more than $760 million annually. This is because of the already lost value of the vehicle and its unexpected repairs.

Whenever, vehicle owners face an odometer fraud case, similarly they face the  loses thousands of dollars on the car that they could buy much more cheaper.

Although when the digital odometers have entered the market, rolling back the vehicle odometer become easier. Currently, there are on-line tools that allow fraudsters roll back the odometer in few seconds. The acknowledgment about the tricks the dealers may use can  to let them down.  They should never rely on digital odometers.

What to Do with Odometer Fraud Cases

After all, if you are a buyer of a used car and want to avoid such further problems with the car, you should be very attentive. Always ask the dealers for service records. Look at the vehicle’s wear. Tear to be consistent with the odometer reading. Actually, you need to buy a vehicle from a trusted dealer or seller. You should have the vehicle inspected by the impartial mechanic. They will explore vehicle history report, etc. These are all tools that can help you with the right choice of vehicle without having waste of money and time.