You suspect leakage but cannot prove it
Collection that never quite matches ridership, on routes that should be profitable and somehow are not.
Transport & mobility
Fare reconciliation & revenue assurance
A finance-facing dashboard that sets the passengers your sensors counted against the fares your ticketing recorded, trip by trip and unit by unit.
Where it hurts today
The problem this is built for
Auditing everything audits nothing
Without severity ranking, the investigation list is too long for anyone to actually work through.
One-off variance looks like a pattern
And a real pattern looks like noise, until the same route on the same shift repeats week after week.
Findings that do not survive review
A flag with no source counts, footage reference or timestamps gets argued away.
How it works
Four steps, in this order
- 01
Count the passengers
Automatic counting supplies the ridership figure the reconciliation compares against.
- 02
Import the fare record
Collected fare comes from your ticketing or POS, by API where one exists and by scheduled import where it does not.
- 03
Compare per trip
Expected fare from counted passengers is set against collected fare, flagged by bus and by trip.
- 04
Tier and investigate
Variance beyond tolerance is tiered by severity so your team works the handful of trips that warrant it.
What gets installed
Hardware and software
- Passenger counting system
- Fare reconciliation dashboard
- API integration to ticketing or POS
Exact models are specified against your site. Read range, tag material and mounting all change the answer.
What you get back
Outcomes
- Trip-level variance instead of a monthly total
- Patterns by route, shift and vehicle
- An audit trail each finding can stand on
- The measurement that usually pays for the system
Scope this against your own site
Send us the operation, the site and what is going wrong in it. We come back with a scope and a number, or we tell you it is not a fit.