To access the Transaction Matching report, from the main menu click Reports, then go to Fuel, Diagnostics & Usage and click Transaction Matching.
Carefully read the accuracy disclaimer found on the Transaction Matching report page before using this report for disciplinary purposes.
This report is not used for electric vehicles.
The Transaction Matching report is an optional Zonar report. The primary purpose of this report is to identify and investigate possible fuel theft. The report is designed to work with WEX fuel cards, but is adaptable to other types of fuel cards and other types of generic transactional data. There are four major steps to running the Transaction Matching Report:
- Upload the CSV of fuel purchase data.
- Select the max allowable time and distance variance threshold values.
- Run the report for the desired target date.
- Investigate irregularities.
The report identifies two major categories for investigation:
- Excessive Time and/or Distance variance between where & when the CSV states fuel was purchased and where & when the GPS data states the fuel was purchased. Investigate all cases in which the Time / Distance value is null (empty or blank)
- No change in fuel level before and after refuel. Fuel tank level is based on a 0 to 255 scale. If the before and after fuel level after refueling is the same or less, this is an event that should be investigated further.
Select from the following filters to display only certain assets in the results:
|Clicking the drop-down menu will allow the user to select which petroleum products to filter for within the generated report.
|Select the range of dates, such as today, yesterday, last 7 days, last 30 days, and custom. When picking custom as a date range, a beginning and ending date must be selected in order to generate the report.
When generating this report, keep in mind the longer the date range, the longer it will take to generate the report.
|Asset Time Within
|Enter the maximum time variance that is acceptable between the CSV and GPS data. For example if you were to select 15 minutes, all time variance below 15 minutes would be listed, and all those above 15 minutes will be null/empty and should be investigated.
|Asset Distance Within
|Enter the maximum Distance variance that is acceptable between the CSV and GPS data. For example, if you were to select 150 feet, all distance variances less than 150 feet would be listed, and all those greater than 150 feet will be null/empty and should be investigated.
|When this box is checked, Asset Time Within and Asset Distance Within will be grayed out. We recommend having the Best Match check box selected for the best accuracy within the generated report.
The Best Match algorithm attempts to compensate for inaccuracy from the fueling station address in the CSV and time/date errors at the fueling pumps. See the logic diagrams below for an explanation of this filter.
|Displays the assigned number to identify an asset. Clicking on the asset number itself will filter to that specified asset. Clicking on the Asset Info icon will display the available asset information.
|Displays the product that was purchased.
|Purchase Date (CSV)
|Displays the date and time of when the purchase was made.
|Stop Date (GPS)
|Displays the date and time of the closest matching stop motion event.
|Displays the merchant name associated with the transaction.
|Displays the address of the merchant. Clicking on the magnifier icon will bring the user to a pop up window and show a GPS point of where the transaction took place on a map.
|Displays time variance between CSV and GPS data. All Null (empty/blank) values that should be investigated are outside your set maximum allowable variance.
|Displays distance variance between CSV and GPS data. All Null (empty/blank) values that should be investigated are outside your set maximum allowable variance.
This report utilizes straight-line distance calculation based on the WEX and Motion Stop Lat/Lon information.
|Displays the odometer reading of the asset at the motion stop.
|Displays how much fuel the asset had at the motion stop event.
|Displays how much fuel the asset has after the next motion start event. The fuel scale is from 0 (empty) to 255 (full).
The fuel after calculation takes the maximum reading on the asset over the 10 GPS points following the power on event immediately after the motion stop event.
Before the user can access the data from this report, they must first import their data with a CSV file that contains WEX or other transactional data.
- Click on Import. It is located underneath Apply.
- After clicking import, a pop up dialogue box will appear. The drop-down menu will have three formats that the user can choose to import their data with, these are WEX, Zonar, and Zonar Extended.
- Clicking Sample located to the right of the drop-down menu will download a template with the required columns already in place, letting the user easily enter in the data that is needed.
When downloading a template, there will be an example in the first row that should be deleted prior to entering the new data.
- When the user is ready to import a CSV file, click Browse.
- Navigate to the directory that contains the CSV file for import and select the file.
- After the file has been selected, the file name should be shown in the dialogue box located to the right of browse. When the user is ready, click Submit.
When uploading the data for the report, after a successful upload, the user will not need to re-upload the CSV file in order to generate the report. If the data does not successfully upload, they must correct the fields prior to re-uploading the CSV file.
- If errors occurred, a CSV file will automatically download. A new column in the first position will display one of the following error messages:
Invalid Asset The asset specified in the CSV does not exist in Ground Traffic Control. Missing Merchant Data One of the following pieces of address information for the merchant was left out of the transaction; address, locality, district, postal code, or country. Invalid Merchant Country The country must be listed as two characters (A-Z). Invalid Merchant State The state must be listed as two characters (A-Z). Invalid Merchant Postal Code If the country is listed as the United States or Canada, it will validate the zip code per the US or CA postal standards. Invalid Product The product must have a value in the field and must be 10 characters or fewer. If the product type is unknown, we suggest entering “Unknown.” Invalid Latitude/Longitude If one is specified, then both latitude and longitude need to be present. Transaction Date Time Is Missing or Invalid A transaction date and time must be present. Duplicate Transaction An identical transaction is in the same CSV file that is being imported. Merchant Geocode Failed Latitude and longitude coordinates were not present in the import when adding an address. The first time an address is added, latitude and longitude must be present. Once added, future imports will not require latitude and longitude.
- After correcting the errors found in the CSV file, remove the first column and re-upload the corrected file. While it’s possible to edit the original CSV file and re-import it, a new error file will be downloaded with those transactions that were previously imported successfully shown as Duplicate Transaction.
Best Match Overview
The best match check box, when selected, will disable the option for Asset time within and Asset distance under the filtering option and instead will run an algorithm to determine the best matched vehicle stop motion for the transaction.
The best match algorithm will create 23 time segments to cover a 12-hour window around the transaction time. For each segment, it finds the closest vehicle stop motion event. Note that a time segment may not contain a stop motion event.
Next, the algorithm will find the four vehicle motion stop events closest to the transaction merchant location. The algorithm utilizes the Lat/Lon obtained from WEX and compares it to the Lat/Lon of the motion stop recorded in Ground Traffic Control.
Finally, of the four vehicle stop motion events, it will then select the closest point within the shortest amount of time from the motion stop event. Here, the algorithm utilizes “straight line” distance calculations to determine the closest stop motion.